Files
windmill/system_prompts/generate.py
hugocasa e80c62b958 docs(cli): improve generate-metadata guidance, fix description parser (#9635)
* docs(cli): improve generate-metadata guidance, fix description parser

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* docs(cli): surface dependency version bumps after generate-metadata

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* docs(cli): explain generate-metadata scope, import cascade, and --dry-run troubleshooting

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-17 14:08:50 +00:00

2639 lines
94 KiB
Python

#!/usr/bin/env python3
"""
Generate system prompts documentation from SDKs and OpenFlow schema.
This script:
1. Parses TypeScript SDK to extract function signatures
2. Parses Python SDK using Python's ast module
3. Parses OpenFlow YAML schema
4. Generates markdown files in sdks/ and schemas/
5. Assembles complete prompts and generates TypeScript exports in generated/
Usage:
python generate.py
python generate.py --plugin-dir /path/to/windmill-claude-plugin
python generate.py --context7-dir /path/to/windmill-cli-docs
"""
import argparse
import ast
import copy
import json
import re
import shutil
from pathlib import Path
import yaml
from utils import (
# Path constants
SCRIPT_DIR,
TS_SDK_DIR,
PY_SDK_PATH,
OPENFLOW_SCHEMA_PATH,
BACKEND_OPENAPI_PATH,
OUTPUT_SDKS_DIR,
OUTPUT_GENERATED_DIR,
OUTPUT_CLI_DIR,
OUTPUT_SKILLS_DIR,
OUTPUT_SCHEMAS_DIR,
CLI_GUIDANCE_DIR,
CLI_MAIN,
CLI_COMMANDS_DIR,
# Language metadata
LANGUAGE_METADATA,
TS_SDK_LANGUAGES,
PY_SDK_LANGUAGES,
# Schema mappings
SCHEMA_MAPPINGS,
# String/file utilities
clean_jsdoc,
clean_params,
escape_for_ts,
read_markdown_file,
# Parsing utilities
extract_balanced,
extract_return_type,
parse_default_imports,
extract_options,
# Schema utilities
extract_cli_schema,
format_schema_for_markdown,
format_schema_as_json,
)
# =============================================================================
# TypeScript SDK Parsing
# =============================================================================
def extract_ts_functions(content: str) -> list[dict]:
"""Extract exported function signatures from TypeScript SDK."""
functions = []
seen_names = set()
# Pattern to find export function declarations (with or without JSDoc)
# Captures JSDoc if present, then the function declaration
pattern = re.compile(
r'(?:(/\*\*(?:[^*]|\*(?!/))*\*/)\s*)?' # Optional JSDoc comment
r'export\s+(async\s+)?function\s+(\w+)\s*' # export [async] function name
r'(<[^>]+>)?\s*', # optional generic
re.MULTILINE
)
for match in pattern.finditer(content):
jsdoc_raw, is_async, name, generic = match.groups()
if name in seen_names:
continue
# Find the opening parenthesis for parameters
pos = match.end()
while pos < len(content) and content[pos] in ' \t\n':
pos += 1
if pos >= len(content) or content[pos] != '(':
continue
# Extract balanced parameters
params, paren_end = extract_balanced(content, pos, '(', ')')
if paren_end == -1:
continue
# Extract return type (handles multi-line types like Promise<{...}>)
return_type, _ = extract_return_type(content, paren_end + 1)
if not return_type:
return_type = 'Promise<void>' if is_async else 'void'
docstring = clean_jsdoc(jsdoc_raw) if jsdoc_raw else ''
seen_names.add(name)
functions.append({
'name': name,
'generic': generic or '',
'params': clean_params(params),
'return_type': return_type,
'async': bool(is_async),
'docstring': docstring
})
return functions
def extract_ts_types(content: str) -> list[dict]:
"""Extract exported type definitions from TypeScript SDK."""
types = []
# Pattern for exported type aliases
type_pattern = re.compile(
r'export\s+type\s+(\w+)\s*=\s*([^;]+);',
re.MULTILINE
)
# Pattern for exported interfaces
interface_pattern = re.compile(
r'export\s+interface\s+(\w+)\s*\{([^}]+)\}',
re.MULTILINE | re.DOTALL
)
for match in type_pattern.finditer(content):
name, definition = match.groups()
types.append({
'name': name,
'kind': 'type',
'definition': definition.strip()
})
for match in interface_pattern.finditer(content):
name, body = match.groups()
types.append({
'name': name,
'kind': 'interface',
'definition': body.strip()
})
return types
# =============================================================================
# Python SDK Parsing
# =============================================================================
def extract_py_functions(content: str) -> list[dict]:
"""Extract function signatures from Python SDK using AST."""
functions = []
seen_names = set()
try:
tree = ast.parse(content)
except SyntaxError as e:
print(f"Warning: Could not parse Python SDK: {e}")
return functions
def process_function(node):
"""Process a function node and add to functions list if not duplicate."""
# Skip private functions
if node.name.startswith('_') and not node.name.startswith('__'):
return
# Skip duplicates
if node.name in seen_names:
return
# Get docstring
docstring = ast.get_docstring(node) or ''
# Build parameter list
params = []
args = node.args
# Handle regular args
num_defaults = len(args.defaults)
num_args = len(args.args)
for i, arg in enumerate(args.args):
if arg.arg == 'self':
continue
param_str = arg.arg
if arg.annotation:
param_str += f": {ast.unparse(arg.annotation)}"
# Check if has default
default_idx = i - (num_args - num_defaults)
if default_idx >= 0:
default = args.defaults[default_idx]
param_str += f" = {ast.unparse(default)}"
params.append(param_str)
# Handle *args
if args.vararg:
params.append(f"*{args.vararg.arg}")
# Handle keyword-only args
for i, arg in enumerate(args.kwonlyargs):
param_str = arg.arg
if arg.annotation:
param_str += f": {ast.unparse(arg.annotation)}"
if args.kw_defaults[i]:
param_str += f" = {ast.unparse(args.kw_defaults[i])}"
params.append(param_str)
# Handle **kwargs
if args.kwarg:
params.append(f"**{args.kwarg.arg}")
# Get return type
return_type = ''
if node.returns:
return_type = ast.unparse(node.returns)
seen_names.add(node.name)
functions.append({
'name': node.name,
'params': ', '.join(params),
'return_type': return_type,
'docstring': docstring,
'async': isinstance(node, ast.AsyncFunctionDef)
})
# Process top-level functions and class methods (but not nested functions)
for node in tree.body:
if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)):
process_function(node)
elif isinstance(node, ast.ClassDef):
for item in node.body:
if isinstance(item, (ast.FunctionDef, ast.AsyncFunctionDef)):
process_function(item)
return functions
def extract_py_classes(content: str) -> list[dict]:
"""Extract class definitions from Python SDK."""
classes = []
try:
tree = ast.parse(content)
except SyntaxError:
return classes
for node in ast.walk(tree):
if isinstance(node, ast.ClassDef):
methods = []
for item in node.body:
if isinstance(item, (ast.FunctionDef, ast.AsyncFunctionDef)):
if not item.name.startswith('_') or item.name == '__init__':
docstring = ast.get_docstring(item) or ''
methods.append({
'name': item.name,
'docstring': docstring
})
classes.append({
'name': node.name,
'docstring': ast.get_docstring(node) or '',
'methods': methods
})
return classes
# =============================================================================
# CLI Command Parsing
# =============================================================================
# Reusable option pattern for CLI parsing. Matches both `.option(...)` and
# `.globalOption(...)` so subcommand-level global options surface in the docs.
OPTION_PATTERN = re.compile(
r'\.(?:option|globalOption)\(\s*"([^"]+)"\s*,\s*"([^"]+)"' # double-quoted
r'|'
r"\.(?:option|globalOption)\(\s*'([^']+)'\s*,\s*'([^']+)'", # single-quoted
re.MULTILINE | re.DOTALL
)
# A single JS string literal: double/single quoted or backtick. The other
# quote chars may appear inside (apostrophes inside a "..." string, etc.) and
# backslash escapes are consumed so a `\"` doesn't end the match early.
_STRING_LITERAL = (
r'"(?:[^"\\]|\\.)*"'
r"|'(?:[^'\\]|\\.)*'"
r'|`(?:[^`\\]|\\.)*`'
)
def _unquote_js_string(literal: str) -> str:
"""Drop the surrounding quotes of a JS string literal and unescape the
escapes that show up in command descriptions."""
body = literal[1:-1]
return (
body.replace('\\\\', '\x00')
.replace('\\n', '\n')
.replace('\\t', '\t')
.replace('\\"', '"')
.replace("\\'", "'")
.replace('\\`', '`')
.replace('\x00', '\\')
)
def extract_description(section: str) -> str | None:
"""Extract the text of the first chained `.description(...)` call.
Handles double/single-quoted and backtick strings (a quote of one kind may
appear inside a string delimited by another — e.g. an apostrophe inside a
"..." description), backslash escapes, and `"a" + "b"` concatenation across
lines. Returns None when `.description(` is absent or its argument is not a
string literal (e.g. a variable), matching the previous empty-description
behavior. Using `[^"\\']+` here instead would silently drop any description
containing an apostrophe.
"""
m = re.search(
r'\.description\(\s*((?:' + _STRING_LITERAL + r')(?:\s*\+\s*(?:' + _STRING_LITERAL + r'))*)',
section,
re.DOTALL,
)
if not m:
return None
parts = re.findall(_STRING_LITERAL, m.group(1), re.DOTALL)
return ''.join(_unquote_js_string(p) for p in parts).strip() or None
def parse_command_block(content: str, file_path: Path | None = None) -> dict:
"""
Parse a Cliffy Command() definition block and extract metadata.
Returns a dict with: description, options, subcommands, arguments, alias
If file_path is provided, imported subcommands will be resolved by parsing
the imported files.
"""
result = {
'description': '',
'options': [],
'subcommands': [],
'arguments': '',
'alias': ''
}
# Find the command block
command_match = re.search(
r'(?:const\s+command\s*=\s*)?new\s+Command\(\)([\s\S]*?)(?=export\s+default)',
content
)
if not command_match:
return result
block = command_match.group(1)
# Find where subcommands start
first_subcommand_pos = block.find('.command(')
if first_subcommand_pos == -1:
first_subcommand_pos = len(block)
top_section = block[:first_subcommand_pos]
# Extract main description
main_desc = extract_description(top_section)
if main_desc:
result['description'] = main_desc
# Extract alias
alias_match = re.search(r'\.alias\(\s*["\']([^"\']+)["\']\s*\)', top_section)
if alias_match:
result['alias'] = alias_match.group(1)
# Extract top-level options (before any .command() or .action())
top_section_until_action = re.split(r'\.action\(', top_section)[0]
result['options'] = extract_options(top_section_until_action, OPTION_PATTERN)
# Extract top-level arguments
args_match = re.search(r'\.arguments\(\s*["\']([^"\']+)["\']\s*\)', top_section)
if args_match:
result['arguments'] = args_match.group(1)
# Parse imports if we have a file path (for resolving imported subcommands)
imports = parse_default_imports(content) if file_path else {}
# Extract subcommands
subcommand_sections = re.split(r'(?=\.command\()', block)
for section in subcommand_sections:
# Second arg is either a quoted description, a bare identifier (imported
# command, e.g. `.command("app", app)`), or a more complex expression
# like `someWrapper(new Command()...)` — the `[^)]+` fallback covers
# the last case by matching up to the next `)`.
#
# Two subtleties:
# - The quoted-string alts are tried first so a description containing
# `(` like "(psql, DBeaver)" isn't truncated by the `[^)]+` fallback.
# - The trailing `,?` accommodates the prettier-style `\n )` close
# paren that follows a comma. Without it, the quoted alt would
# succeed but the outer `\s*\)` would fail, forcing a backtrack to
# `[^)]+` and producing a truncated description with a trailing `",`.
cmd_match = re.match(
r'\.command\(\s*["\']([^"\']+)["\']\s*'
r'(?:,\s*("(?:[^"\\]|\\.)*"|\'(?:[^\'\\]|\\.)*\'|[^)]+))?'
r'\s*,?\s*\)',
section,
)
if not cmd_match:
continue
# Explicit source marker for backwards-compatible CLI commands that
# should not be suggested in generated system prompts.
if '@deprecated' in section:
continue
# Hidden commands (Cliffy .hidden()) are internal — invoked by other
# Windmill components, not users — and must not surface in the
# generated agent system prompts or help.
if '.hidden()' in section:
continue
cmd_name = cmd_match.group(1)
second_arg = cmd_match.group(2).strip() if cmd_match.group(2) else ''
# Check if second arg is a string (description) or a variable (imported command)
is_string_desc = second_arg.startswith('"') or second_arg.startswith("'")
if is_string_desc:
cmd_desc = second_arg.strip('"\'')
elif second_arg and second_arg in imports and file_path:
# Imported command - resolve and parse the imported file
import_path = imports[second_arg]
if import_path.startswith('./') or import_path.startswith('../'):
imported_file = (file_path.parent / import_path).resolve()
if imported_file.exists():
try:
imported_content = imported_file.read_text()
imported_cmd = parse_command_block(imported_content, imported_file)
result['subcommands'].append({
'name': cmd_name,
'description': imported_cmd.get('description', ''),
'arguments': imported_cmd.get('arguments', ''),
'options': imported_cmd.get('options', [])
})
continue
except Exception as e:
print(f" Warning: Could not parse imported command {second_arg}: {e}")
cmd_desc = ''
else:
cmd_desc = ''
# Check for description in chained .description() call
chained_desc = extract_description(section)
if chained_desc:
cmd_desc = chained_desc
# Check for arguments
args_match = re.search(r'\.arguments\(\s*["\']([^"\']+)["\']\s*\)', section)
cmd_args = args_match.group(1) if args_match else ''
# Extract options specific to this subcommand (before .action())
section_until_action = re.split(r'\.action\(', section)[0]
cmd_options = extract_options(section_until_action, OPTION_PATTERN)
result['subcommands'].append({
'name': cmd_name,
'description': cmd_desc,
'arguments': cmd_args,
'options': cmd_options
})
return result
def find_command_file(cmd_name: str) -> Path | None:
"""Find the command file for a given command name."""
standard_path = CLI_COMMANDS_DIR / cmd_name / f"{cmd_name}.ts"
if standard_path.exists():
return standard_path
return None
def extract_cli_commands() -> dict:
"""
Extract CLI command metadata from the CLI source files.
Returns a dict with global_options and commands.
"""
result = {
'version': '',
'global_options': [],
'commands': []
}
if not CLI_MAIN.exists():
print(f"Warning: CLI main file not found at {CLI_MAIN}")
return result
main_content = CLI_MAIN.read_text()
# Extract version
version_match = re.search(r'export\s+const\s+VERSION\s*=\s*["\']([^"\']+)["\']', main_content)
if version_match:
result['version'] = version_match.group(1)
# Extract global options from main.ts
global_opt_pattern = re.compile(
r'\.globalOption\(\s*["\']([^"\']+)["\']\s*,\s*["\']([^"\']+)["\']\s*\)',
re.MULTILINE
)
for match in global_opt_pattern.finditer(main_content):
flag, desc = match.groups()
result['global_options'].append({'flag': flag, 'description': desc})
# Extract command registrations from main.ts
cmd_reg_pattern = re.compile(
r'\.command\(\s*["\']([^"\']+)["\']\s*,\s*(\w+)\s*\)',
re.MULTILINE
)
inline_cmd_pattern = re.compile(
r'\.command\(\s*["\']([^"\']+)["\']\s*,\s*["\']([^"\']+)["\']\s*\)',
re.MULTILINE
)
registered_commands = []
for match in cmd_reg_pattern.finditer(main_content):
cmd_name = match.group(1).split()[0]
registered_commands.append(cmd_name)
# Process each registered command
for cmd_name in registered_commands:
cmd_file = find_command_file(cmd_name)
if cmd_file:
try:
cmd_content = cmd_file.read_text()
cmd_data = parse_command_block(cmd_content, cmd_file)
cmd_data['name'] = cmd_name
result['commands'].append(cmd_data)
except Exception as e:
print(f"Warning: Could not parse command file for {cmd_name}: {e}")
# Handle special inline commands from main.ts
for match in inline_cmd_pattern.finditer(main_content):
cmd_name = match.group(1).split()[0]
cmd_desc = match.group(2)
if cmd_name not in [c['name'] for c in result['commands']]:
result['commands'].append({
'name': cmd_name,
'description': cmd_desc,
'options': [],
'subcommands': [],
'arguments': '',
'alias': ''
})
return result
# =============================================================================
# Markdown Generation
# =============================================================================
def generate_cli_commands_markdown(cli_data: dict) -> str:
"""Generate markdown documentation from extracted CLI command data."""
md = "# Windmill CLI Commands\n\n"
md += "The Windmill CLI (`wmill`) provides commands for managing scripts, flows, apps, and other resources.\n\n"
# Global options
if cli_data.get('global_options'):
md += "## Global Options\n\n"
for opt in cli_data['global_options']:
flag = opt['flag']
desc = opt['description']
md += f"- `{flag}` - {desc}\n"
md += "\n"
# Commands
if cli_data.get('commands'):
md += "## Commands\n\n"
for cmd in sorted(cli_data['commands'], key=lambda x: x['name']):
md += f"### {cmd['name']}\n\n"
if cmd.get('description'):
md += f"{cmd['description']}\n\n"
if cmd.get('alias'):
md += f"**Alias:** `{cmd['alias']}`\n\n"
if cmd.get('arguments'):
md += f"**Arguments:** `{cmd['arguments']}`\n\n"
# Top-level options for this command
if cmd.get('options'):
md += "**Options:**\n"
for opt in cmd['options']:
md += f"- `{opt['flag']}` - {opt['description']}\n"
md += "\n"
# Subcommands
if cmd.get('subcommands'):
md += "**Subcommands:**\n\n"
for sub in cmd['subcommands']:
sub_name = sub['name']
sub_args = f" {sub['arguments']}" if sub.get('arguments') else ""
sub_desc = sub.get('description', '')
md += f"- `{cmd['name']} {sub_name}{sub_args}`"
if sub_desc:
md += f" - {sub_desc}"
md += "\n"
# Subcommand options
if sub.get('options'):
for opt in sub['options']:
md += f" - `{opt['flag']}` - {opt['description']}\n"
md += "\n"
return md
def generate_ts_sdk_markdown(functions: list[dict], _types: list[dict]) -> str:
"""Generate compact documentation for TypeScript SDK."""
md = "# TypeScript SDK (windmill-client)\n\n"
md += "Import: import * as wmill from 'windmill-client'\n\n"
for i, func in enumerate(functions):
if func.get('docstring'):
# Format docstrings with JSDoc /** */ syntax
md += "/**\n"
docstring_lines = func['docstring'].split('\n')
for line in docstring_lines:
md += f" * {line}\n"
md += " */\n"
async_prefix = 'async ' if func['async'] else ''
md += f"{async_prefix}{func['name']}{func['generic']}({func['params']}): {func['return_type']}"
md += "\n"
if i < len(functions) - 1:
md += "\n"
return md
def generate_py_sdk_markdown(functions: list[dict], _classes: list[dict]) -> str:
"""Generate compact documentation for Python SDK."""
md = "# Python SDK (wmill)\n\n"
md += "Import: import wmill\n\n"
for func in functions:
# Skip private functions
if func['name'].startswith('_'):
continue
docstring = func.get('docstring')
if docstring:
# Format multi-line docstrings with # prefix on each line
docstring_lines = docstring.split('\n')
for line in docstring_lines:
md += f"# {line}\n"
async_prefix = 'async ' if func['async'] else ''
return_annotation = f" -> {func['return_type']}" if func['return_type'] else ''
md += f"{async_prefix}def {func['name']}({func['params']}){return_annotation}\n"
md += "\n"
return md
def generate_ts_exports(prompts: dict[str, str]) -> str:
"""Generate TypeScript file that exports all prompts."""
ts = "// Auto-generated by generate.py - DO NOT EDIT\n\n"
for name, content in prompts.items():
escaped = escape_for_ts(content)
ts += f"export const {name} = `{escaped}`;\n\n"
return ts
# =============================================================================
# Schema File Generation
# =============================================================================
def generate_schema_files(cli_schemas: dict[str, dict]) -> dict[str, str]:
"""
Generate standalone YAML schema files for triggers and schedules.
Returns a dict mapping schema keys (e.g., 'http_trigger') to YAML content.
"""
print("Generating standalone schema files...")
# Ensure schemas directory exists
OUTPUT_SCHEMAS_DIR.mkdir(parents=True, exist_ok=True)
schema_yaml_content = {}
# Collect all schema types from SCHEMA_MAPPINGS
for skill_name, schema_types in SCHEMA_MAPPINGS.items():
for schema_name, file_suffix in schema_types:
if schema_name not in cli_schemas:
print(f" Warning: Schema '{schema_name}' not found, skipping")
continue
# Convert the schema to JSON Schema format
json_schema = format_schema_as_json(cli_schemas[schema_name])
if not json_schema:
print(f" Warning: Empty schema for '{schema_name}', skipping")
continue
# Convert to YAML
schema_yaml = yaml.dump(json_schema, default_flow_style=False, sort_keys=False, allow_unicode=True)
# Write to file
schema_file = OUTPUT_SCHEMAS_DIR / f"{file_suffix}.schema.yaml"
schema_file.write_text(schema_yaml)
# Store for return
schema_yaml_content[file_suffix] = schema_yaml
print(f" Generated {len(schema_yaml_content)} schema files")
return schema_yaml_content
# =============================================================================
# Workspace Tool Zod Schema Generation
# =============================================================================
WORKSPACE_TOOL_ZOD_SCHEMAS = [
('NewSchedule', 'scheduleRequestSchema'),
('NewHttpTrigger', 'httpTriggerRequestSchema'),
('NewWebsocketTrigger', 'websocketTriggerRequestSchema'),
('NewKafkaTrigger', 'kafkaTriggerRequestSchema'),
('NewNatsTrigger', 'natsTriggerRequestSchema'),
('NewPostgresTrigger', 'postgresTriggerRequestSchema'),
('NewMqttTrigger', 'mqttTriggerRequestSchema'),
('NewSqsTrigger', 'sqsTriggerRequestSchema'),
('GcpTriggerData', 'gcpTriggerRequestSchema'),
('AzureTriggerData', 'azureTriggerRequestSchema'),
('CreateVariable', 'variableRequestSchema'),
('CreateResource', 'resourceRequestSchema'),
]
WORKSPACE_TOOL_TRIGGER_SCHEMAS = [
('http', 'httpTriggerRequestSchema'),
('websocket', 'websocketTriggerRequestSchema'),
('kafka', 'kafkaTriggerRequestSchema'),
('nats', 'natsTriggerRequestSchema'),
('postgres', 'postgresTriggerRequestSchema'),
('mqtt', 'mqttTriggerRequestSchema'),
('sqs', 'sqsTriggerRequestSchema'),
('gcp', 'gcpTriggerRequestSchema'),
('azure', 'azureTriggerRequestSchema'),
]
WORKSPACE_TOOL_ZOD_OUTPUT_PATH = (
SCRIPT_DIR.parent
/ 'frontend'
/ 'src'
/ 'lib'
/ 'components'
/ 'copilot'
/ 'chat'
/ 'workspaceToolsZod.gen.ts'
)
def _resolve_schema_refs(schema: dict, backend_schemas: dict, openflow_schemas: dict, seen: tuple[str, ...] = ()) -> dict:
"""Resolve OpenAPI refs so json-schema-to-zod emits concrete enums/objects."""
if isinstance(schema, list):
return [_resolve_schema_refs(item, backend_schemas, openflow_schemas, seen) for item in schema]
if not isinstance(schema, dict):
return schema
if '$ref' in schema:
ref = schema['$ref']
ref_name = ref.split('/')[-1]
if ref_name in seen:
return {'type': 'object'}
source = openflow_schemas if 'openflow.openapi.yaml' in ref or ref_name not in backend_schemas else backend_schemas
ref_schema = source.get(ref_name)
if not ref_schema:
return {'type': 'object'}
resolved = _resolve_schema_refs(copy.deepcopy(ref_schema), backend_schemas, openflow_schemas, (*seen, ref_name))
for key, value in schema.items():
if key != '$ref':
resolved[key] = _resolve_schema_refs(value, backend_schemas, openflow_schemas, seen)
return resolved
return {
key: _resolve_schema_refs(value, backend_schemas, openflow_schemas, seen)
for key, value in schema.items()
}
def _ts_string(value: str) -> str:
return json.dumps(value)
def _zod_literal(value) -> str:
return json.dumps(value)
def _apply_zod_metadata(expr: str, schema: dict) -> str:
if schema.get('description'):
expr += f".describe({_ts_string(schema['description'])})"
if schema.get('nullable'):
expr += ".nullable()"
if 'default' in schema:
expr += f".default({_zod_literal(schema['default'])})"
return expr
def _json_schema_to_zod(schema: dict, indent: int = 0) -> str:
schema = schema or {}
if 'oneOf' in schema:
raise ValueError('Unsupported oneOf in workspace tool Zod schema generation')
if 'allOf' in schema:
raise ValueError('Unsupported allOf in workspace tool Zod schema generation')
if 'anyOf' in schema:
expr = "z.union([{}])".format(
', '.join(_json_schema_to_zod(item, indent) for item in schema['anyOf'])
)
return _apply_zod_metadata(expr, schema)
if 'enum' in schema:
enum_values = ', '.join(_zod_literal(value) for value in schema['enum'])
expr = f"z.enum([{enum_values}])"
return _apply_zod_metadata(expr, schema)
schema_type = schema.get('type')
if schema_type == 'string':
expr = 'z.string()'
if schema.get('format') == 'date-time':
expr += '.datetime({ offset: true })'
elif schema_type == 'boolean':
expr = 'z.boolean()'
elif schema_type in ('number', 'integer'):
expr = 'z.number()'
if schema_type == 'integer':
expr += '.int()'
if 'minimum' in schema:
expr += f".gte({_zod_literal(schema['minimum'])})"
if 'maximum' in schema:
expr += f".lte({_zod_literal(schema['maximum'])})"
elif schema_type == 'array':
expr = f"z.array({_json_schema_to_zod(schema.get('items', {}), indent)})"
elif schema_type == 'object' or schema.get('properties') is not None or schema.get('additionalProperties') is not None:
properties = schema.get('properties') or {}
if not properties and schema.get('additionalProperties'):
expr = 'z.record(z.string(), z.any())'
else:
required = set(schema.get('required') or [])
prop_lines = []
child_indent = '\t' * (indent + 1)
closing_indent = '\t' * indent
for key, value in properties.items():
prop_expr = _json_schema_to_zod(value, indent + 1)
if key not in required:
prop_expr += '.optional()'
prop_lines.append(f"{child_indent}{_ts_string(key)}: {prop_expr}")
if prop_lines:
expr = "z.object({\n" + ",\n".join(prop_lines) + f"\n{closing_indent}}})"
else:
expr = 'z.object({})'
else:
expr = 'z.any()'
return _apply_zod_metadata(expr, schema)
def generate_workspace_tool_zod_schemas(backend_schemas: dict, openflow_schemas: dict) -> None:
"""Generate Zod schemas used by frontend AI chat workspace mutation tools."""
print("Generating workspace tool Zod schemas...")
missing = [schema_name for schema_name, _ in WORKSPACE_TOOL_ZOD_SCHEMAS if schema_name not in backend_schemas]
if missing:
print(f" Warning: Missing schemas for workspace tool Zod generation: {', '.join(missing)}")
return
trigger_path_description = (
backend_schemas.get('NewHttpTrigger', {})
.get('properties', {})
.get('path', {})
.get('description')
or "The new trigger's Windmill path"
)
lines = [
"// Auto-generated by generate.py - DO NOT EDIT",
"",
"import { z } from 'zod'",
"",
]
for schema_name, export_name in WORKSPACE_TOOL_ZOD_SCHEMAS:
schema = _resolve_schema_refs(
copy.deepcopy(backend_schemas[schema_name]),
backend_schemas,
openflow_schemas,
)
lines.append(f"export const {export_name} = {_json_schema_to_zod(schema)}")
lines.append("")
lines.extend([
"export const triggerRequestSchemas = {",
*[
f"\t{kind}: {schema_name},"
for kind, schema_name in WORKSPACE_TOOL_TRIGGER_SCHEMAS
],
"} as const",
"",
f"const triggerPathSchema = z.string().min(1).describe({_ts_string(trigger_path_description)})",
"",
"export const createTriggerToolSchema = z.object({",
"\tkind: z.enum([",
*[
f"\t\t{_ts_string(kind)},"
for kind, _ in WORKSPACE_TOOL_TRIGGER_SCHEMAS
],
"\t]),",
"\tpath: triggerPathSchema,",
"\tconfig: z.union([",
])
for kind, schema_name in WORKSPACE_TOOL_TRIGGER_SCHEMAS:
lines.append(f"\t\t{schema_name}.omit({{ path: true, script_path: true, is_flow: true }}),")
lines.extend([
"\t])",
"})",
])
lines.append("")
WORKSPACE_TOOL_ZOD_OUTPUT_PATH.write_text("\n".join(lines))
print(" Generated workspaceToolsZod.gen.ts")
# =============================================================================
# Datatable SDK Extraction
# =============================================================================
TS_SQL_UTILS_PATH = TS_SDK_DIR / "sqlUtils.ts"
def extract_datatable_ts_sdk() -> str:
"""Extract datatable-specific type definitions from TypeScript SDK (sqlUtils.ts).
Reads the source file and extracts the public API surface:
- SqlStatement<T> type (fetch, fetchOne, fetchOneScalar, execute methods)
- DatatableSqlTemplateFunction interface (template tag + query method)
- datatable() function signature
"""
if not TS_SQL_UTILS_PATH.exists():
print(f" Warning: sqlUtils.ts not found at {TS_SQL_UTILS_PATH}")
return ''
content = TS_SQL_UTILS_PATH.read_text()
md = "## TypeScript Datatable API (windmill-client)\n\n"
md += "Import: `import * as wmill from 'windmill-client'`\n\n"
# Extract exported type/interface/function definitions from sqlUtils.ts
# We use extract_balanced to handle nested braces correctly
# 1. Extract SqlStatement<T> type
match = re.search(r'(\/\*\*(?:[^*]|\*(?!\/))*\*\/\s*)?export\s+type\s+SqlStatement<T>\s*=\s*', content)
if match:
jsdoc_raw = match.group(1)
brace_start = content.index('{', match.end() - 1)
body, end = extract_balanced(content, brace_start, '{', '}')
if end != -1:
if jsdoc_raw:
md += clean_jsdoc(jsdoc_raw) + "\n"
md += "```typescript\n"
md += f"type SqlStatement<T> = {{\n{_indent_body(body)}\n}};\n"
md += "```\n\n"
# 2. Extract DatatableSqlTemplateFunction interface
match = re.search(
r'(\/\*\*(?:[^*]|\*(?!\/))*\*\/\s*)?export\s+interface\s+DatatableSqlTemplateFunction\s+extends\s+SqlTemplateFunction\s*',
content
)
if match:
brace_start = content.index('{', match.end() - 1)
body, end = extract_balanced(content, brace_start, '{', '}')
if end != -1:
md += "```typescript\n"
md += "// Template tag function: sql`SELECT * FROM table WHERE id = ${id}`.fetch()\n"
md += f"interface DatatableSqlTemplateFunction {{\n"
md += f" // Tagged template usage:\n"
md += f" <T = any>(strings: TemplateStringsArray, ...values: any[]): SqlStatement<T>;\n"
md += f"{_indent_body(body)}\n"
md += "};\n"
md += "```\n\n"
# 3. Extract datatable() function
match = re.search(
r'(\/\*\*(?:[^*]|\*(?!\/))*\*\/\s*)?export\s+function\s+datatable\s*\(([^)]*)\)\s*:\s*(\S+)',
content
)
if match:
jsdoc_raw, params, return_type = match.groups()
if jsdoc_raw:
md += clean_jsdoc(jsdoc_raw) + "\n"
md += "```typescript\n"
md += f"function datatable({params.strip()}): {return_type}\n"
md += "```\n"
return md
def extract_datatable_py_sdk(py_content: str) -> str:
"""Extract datatable-specific class/function definitions from Python SDK.
Uses Python AST to extract:
- datatable() function
- DataTableClient class with query() method
- SqlQuery class with fetch(), fetch_one(), fetch_one_scalar(), execute() methods
"""
if not py_content:
return ''
try:
tree = ast.parse(py_content)
except SyntaxError as e:
print(f" Warning: Could not parse Python SDK for datatable extraction: {e}")
return ''
md = "## Python Datatable API (wmill)\n\n"
md += "Import: `import wmill`\n\n"
# Target classes and the top-level datatable function
target_classes = {'DataTableClient', 'SqlQuery'}
# 1. Extract datatable() top-level function
for node in tree.body:
if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)) and node.name == 'datatable':
docstring = ast.get_docstring(node) or ''
params = _format_py_params(node)
return_ann = f" -> {ast.unparse(node.returns)}" if node.returns else ''
if docstring:
for line in docstring.split('\n'):
md += f"# {line}\n"
md += f"def datatable({params}){return_ann}\n\n"
break
# 2. Extract target classes with their public methods
for node in tree.body:
if isinstance(node, ast.ClassDef) and node.name in target_classes:
class_doc = ast.get_docstring(node) or ''
if class_doc:
for line in class_doc.split('\n'):
md += f"# {line}\n"
md += f"class {node.name}:\n"
for item in node.body:
if isinstance(item, (ast.FunctionDef, ast.AsyncFunctionDef)):
if item.name.startswith('_') and item.name != '__init__':
continue
docstring = ast.get_docstring(item) or ''
params = _format_py_params(item, skip_self=True)
return_ann = f" -> {ast.unparse(item.returns)}" if item.returns else ''
async_prefix = 'async ' if isinstance(item, ast.AsyncFunctionDef) else ''
if docstring:
for line in docstring.split('\n'):
md += f" # {line}\n"
md += f" {async_prefix}def {item.name}({params}){return_ann}\n\n"
md += "\n"
return md
def _format_py_params(node: ast.FunctionDef, skip_self: bool = False) -> str:
"""Format function parameters from AST node."""
params = []
args = node.args
num_defaults = len(args.defaults)
num_args = len(args.args)
for i, arg in enumerate(args.args):
if skip_self and arg.arg == 'self':
continue
param_str = arg.arg
if arg.annotation:
param_str += f": {ast.unparse(arg.annotation)}"
default_idx = i - (num_args - num_defaults)
if default_idx >= 0:
default = args.defaults[default_idx]
param_str += f" = {ast.unparse(default)}"
params.append(param_str)
if args.vararg:
vararg_str = f"*{args.vararg.arg}"
if args.vararg.annotation:
vararg_str += f": {ast.unparse(args.vararg.annotation)}"
params.append(vararg_str)
for i, arg in enumerate(args.kwonlyargs):
param_str = arg.arg
if arg.annotation:
param_str += f": {ast.unparse(arg.annotation)}"
if args.kw_defaults[i]:
param_str += f" = {ast.unparse(args.kw_defaults[i])}"
params.append(param_str)
if args.kwarg:
kwarg_str = f"**{args.kwarg.arg}"
if args.kwarg.annotation:
kwarg_str += f": {ast.unparse(args.kwarg.annotation)}"
params.append(kwarg_str)
return ', '.join(params)
def _indent_body(body: str) -> str:
"""Clean and re-indent a type body for readable output."""
lines = body.strip().split('\n')
result = []
for line in lines:
stripped = line.strip()
if stripped:
# Keep JSDoc comments and method signatures with consistent indentation
if not stripped.startswith('//') and not stripped.startswith('/*') and not stripped.startswith('*'):
result.append(f" {stripped}")
else:
result.append(f" {stripped}")
else:
result.append('')
return '\n'.join(result)
# =============================================================================
# Workflow-as-Code SDK Extraction
# =============================================================================
WAC_TS_FUNCTIONS = [
'getResumeUrls',
'task',
'taskScript',
'taskFlow',
'workflow',
'step',
'sleep',
'waitForApproval',
'parallel',
]
WAC_PY_FUNCTIONS = [
'get_resume_urls',
'task',
'task_script',
'task_flow',
'workflow',
'step',
'sleep',
'wait_for_approval',
'parallel',
]
def _extract_ts_angle_params(content: str, start_pos: int) -> tuple[str, int]:
"""Extract TypeScript generic parameters, ignoring arrow `=>` tokens."""
if start_pos >= len(content) or content[start_pos] != '<':
return '', start_pos
depth = 0
i = start_pos
quote: str | None = None
while i < len(content):
char = content[i]
prev = content[i - 1] if i > 0 else ''
if quote:
if char == '\\':
i += 2
continue
if char == quote:
quote = None
i += 1
continue
if char in ('"', "'", '`'):
quote = char
elif char == '<':
depth += 1
elif char == '>' and prev != '=':
depth -= 1
if depth == 0:
return content[start_pos:i + 1], i + 1
i += 1
return '', -1
def _render_ts_jsdoc(jsdoc_raw: str | None) -> str:
if not jsdoc_raw:
return ''
docstring = clean_jsdoc(jsdoc_raw)
if not docstring:
return ''
lines = ["/**"]
for line in docstring.split('\n'):
lines.append(f" * {line}" if line else " *")
lines.append(" */")
return '\n'.join(lines)
def _extract_ts_interface(content: str, name: str) -> str:
pattern = re.compile(
r'(?:(/\*\*(?:[^*]|\*(?!/))*\*/)\s*)?'
rf'export\s+interface\s+{re.escape(name)}\s*',
re.MULTILINE
)
match = pattern.search(content)
if not match:
return ''
try:
brace_start = content.index('{', match.end() - 1)
except ValueError:
return ''
body, end = extract_balanced(content, brace_start, '{', '}')
if end == -1:
return ''
parts = []
jsdoc = _render_ts_jsdoc(match.group(1))
if jsdoc:
parts.append(jsdoc)
parts.append(f"export interface {name} {{\n{_indent_body(body)}\n}}")
return '\n'.join(parts)
def _extract_ts_exported_function(content: str, name: str) -> str:
pattern = re.compile(
r'(?:(/\*\*(?:[^*]|\*(?!/))*\*/)\s*)?'
rf'export\s+(async\s+)?function\s+{re.escape(name)}\s*',
re.MULTILINE
)
match = pattern.search(content)
if not match:
return ''
jsdoc_raw, is_async = match.groups()
pos = match.end()
while pos < len(content) and content[pos] in ' \t\n':
pos += 1
generic = ''
if pos < len(content) and content[pos] == '<':
generic, pos = _extract_ts_angle_params(content, pos)
if pos == -1:
return ''
while pos < len(content) and content[pos] in ' \t\n':
pos += 1
if pos >= len(content) or content[pos] != '(':
return ''
params, paren_end = extract_balanced(content, pos, '(', ')')
if paren_end == -1:
return ''
return_type, _ = extract_return_type(content, paren_end + 1)
async_prefix = 'async ' if is_async else ''
signature = f"export {async_prefix}function {name}{generic}({clean_params(params)})"
if return_type:
signature += f": {clean_params(return_type)}"
parts = []
jsdoc = _render_ts_jsdoc(jsdoc_raw)
if jsdoc:
parts.append(jsdoc)
parts.append(signature)
return '\n'.join(parts)
def extract_wac_ts_sdk(ts_content: str) -> str:
"""Extract Workflow-as-Code API signatures from the TypeScript SDK."""
if not ts_content:
return ''
declarations = []
task_options = _extract_ts_interface(ts_content, 'TaskOptions')
if task_options:
declarations.append(task_options)
for function_name in WAC_TS_FUNCTIONS:
signature = _extract_ts_exported_function(ts_content, function_name)
if signature:
declarations.append(signature)
else:
print(f" Warning: TypeScript WAC function '{function_name}' not found")
if not declarations:
return ''
md = "## TypeScript Workflow-as-Code API (windmill-client)\n\n"
md += 'Import: `import { workflow, task, taskScript, taskFlow, step, sleep, waitForApproval, getResumeUrls, parallel } from "windmill-client"`\n\n'
md += "```typescript\n"
md += "\n\n".join(declarations)
md += "\n```\n"
return md
def _format_py_params_exact(node, skip_self: bool = False) -> str:
"""Format Python parameters from AST, preserving bare * for keyword-only args."""
params = []
args = node.args
positional = list(args.posonlyargs) + list(args.args)
num_defaults = len(args.defaults)
num_positional = len(positional)
for i, arg in enumerate(positional):
if skip_self and arg.arg == 'self':
continue
param_str = arg.arg
if arg.annotation:
param_str += f": {ast.unparse(arg.annotation)}"
default_idx = i - (num_positional - num_defaults)
if default_idx >= 0:
param_str += f" = {ast.unparse(args.defaults[default_idx])}"
params.append(param_str)
if args.vararg:
vararg_str = f"*{args.vararg.arg}"
if args.vararg.annotation:
vararg_str += f": {ast.unparse(args.vararg.annotation)}"
params.append(vararg_str)
elif args.kwonlyargs:
params.append('*')
for i, arg in enumerate(args.kwonlyargs):
param_str = arg.arg
if arg.annotation:
param_str += f": {ast.unparse(arg.annotation)}"
if args.kw_defaults[i] is not None:
param_str += f" = {ast.unparse(args.kw_defaults[i])}"
params.append(param_str)
if args.kwarg:
kwarg_str = f"**{args.kwarg.arg}"
if args.kwarg.annotation:
kwarg_str += f": {ast.unparse(args.kwarg.annotation)}"
params.append(kwarg_str)
return ', '.join(params)
def _render_py_docstring(docstring: str, indent: str = '') -> str:
if not docstring:
return ''
return '\n'.join(f"{indent}# {line}" if line else f"{indent}#" for line in docstring.split('\n'))
def _extract_py_function_signature(tree: ast.Module, name: str) -> str:
for node in tree.body:
if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef)) and node.name == name:
docstring = ast.get_docstring(node) or ''
params = _format_py_params_exact(node)
return_ann = f" -> {ast.unparse(node.returns)}" if node.returns else ''
async_prefix = 'async ' if isinstance(node, ast.AsyncFunctionDef) else ''
parts = []
rendered_docstring = _render_py_docstring(docstring)
if rendered_docstring:
parts.append(rendered_docstring)
parts.append(f"{async_prefix}def {node.name}({params}){return_ann}")
return '\n'.join(parts)
return ''
def _extract_py_class_signature(tree: ast.Module, name: str) -> str:
for node in tree.body:
if isinstance(node, ast.ClassDef) and node.name == name:
parts = []
docstring = _render_py_docstring(ast.get_docstring(node) or '')
if docstring:
parts.append(docstring)
bases = f"({', '.join(ast.unparse(base) for base in node.bases)})" if node.bases else ''
parts.append(f"class {node.name}{bases}:")
for item in node.body:
if isinstance(item, (ast.FunctionDef, ast.AsyncFunctionDef)) and item.name == '__init__':
init_docstring = _render_py_docstring(ast.get_docstring(item) or '', indent=' ')
if init_docstring:
parts.append(init_docstring)
params = _format_py_params_exact(item)
parts.append(f" def __init__({params})")
break
return '\n'.join(parts)
return ''
def extract_wac_py_sdk(py_content: str) -> str:
"""Extract Workflow-as-Code API signatures from the Python SDK."""
if not py_content:
return ''
try:
tree = ast.parse(py_content)
except SyntaxError as e:
print(f" Warning: Could not parse Python SDK for WAC extraction: {e}")
return ''
declarations = []
task_error = _extract_py_class_signature(tree, 'TaskError')
if task_error:
declarations.append(task_error)
for function_name in WAC_PY_FUNCTIONS:
signature = _extract_py_function_signature(tree, function_name)
if signature:
declarations.append(signature)
else:
print(f" Warning: Python WAC function '{function_name}' not found")
if not declarations:
return ''
md = "## Python Workflow-as-Code API (wmill)\n\n"
md += "Import: `from wmill import workflow, task, task_script, task_flow, step, sleep, wait_for_approval, get_resume_urls, parallel, TaskError`\n\n"
md += "```python\n"
md += "\n\n".join(declarations)
md += "\n```\n"
return md
# =============================================================================
# Skill Generation
# =============================================================================
def generate_skill_content(
skill_name: str,
description: str,
intro: str,
content: str,
sdk_content: str = ''
) -> str:
"""Generate a skill file with YAML frontmatter."""
parts = [
"---",
f"name: {skill_name}",
f"description: {description}",
"---",
"",
]
if intro:
parts.extend([intro, ""])
parts.append(content)
if sdk_content:
parts.extend(["", sdk_content])
return '\n'.join(parts)
# Skill definitions for config-driven generation
SKILL_DEFINITIONS = [
{
'name': 'write-flow',
'description': 'MUST use when creating flows.',
'content_key': 'flow',
},
{
'name': 'raw-app',
'description': 'MUST use when creating raw apps.',
'content_key': 'raw_app',
},
{
'name': 'triggers',
'description': 'MUST use when configuring triggers.',
'content_key': 'triggers',
'schema_types': [
('HttpTrigger', 'http_trigger'),
('WebsocketTrigger', 'websocket_trigger'),
('KafkaTrigger', 'kafka_trigger'),
('NatsTrigger', 'nats_trigger'),
('PostgresTrigger', 'postgres_trigger'),
('MqttTrigger', 'mqtt_trigger'),
('SqsTrigger', 'sqs_trigger'),
('GcpTrigger', 'gcp_trigger'),
('AzureTrigger', 'azure_trigger'),
('EmailTrigger', 'email_trigger'),
],
},
{
'name': 'schedules',
'description': 'MUST use when configuring schedules.',
'content_key': 'schedules',
'schema_types': [('Schedule', 'schedule')],
},
{
'name': 'resources',
'description': 'MUST use when managing resources.',
'content_key': 'resources',
},
{
'name': 'write-workflow-as-code',
'description': 'MUST use when writing or modifying Windmill Workflow-as-Code scripts using workflow, task, step, sleep, approvals, taskScript, taskFlow, task_script, or task_flow.',
'content_key': 'workflow_as_code',
'intro_key': 'wac_cli',
'sdk_content_key': 'wac',
},
{
'name': 'cli-commands',
'description': 'MUST use when using the CLI, including debugging job failures and inspecting run history via `wmill job`.',
'content_key': 'cli_commands',
},
{
'name': 'preview',
'description': 'MUST use when opening the Windmill dev page / visual preview of a flow, script, or app. Triggers on words like preview, open, navigate to, visualize, see the flow/app/script, and after writing a flow/script/app for visual verification.',
'content_key': 'preview',
},
]
def generate_skills(
languages: dict[str, str],
ts_sdk_md: str,
py_sdk_md: str,
wac_ts_md: str,
wac_py_md: str,
flow_cli: str,
flow_base: str,
openflow_content: str,
cli_commands: str,
cli_schemas: dict[str, dict] | None = None
):
"""Generate individual skill files for Claude Code."""
print("Generating skill files...")
cli_schemas = cli_schemas or {}
# Ensure skills directory exists
OUTPUT_SKILLS_DIR.mkdir(parents=True, exist_ok=True)
# Read base files for additional skills.
# Note: raw-app.md is the chat-relevant authoring guide. The CLI workflow
# (wmill app new wizard, on-disk layout, sql_to_apply/, CLI commands) lives
# in raw-app-cli.md. Concatenated here for the skill so CLI users see CLI
# guidance first, then the platform shape.
base_dir = SCRIPT_DIR / "base"
raw_app_cli_md = read_markdown_file(base_dir / "raw-app-cli.md")
raw_app_authoring_md = read_markdown_file(base_dir / "raw-app.md")
base_content = {
'flow': f"{flow_cli}\n\n{flow_base}\n\n{openflow_content}",
'raw_app': f"{raw_app_cli_md}\n\n{raw_app_authoring_md}",
'triggers': read_markdown_file(base_dir / "triggers.md"),
'schedules': read_markdown_file(base_dir / "schedules.md"),
'resources': read_markdown_file(base_dir / "resources.md"),
'workflow_as_code': read_markdown_file(base_dir / "workflow-as-code.md"),
'cli_commands': cli_commands,
'preview': read_markdown_file(base_dir / "preview.md"),
}
# CLI intro for script skills
script_cli_intro = """## CLI Commands
Place scripts in a folder.
After writing, tell the user which command fits what they want to do:
- `wmill script preview <script_path>` — **default when iterating on a local script.** Runs the local file without deploying.
- `wmill script run <path>` — runs the script **already deployed** in the workspace. Use only when the user explicitly wants to test the deployed version, not local edits.
- `wmill generate-metadata` — regenerate the local `.script.yaml` (input schema) and `.lock` (resolved dependencies) for scripts you changed, and refresh their content hashes in `wmill-lock.yaml`. Local files only — **not** a deploy. See "Keep metadata in sync" below.
- `wmill sync push` — deploy local changes to the workspace. Only suggest/run this when the user explicitly asks to deploy/publish/push — not when they say "run", "try", or "test".
### Preview vs run — choose by intent, not habit
If the user says "run the script", "try it", "test it", "does it work" while there are **local edits to the script file**, use `script preview`. Do NOT push the script to then `script run` it — pushing is a deploy, and deploying just to test overwrites the workspace version with untested changes.
Only use `script run` when:
- The user explicitly says "run the deployed version" / "run what's on the server".
- There is no local script being edited (you're just invoking an existing script).
Only use `sync push` when:
- The user explicitly asks to deploy, publish, push, or ship.
- The preview has already validated the change and the user wants it in the workspace.
### Keep metadata in sync after editing
`wmill-lock.yaml` tracks a content hash for each item. Editing a script's content — most importantly **adding or removing an import** or **changing `main`'s arguments** — invalidates that hash and leaves the `.lock`, the `.script.yaml` input schema, and the hash row out of date. Run `wmill generate-metadata` (scoped to what you touched) after such edits so the resolved lock, the auto-generated args UI (driven by `.script.yaml`), and `wmill-lock.yaml` all match the code. Leaving them stale produces spurious diffs in git-sync and CI.
This only writes local files (it is **not** a deploy), but it re-resolves dependencies, so it can bump unpinned versions (the same as deploying from the UI; expected, not a bug). So by default offer it and run it once the user agrees, rather than running it silently after every edit — unless the project's `AGENTS.md` opts into running metadata automatically (see the "Keeping metadata in sync" preference there). Either way YOU run the command, not the user. After running it, diff the regenerated `.lock` / `.script.lock` files and tell the user which dependency versions changed (e.g. `requests 2.31.0 → 2.32.0`), so they can catch an unwanted bump before deploying — even under `Metadata: auto`, since it's information, not a confirmation gate. Pin versions in code to keep them fixed.
With no path argument, `generate-metadata` regenerates only the items whose content hash drifted — not everything. Imports propagate: editing a script that others import marks every importer stale too, so a one-line change to a shared module can regenerate many locks (by design — their locks must reflect the imported code). If it touches more than you expect, run `wmill generate-metadata --dry-run` — it lists each stale item with a reason (`content changed` or `depends on <path>`) without changing anything — then narrow with a path argument (`wmill generate-metadata f/foo`) or `--strict-folder-boundaries`.
If the on-disk `.lock` and `.script.yaml` are already correct and only `wmill-lock.yaml` needs its hashes refreshed (hash drift, or bootstrapping missing entries), use `wmill generate-metadata rehash` — it re-records hashes from disk with no backend round-trip and no dependency changes.
### After writing — offer to test, don't wait passively
If the user hasn't already told you to run/test/preview the script, offer it as a one-sentence next step (e.g. "Want me to run `wmill script preview` with sample args?"). Do not present a multi-option menu.
If the user already asked to test/run/try the script in their original request, skip the offer and just execute `wmill script preview <path> -d '<args>'` directly — pick plausible args from the script's declared parameters. The shape varies by language: `main(...)` for code languages, the SQL dialect's own placeholder syntax (`$1` for PostgreSQL, `?` for MySQL/Snowflake, `@P1` for MSSQL, `@name` for BigQuery, etc.), positional `$1`, `$2`, … for Bash, `param(...)` for PowerShell.
`wmill script preview` does not deploy, but it still executes script code and may cause side effects; run it yourself when the user asked to test/preview (or after confirming that execution is intended). `wmill generate-metadata` does not deploy either — it only writes local files (locks, schemas, hashes) — but offer it before running (or run automatically if the project's `AGENTS.md` opts in), per "Keep metadata in sync" above. Only `wmill sync push` deploys to the workspace — run it only when the user explicitly asks to deploy/publish/push.
For a **visual** open-the-script-in-the-dev-page preview (rather than `script preview`'s run-and-print-result), use the `preview` skill.
Use `wmill resource-type list --schema` to discover available resource types."""
wac_cli_intro = f"""{script_cli_intro}
Workflow-as-Code files use the normal script CLI workflow. There are no separate WAC deploy commands."""
intro_content = {
'wac_cli': wac_cli_intro,
}
extra_sdk_content = {
'wac': "\n\n".join(filter(None, [wac_ts_md, wac_py_md])),
}
skills_generated = []
# Generate script skills for each language
for lang_key, lang_content in languages.items():
if lang_key not in LANGUAGE_METADATA:
print(f" Warning: No metadata for language '{lang_key}', skipping")
continue
metadata = LANGUAGE_METADATA[lang_key]
skill_name = f"write-script-{lang_key}"
skill_dir = OUTPUT_SKILLS_DIR / skill_name
skill_dir.mkdir(parents=True, exist_ok=True)
# Determine which SDK to include
language_sdk_content = ''
if lang_key in TS_SDK_LANGUAGES:
language_sdk_content = ts_sdk_md
elif lang_key in PY_SDK_LANGUAGES:
language_sdk_content = py_sdk_md
skill_content = generate_skill_content(
skill_name=skill_name,
description=metadata['description'],
intro=script_cli_intro,
content=lang_content,
sdk_content=language_sdk_content
)
(skill_dir / "SKILL.md").write_text(skill_content)
skills_generated.append(skill_name)
# Generate other skills from definitions
# Note: Skills with schema_types (triggers, schedules) get base content only.
# Schemas are stored separately and combined at CLI init time.
for skill_def in SKILL_DEFINITIONS:
content = base_content.get(skill_def['content_key'], '')
if not content:
continue
skill_name = skill_def['name']
skill_dir = OUTPUT_SKILLS_DIR / skill_name
skill_dir.mkdir(parents=True, exist_ok=True)
# Note: We no longer append schemas here. Skills with 'schema_types'
# will have schemas combined at CLI init time from SCHEMAS export.
skill_content = generate_skill_content(
skill_name=skill_name,
description=skill_def['description'],
intro=intro_content.get(skill_def.get('intro_key', ''), ''),
content=content,
sdk_content=extra_sdk_content.get(skill_def.get('sdk_content_key', ''), '')
)
(skill_dir / "SKILL.md").write_text(skill_content)
skills_generated.append(skill_name)
print(f" Generated {len(skills_generated)} skills")
return skills_generated
def generate_skills_ts_export(skills: list[str], schema_yaml_content: dict[str, str] | None = None) -> str:
"""Generate TypeScript file that exports skill metadata for the CLI.
Args:
skills: List of skill names
schema_yaml_content: Dict mapping schema keys (e.g., 'http_trigger') to YAML content
"""
schema_yaml_content = schema_yaml_content or {}
ts = "// Auto-generated by generate.py - DO NOT EDIT\n\n"
ts += "export interface SkillMetadata {\n"
ts += " name: string;\n"
ts += " description: string;\n"
ts += " languageKey?: string;\n"
ts += "}\n\n"
ts += "export const SKILLS: SkillMetadata[] = [\n"
skill_desc_map = {s['name']: s['description'] for s in SKILL_DEFINITIONS}
for skill in skills:
if skill.startswith('write-script-'):
lang_key = skill.replace('write-script-', '')
if lang_key in LANGUAGE_METADATA:
metadata = LANGUAGE_METADATA[lang_key]
ts += f' {{ name: "{skill}", description: "{metadata["description"]}", languageKey: "{lang_key}" }},\n'
elif skill in skill_desc_map:
ts += f' {{ name: "{skill}", description: "{skill_desc_map[skill]}" }},\n'
ts += "];\n\n"
# Generate the skills content inline for bundling
ts += "// Skill content for each skill (loaded inline for bundling)\n"
ts += "export const SKILL_CONTENT: Record<string, string> = {\n"
# We'll read the generated files and embed them
for skill in skills:
skill_path = OUTPUT_SKILLS_DIR / skill / "SKILL.md"
if skill_path.exists():
content = skill_path.read_text()
escaped = escape_for_ts(content)
ts += f' "{skill}": `{escaped}`,\n'
ts += "};\n\n"
# Generate SCHEMAS export (YAML content for each schema)
ts += "// YAML schema content for triggers and schedules\n"
ts += "export const SCHEMAS: Record<string, string> = {\n"
for schema_key, yaml_content in sorted(schema_yaml_content.items()):
escaped = escape_for_ts(yaml_content)
ts += f' "{schema_key}": `{escaped}`,\n'
ts += "};\n\n"
# Generate SCHEMA_MAPPINGS export (maps skill names to their schemas)
ts += "// Maps skill names to their schema types and file patterns\n"
ts += "export interface SchemaMapping {\n"
ts += " name: string;\n"
ts += " schemaKey: string;\n"
ts += " filePattern: string;\n"
ts += "}\n\n"
ts += "export const SCHEMA_MAPPINGS: Record<string, SchemaMapping[]> = {\n"
for skill_name, schema_types in SCHEMA_MAPPINGS.items():
ts += f' "{skill_name}": [\n'
for schema_name, file_suffix in schema_types:
ts += f' {{ name: "{schema_name}", schemaKey: "{file_suffix}", filePattern: "*.{file_suffix}.yaml" }},\n'
ts += " ],\n"
ts += "};\n"
return ts
def format_schema_for_markdown(schema_yaml: str, schema_name: str, file_pattern: str) -> str:
"""Format a standalone schema block for plugin skill files."""
return f"""## {schema_name} (`{file_pattern}`)
Must be a YAML file that adheres to the following schema:
```yaml
{schema_yaml.strip()}
```"""
def render_plugin_skill_content(skill_name: str, schema_yaml_content: dict[str, str]) -> str:
"""Render plugin-ready skill content from generated base skill files."""
skill_path = OUTPUT_SKILLS_DIR / skill_name / "SKILL.md"
if not skill_path.exists():
raise FileNotFoundError(f"Missing generated skill content for {skill_name}: {skill_path}")
skill_content = skill_path.read_text()
schema_mappings = SCHEMA_MAPPINGS.get(skill_name, [])
if not schema_mappings:
return skill_content
schema_docs = []
for schema_name, schema_key in schema_mappings:
schema_yaml = schema_yaml_content.get(schema_key)
if not schema_yaml:
continue
schema_docs.append(
format_schema_for_markdown(
schema_yaml=schema_yaml,
schema_name=schema_name,
file_pattern=f"*.{schema_key}.yaml",
)
)
if not schema_docs:
return skill_content
return f"{skill_content}\n\n" + "\n\n".join(schema_docs)
def resolve_plugin_skills_dir(plugin_dir: Path) -> Path:
"""Resolve the plugin skills directory from a repo root, plugin root, or skills dir."""
plugin_dir = plugin_dir.expanduser().resolve()
plugin_root = plugin_dir / "plugins" / "windmill"
if (plugin_root / ".claude-plugin" / "plugin.json").exists():
return plugin_root / "skills"
plugin_skills_dir = plugin_dir / "skills"
plugin_json = plugin_dir / ".claude-plugin" / "plugin.json"
if plugin_json.exists():
return plugin_skills_dir
if plugin_dir.name == "skills":
return plugin_dir
return plugin_skills_dir
def generate_plugin_skills(
plugin_dir: Path,
skills: list[str],
schema_yaml_content: dict[str, str],
) -> Path:
"""Generate standalone skills in a Claude plugin checkout."""
skills_dir = resolve_plugin_skills_dir(plugin_dir)
skills_dir.mkdir(parents=True, exist_ok=True)
expected_skills = set(skills)
for existing in skills_dir.iterdir():
if existing.is_dir() and existing.name not in expected_skills:
shutil.rmtree(existing)
for skill_name in skills:
skill_dir = skills_dir / skill_name
skill_dir.mkdir(parents=True, exist_ok=True)
(skill_dir / "SKILL.md").write_text(
render_plugin_skill_content(skill_name, schema_yaml_content)
)
print(f"\nGenerated for plugin:")
print(f" - {skills_dir} ({len(skills)} skills)")
return skills_dir
# =============================================================================
# Context7 Docs Repo Generation
# =============================================================================
# Files in the context7 target directory that must survive a regeneration
# (everything else is wiped to keep the export deterministic).
CONTEXT7_PRESERVE = frozenset(
{
".git",
".github",
".gitignore",
".gitattributes",
"CODEOWNERS",
"LICENSE",
"LICENSE.md",
"context7.json",
}
)
# Name written into manifest.json — also used to recognise the docs repo
# when re-generating into an existing checkout.
CONTEXT7_REPO_NAME = "windmill-cli-docs"
def extract_agents_md_template() -> str:
"""Extract the AGENTS.wmill.md template string from cli/src/guidance/core.ts.
Keeping a single source of truth in TypeScript avoids drift between what
`wmill init` writes locally and what we publish for context7 ingestion.
"""
core_ts_path = SCRIPT_DIR.parent / "cli" / "src" / "guidance" / "core.ts"
content = core_ts_path.read_text()
# Anchor on the function name so adding other template-literal-returning
# functions to core.ts can't silently re-target the regex. The function
# was renamed from `generateAgentsMdContent` → `generateAgentsCliMdContent`
# when the managed file split out of AGENTS.md into AGENTS.cli.md.
match = re.search(
r"function\s+generateAgentsCliMdContent\b[\s\S]*?return\s+`([\s\S]*?)`;",
content,
)
if not match:
raise RuntimeError(
f"Could not extract AGENTS.wmill.md template from {core_ts_path}"
)
return _unescape_ts_template_literal(match.group(1))
def _unescape_ts_template_literal(raw: str) -> str:
"""Decode TS template-literal escapes in one pass.
Multi-pass `.replace()` would mangle e.g. `\\\\` -> `\\` -> `` ` `` if the
template ever contained a literal backslash followed by a backtick. A
single-pass scan is order-independent.
"""
return re.sub(
r"\\(.)",
lambda m: {"`": "`", "$": "$", "\\": "\\"}.get(m.group(1), m.group(0)),
raw,
)
def render_agents_md_for_docs(
skills: list[str], skill_desc_map: dict[str, str]
) -> str:
"""Render AGENTS.wmill.md exactly as `wmill init` would, for the docs repo.
The skill reference paths point at `.agents/skills/` (the canonical tree
that Codex/Pi read directly and that Claude Code mirrors under
`.claude/skills/`) — matching `buildSkillsReference` in
`cli/src/guidance/writer.ts`.
"""
template = extract_agents_md_template()
skills_reference = "\n".join(
f"- `.agents/skills/{name}/SKILL.md` - {skill_desc_map[name]}"
for name in skills
if name in skill_desc_map
)
return template.replace("${skillsReference}", skills_reference)
def build_skill_desc_map(skills: list[str]) -> dict[str, str]:
"""Map each skill name to its user-facing description.
Mirrors the logic in `generate_skills_ts_export`: language skills draw from
LANGUAGE_METADATA, everything else from SKILL_DEFINITIONS.
"""
desc_map = {s["name"]: s["description"] for s in SKILL_DEFINITIONS}
for skill in skills:
if skill.startswith("write-script-"):
lang_key = skill.replace("write-script-", "")
metadata = LANGUAGE_METADATA.get(lang_key)
if metadata:
desc_map[skill] = metadata["description"]
return desc_map
def _looks_like_windmill_manifest(path: Path) -> bool:
"""Return True iff `path` is a JSON file whose top-level `name` is ours.
Used to distinguish a previously-generated docs repo from an unrelated
project that happens to have a `manifest.json` (Chrome extensions, npm
packages, web app manifests, etc.).
"""
try:
data = json.loads(path.read_text())
except (OSError, json.JSONDecodeError):
return False
return isinstance(data, dict) and data.get("name") == CONTEXT7_REPO_NAME
def _verify_context7_target(target_dir: Path) -> None:
"""Refuse to wipe a non-empty dir that doesn't look like the docs repo.
A typo such as `--context7-dir .`, `~`, or the wrong checkout could
otherwise nuke unrelated files. We accept the target if it's empty/new,
if it has our ownership file, if its `manifest.json` self-identifies as
the windmill-cli-docs repo, or if its git origin points at one.
"""
if not target_dir.exists() or not any(target_dir.iterdir()):
return
if (target_dir / "context7.json").exists():
return
manifest_path = target_dir / "manifest.json"
if manifest_path.exists() and _looks_like_windmill_manifest(manifest_path):
return
git_dir = target_dir / ".git"
if git_dir.exists():
import subprocess
try:
origin = subprocess.run(
["git", "-C", str(target_dir), "config", "--get", "remote.origin.url"],
capture_output=True,
text=True,
check=True,
).stdout.strip()
if CONTEXT7_REPO_NAME in origin:
return
except subprocess.CalledProcessError:
pass
raise RuntimeError(
f"Refusing to overwrite {target_dir}: target does not look like the "
f"{CONTEXT7_REPO_NAME} docs repo.\n"
f"Expected one of:\n"
f" - a `context7.json` at the top level,\n"
f" - a `manifest.json` whose top-level `name` is {CONTEXT7_REPO_NAME!r},\n"
f" - a git remote `origin` containing '{CONTEXT7_REPO_NAME}'.\n"
f"If this is the right directory, add a `context7.json` and retry."
)
def clear_context7_dir(target_dir: Path) -> None:
"""Wipe the docs repo dir of previously generated content.
Preserves a small allowlist (.git, .github, LICENSE, context7.json, etc.)
so this can run against a real checkout without nuking version control or
CI config.
"""
if not target_dir.exists():
return
for entry in target_dir.iterdir():
if entry.name in CONTEXT7_PRESERVE:
continue
if entry.is_dir():
shutil.rmtree(entry)
else:
entry.unlink()
def _read_windmill_version() -> str | None:
"""Return the Windmill release version (e.g. '1.700.2'), or None if absent.
Sourced from `version.txt` at the repo root — the same file release-please
updates on every release.
"""
version_file = SCRIPT_DIR.parent / "version.txt"
if not version_file.exists():
return None
return version_file.read_text().strip() or None
def generate_context7_repo(
target_dir: Path,
skills: list[str],
schema_yaml_content: dict[str, str],
cli_commands_md: str,
) -> Path:
"""Generate a fully-rendered docs repo suitable for context7 ingestion.
Layout written to `target_dir`:
AGENTS.md # the prompt agents see in their projects
README.md # stable intro for humans / context7
manifest.json # version + skill list (for indexing)
cli-commands.md # full CLI flag reference
skills/<name>/SKILL.md # one rendered skill per file
"""
target_dir = target_dir.expanduser().resolve()
target_dir.mkdir(parents=True, exist_ok=True)
_verify_context7_target(target_dir)
clear_context7_dir(target_dir)
skill_desc_map = build_skill_desc_map(skills)
# AGENTS.md — the managed CLI guidance (what `wmill init` writes as
# AGENTS.wmill.md locally). Kept under the `AGENTS.md` filename here to
# preserve the existing context7 ingest path; docs consumers read this
# as the canonical AGENTS file.
(target_dir / "AGENTS.md").write_text(
render_agents_md_for_docs(skills, skill_desc_map)
)
# Full CLI reference at top level.
(target_dir / "cli-commands.md").write_text(cli_commands_md)
# One markdown per skill, with schemas inlined (no template placeholders).
skills_dir = target_dir / "skills"
skills_dir.mkdir(parents=True, exist_ok=True)
for skill_name in skills:
skill_dir = skills_dir / skill_name
skill_dir.mkdir(parents=True, exist_ok=True)
(skill_dir / "SKILL.md").write_text(
render_plugin_skill_content(skill_name, schema_yaml_content)
)
# Stable README so the GitHub repo landing page tells readers (and
# context7's crawler) what they're looking at.
(target_dir / "README.md").write_text(_context7_readme(skills))
# Machine-readable index for context7 / downstream consumers.
# Note: the `name` field is also the marker `_verify_context7_target`
# uses to distinguish our `manifest.json` from generic ones.
manifest = {
"name": CONTEXT7_REPO_NAME,
"description": (
"Auto-generated Windmill CLI docs: agent prompt, skills, and "
"full CLI reference. Source: github.com/windmill-labs/windmill."
),
"skills": [
{"name": name, "description": skill_desc_map.get(name, "")}
for name in skills
],
}
version = _read_windmill_version()
if version:
manifest["version"] = version
(target_dir / "manifest.json").write_text(
json.dumps(manifest, indent=2) + "\n"
)
print(f"\nGenerated for context7 docs repo:")
print(f" - {target_dir} ({len(skills)} skills + AGENTS.md + cli-commands.md)")
return target_dir
def _context7_readme(skills: list[str]) -> str:
"""Render the README that ships at the root of the docs repo.
Doubles as a CLI quickstart for humans landing on the GitHub page and as
the top-level entry point context7 indexes first — keep it actionable.
"""
skill_lines = "\n".join(f"- `skills/{name}/SKILL.md`" for name in skills)
return f"""# Windmill CLI Quickstart
[`wmill`](https://www.windmill.dev/docs/advanced/cli) is the official command
line interface for [Windmill](https://www.windmill.dev) — an open-source
platform for internal tools, workflows, API integrations, background jobs, and
UIs. Use it to authenticate against a workspace, scaffold local projects,
sync scripts/flows/apps between your filesystem and a workspace, and run or
debug jobs from your terminal.
## Install
```sh
npm install -g windmill-cli
wmill --version
```
Upgrade later with `wmill upgrade`.
## Connect to a workspace
```sh
wmill workspace add
```
This walks you through adding a workspace profile — a `(name, remote URL,
workspace id, token)` tuple stored under `~/.config/windmill`. You can have
multiple profiles and switch between them with `wmill workspace switch <name>`.
A workspace token is created from the Windmill UI under
`User Settings → Tokens`. For self-hosted instances, point the remote at your
own URL (e.g. `https://windmill.example.com`).
## Initialize a project directory
```sh
wmill init
```
`wmill init` creates:
- `wmill.yaml` — sync configuration (which folders/types to track).
- `AGENTS.md` + `CLAUDE.md` — the agent prompt published in this repo.
- `.claude/skills/` and `.agents/skills/` — per-task guides used by AI coding
assistants (Claude Code, Codex, Pi). These are the same `SKILL.md` files
you'll find under `skills/` in this repo.
It also offers to bind a workspace profile to the current git branch and to
import git-sync settings from the backend if any are configured.
## Sync between local files and a workspace
```sh
wmill sync pull # workspace → local (writes flows, scripts, apps, etc.)
wmill sync push # local → workspace
```
Sync is idempotent and diff-aware: `wmill sync push --dry-run` previews the
changes without applying them. Use `--yaml` (recommended) to keep specs as
YAML rather than JSON.
For individual entities you can also use the type-specific commands:
```sh
wmill script push path/to/script.ts
wmill flow push path/to/flow.yaml
wmill app push path/to/app.yaml
wmill resource push path/to/resource.yaml
```
## Run, inspect, and debug jobs
```sh
wmill script run u/me/my_script --data '{{"foo": "bar"}}'
wmill flow run u/me/my_flow --data @inputs.json
wmill job list --failed --limit 20
wmill job get <job_id>
wmill job logs <job_id>
```
Logs and flow steps stream as the job runs. For flow failures, `wmill job get`
shows the step tree with each sub-job's id so you can drill in with
`wmill job logs <sub_job_id>`.
## Scaffold new entities
```sh
wmill script new u/me/path --language bun
wmill flow new u/me/path --summary "..."
wmill app new u/me/path --summary "..." --framework svelte
```
These create the correct folder layout and a minimal spec file, then print
next-step hints. Prefer them over hand-creating the folders — they pick the
right naming conventions for your workspace.
## Triggers and schedules
Triggers (HTTP routes, WebSocket, Kafka, NATS, MQTT, SQS, GCP Pub/Sub, Azure
Event Hubs, Email, Postgres CDC) and cron schedules are tracked as YAML files
synced alongside your scripts and flows. See `skills/triggers/SKILL.md` and
`skills/schedules/SKILL.md` for the full schemas.
## Completion
```sh
source <(wmill completions bash) # bash, zsh: source <(wmill completions zsh)
source (wmill completions fish | psub) # fish
```
## Reference
- `cli-commands.md` — every `wmill` command and flag, generated from the
source.
- `AGENTS.md` — the top-level prompt the CLI installs into each project (and
the same instructions AI coding assistants follow when working in a
Windmill repo).
- `skills/<name>/SKILL.md` — one self-contained guide per common task.
### Skills index
{skill_lines}
## About this repo
Auto-generated mirror of the Windmill CLI's bundled AI-agent guidance and
command reference, published for ingestion by docs aggregators such as
[context7](https://context7.com).
**Do not edit by hand.** This repo is regenerated from
[windmill-labs/windmill](https://github.com/windmill-labs/windmill) on every
release. Open issues and PRs in the source repo, not here. The generator is
`system_prompts/generate.py --context7-dir`.
"""
# =============================================================================
# Main Entry Point
# =============================================================================
def parse_args() -> argparse.Namespace:
"""Parse command line arguments."""
parser = argparse.ArgumentParser(
description=(
"Generate Windmill system prompts, CLI guidance, and optionally "
"plugin-ready standalone skills."
)
)
parser.add_argument(
"--plugin-dir",
type=Path,
help=(
"Optional plugin target. Accepts a windmill-claude-plugin repo root, "
"a plugin root, or a skills directory, and refreshes standalone skills there."
),
)
parser.add_argument(
"--context7-dir",
type=Path,
help=(
"Optional path to a docs-repo checkout (e.g. windmill-cli-docs). "
"Writes AGENTS.md, cli-commands.md, skills/, README.md, and manifest.json "
"with all placeholders resolved, suitable for context7 ingestion."
),
)
return parser.parse_args()
def main():
"""Main generation function."""
args = parse_args()
print("Generating system prompts documentation...")
# Ensure output directories exist
OUTPUT_SDKS_DIR.mkdir(parents=True, exist_ok=True)
OUTPUT_GENERATED_DIR.mkdir(parents=True, exist_ok=True)
# Read SDK files
ts_content = ''
if TS_SDK_DIR.exists():
for ts_file in sorted(TS_SDK_DIR.glob('*.ts')):
if not ts_file.name.endswith('.d.ts'):
ts_content += ts_file.read_text() + '\n'
py_content = PY_SDK_PATH.read_text() if PY_SDK_PATH.exists() else ''
openflow_raw = OPENFLOW_SCHEMA_PATH.read_text() if OPENFLOW_SCHEMA_PATH.exists() else ''
# Extract only components.schemas from OpenFlow and convert to minified JSON
openflow_yaml = yaml.safe_load(openflow_raw) if openflow_raw else {}
openflow_schemas = openflow_yaml.get('components', {}).get('schemas', {})
openflow_schemas_json = json.dumps(openflow_schemas, separators=(',', ':'))
openflow_content = f"## OpenFlow Schema\n\n{openflow_schemas_json}"
# Extract TypeScript SDK info
print("Parsing TypeScript SDK...")
ts_functions = extract_ts_functions(ts_content)
ts_types = extract_ts_types(ts_content)
ts_sdk_md = generate_ts_sdk_markdown(ts_functions, ts_types)
(OUTPUT_SDKS_DIR / "typescript.md").write_text(ts_sdk_md)
print(f" Found {len(ts_functions)} functions, {len(ts_types)} types")
# Extract Python SDK info
print("Parsing Python SDK...")
py_functions = extract_py_functions(py_content)
py_classes = extract_py_classes(py_content)
py_sdk_md = generate_py_sdk_markdown(py_functions, py_classes)
(OUTPUT_SDKS_DIR / "python.md").write_text(py_sdk_md)
print(f" Found {len(py_functions)} functions, {len(py_classes)} classes")
# Extract datatable-specific SDK docs (for app mode system prompt)
print("Extracting datatable SDK docs...")
datatable_ts_md = extract_datatable_ts_sdk()
datatable_py_md = extract_datatable_py_sdk(py_content)
(OUTPUT_SDKS_DIR / "datatable-typescript.md").write_text(datatable_ts_md)
(OUTPUT_SDKS_DIR / "datatable-python.md").write_text(datatable_py_md)
# Extract Workflow-as-Code SDK docs (for WAC skills and prompt helpers)
print("Extracting Workflow-as-Code SDK docs...")
wac_ts_md = extract_wac_ts_sdk(ts_content)
wac_py_md = extract_wac_py_sdk(py_content)
(OUTPUT_SDKS_DIR / "wac-typescript.md").write_text(wac_ts_md)
(OUTPUT_SDKS_DIR / "wac-python.md").write_text(wac_py_md)
# Read base prompts
print("Assembling complete prompts...")
base_dir = SCRIPT_DIR / "base"
languages_dir = SCRIPT_DIR / "languages"
script_base = read_markdown_file(base_dir / "script-base.md")
flow_base = read_markdown_file(base_dir / "flow-base.md")
resources_base = read_markdown_file(base_dir / "resources.md")
raw_app_base = read_markdown_file(base_dir / "raw-app.md")
workflow_as_code_base = read_markdown_file(base_dir / "workflow-as-code.md")
flow_cli = read_markdown_file(base_dir / "flow-cli.md")
flow_chat_special_modules = read_markdown_file(base_dir / "flow-chat-special-modules.md")
# Read language files
languages = {}
for lang_file in sorted(languages_dir.glob("*.md")):
languages[lang_file.stem] = lang_file.read_text()
# Extract and generate CLI commands documentation
print("Extracting CLI commands...")
cli_data = extract_cli_commands()
cli_commands = generate_cli_commands_markdown(cli_data)
# Append hand-written CLI guidance covering bits that aren't obvious from
# the auto-generated per-command --help (file_key semantics, --storage,
# workspace scope). The cli-commands skill is the entry point agents read
# to learn about `wmill`, so non-obvious usage notes belong here.
object_storage_cli = read_markdown_file(base_dir / "object-storage-cli.md")
if object_storage_cli:
cli_commands = f"{cli_commands}\n\n{object_storage_cli}"
OUTPUT_CLI_DIR.mkdir(parents=True, exist_ok=True)
(OUTPUT_CLI_DIR / "cli-commands.md").write_text(cli_commands)
print(f" Found {len(cli_data['commands'])} commands, {len(cli_data['global_options'])} global options")
# Extract schemas from backend OpenAPI for CLI format documentation
print("Extracting backend OpenAPI schemas...")
cli_schemas = {}
backend_schemas = {}
if BACKEND_OPENAPI_PATH.exists():
backend_openapi_raw = BACKEND_OPENAPI_PATH.read_text()
backend_openapi = yaml.safe_load(backend_openapi_raw)
backend_schemas = backend_openapi.get('components', {}).get('schemas', {})
# Extract and transform schemas for CLI format (removing server-managed fields)
schema_names = [
'Schedule', 'NewSchedule',
'HttpTrigger', 'NewHttpTrigger',
'WebsocketTrigger', 'NewWebsocketTrigger',
'KafkaTrigger', 'NewKafkaTrigger',
'NatsTrigger', 'NewNatsTrigger',
'PostgresTrigger', 'NewPostgresTrigger',
'MqttTrigger', 'NewMqttTrigger',
'SqsTrigger', 'NewSqsTrigger',
'GcpTrigger',
'AzureTrigger',
'EmailTrigger', 'NewEmailTrigger',
]
for schema_name in schema_names:
if schema_name in backend_schemas:
cli_schemas[schema_name] = extract_cli_schema(backend_schemas[schema_name], backend_schemas, openflow_schemas)
print(f" Extracted {len(cli_schemas)} schemas for CLI format")
else:
print(f" Warning: Backend OpenAPI file not found at {BACKEND_OPENAPI_PATH}")
# Generate standalone schema files for triggers and schedules
schema_yaml_content = generate_schema_files(cli_schemas)
generate_workspace_tool_zod_schemas(backend_schemas, openflow_schemas)
# Assemble prompts for export
prompts = {
# Base prompts
'SCRIPT_BASE': script_base,
'FLOW_BASE': flow_base,
'RESOURCES_BASE': resources_base,
'RAW_APP_BASE': raw_app_base,
'WORKFLOW_AS_CODE_BASE': workflow_as_code_base,
'FLOW_CHAT_SPECIAL_MODULES': flow_chat_special_modules,
# SDKs
'SDK_TYPESCRIPT': ts_sdk_md,
'SDK_PYTHON': py_sdk_md,
'WAC_SDK_TYPESCRIPT': wac_ts_md,
'WAC_SDK_PYTHON': wac_py_md,
# Datatable-specific SDK docs (for app mode)
'DATATABLE_SDK_TYPESCRIPT': datatable_ts_md,
'DATATABLE_SDK_PYTHON': datatable_py_md,
# Schema (raw YAML content)
'OPENFLOW_SCHEMA': openflow_content,
# CLI
'CLI_COMMANDS': cli_commands,
}
# Add language prompts
for lang_name, lang_content in languages.items():
prompts[f'LANG_{lang_name.upper()}'] = lang_content
# Generate TypeScript exports
ts_exports = generate_ts_exports(prompts)
(OUTPUT_GENERATED_DIR / "prompts.ts").write_text(ts_exports)
# Generate complete script.md (all languages combined)
script_md_parts = [script_base]
for lang_name in sorted(languages.keys()):
script_md_parts.append(languages[lang_name])
script_md_parts.extend([ts_sdk_md, py_sdk_md])
script_md = "\n\n".join(filter(None, script_md_parts))
(OUTPUT_GENERATED_DIR / "script.md").write_text(script_md)
# Generate complete flow.md
flow_md_parts = [flow_base, openflow_content]
flow_md = "\n\n".join(filter(None, flow_md_parts))
(OUTPUT_GENERATED_DIR / "flow.md").write_text(flow_md)
# Generate an index file
index_content = """// Auto-generated by generate.py - DO NOT EDIT
// Re-export all prompts
export * from './prompts';
import * as prompts from './prompts';
// Languages that use the TypeScript SDK
const TS_SDK_LANGUAGES = ['bun', 'deno', 'nativets', 'bunnative'];
// Languages that use the Python SDK
const PY_SDK_LANGUAGES = ['python3'];
// Languages that use the TypeScript Workflow-as-Code SDK
const WAC_TS_SDK_LANGUAGES = ['bun'];
// Languages that use the Python Workflow-as-Code SDK
const WAC_PY_SDK_LANGUAGES = PY_SDK_LANGUAGES;
// Helper to combine prompts for scripts
export function getScriptPrompt(language: string): string {
const langKey = `LANG_${language.toUpperCase()}` as keyof typeof prompts;
const langPrompt = (prompts as Record<string, string>)[langKey] || '';
// Determine which SDK to include based on language
let sdkPrompt = '';
if (TS_SDK_LANGUAGES.includes(language)) {
sdkPrompt = prompts.SDK_TYPESCRIPT;
} else if (PY_SDK_LANGUAGES.includes(language)) {
sdkPrompt = prompts.SDK_PYTHON;
}
return [
prompts.SCRIPT_BASE,
langPrompt,
sdkPrompt
].filter(Boolean).join('\\n\\n');
}
// Helper to combine prompts for flows
export function getFlowPrompt(): string {
return [
prompts.FLOW_BASE,
prompts.OPENFLOW_SCHEMA
].filter(Boolean).join('\\n\\n');
}
// Helper for resource & variable authoring
export function getResourcePrompt(): string {
return prompts.RESOURCES_BASE;
}
// Helper for raw app authoring (chat consumers)
export function getRawAppPrompt(): string {
return prompts.RAW_APP_BASE;
}
// Helper to get the datatable SQL SDK reference (wmill.datatable()).
// Pass a language to get only that SDK; omit it to get both.
export function getDatatableSdkReference(language?: string): string {
if (language == null) {
return [
prompts.DATATABLE_SDK_TYPESCRIPT,
prompts.DATATABLE_SDK_PYTHON
].filter(Boolean).join('\\n\\n');
}
if (TS_SDK_LANGUAGES.includes(language)) {
return prompts.DATATABLE_SDK_TYPESCRIPT;
}
if (PY_SDK_LANGUAGES.includes(language)) {
return prompts.DATATABLE_SDK_PYTHON;
}
// Unknown language: return both rather than nothing.
return [
prompts.DATATABLE_SDK_TYPESCRIPT,
prompts.DATATABLE_SDK_PYTHON
].filter(Boolean).join('\\n\\n');
}
// Helper to combine prompts for Workflow-as-Code scripts
export function getWorkflowAsCodePrompt(language?: string): string {
let sdkPrompt = '';
if (language == null) {
sdkPrompt = [
prompts.WAC_SDK_TYPESCRIPT,
prompts.WAC_SDK_PYTHON
].filter(Boolean).join('\\n\\n');
} else if (WAC_TS_SDK_LANGUAGES.includes(language)) {
sdkPrompt = prompts.WAC_SDK_TYPESCRIPT;
} else if (WAC_PY_SDK_LANGUAGES.includes(language)) {
sdkPrompt = prompts.WAC_SDK_PYTHON;
} else {
return '';
}
return [
prompts.WORKFLOW_AS_CODE_BASE,
sdkPrompt
].filter(Boolean).join('\\n\\n');
}
"""
(OUTPUT_GENERATED_DIR / "index.ts").write_text(index_content)
index_dts_content = """export * from './prompts';
export declare function getScriptPrompt(language: string): string;
export declare function getFlowPrompt(): string;
export declare function getResourcePrompt(): string;
export declare function getRawAppPrompt(): string;
export declare function getDatatableSdkReference(language?: string): string;
export declare function getWorkflowAsCodePrompt(language?: string): string;
"""
(OUTPUT_GENERATED_DIR / "index.d.ts").write_text(index_dts_content)
# Generate skill files for Claude Code
CLI_GUIDANCE_DIR.mkdir(parents=True, exist_ok=True)
skills = generate_skills(
languages=languages,
ts_sdk_md=ts_sdk_md,
py_sdk_md=py_sdk_md,
wac_ts_md=wac_ts_md,
wac_py_md=wac_py_md,
flow_cli=flow_cli,
flow_base=flow_base,
cli_commands=cli_commands,
openflow_content=openflow_content,
cli_schemas=cli_schemas
)
# Generate skills TypeScript export for CLI
skills_ts = generate_skills_ts_export(skills, schema_yaml_content)
# Replace hardcoded path conventions with placeholders for CLI runtime resolution.
# init.ts resolves these based on the nonDottedPaths setting in wmill.yaml.
# (Frontend auto-generated files keep the default non-dotted conventions.)
skills_ts = (skills_ts
.replace("\\`__flow\\`", "\\`{{FLOW_SUFFIX}}\\`")
.replace(
"Inline script files should NOT include \\`.inline_script.\\`"
" in their names (e.g. use \\`a.ts\\`, not \\`a.inline_script.ts\\`).",
"{{INLINE_SCRIPT_NAMING}}"
)
.replace("my_flow__flow", "my_flow{{FLOW_SUFFIX}}")
.replace("my_app__raw_app/", "my_app{{RAW_APP_SUFFIX}}/")
)
(CLI_GUIDANCE_DIR / "skills.gen.ts").write_text(skills_ts)
print(f"\nGenerated files:")
print(f" - auto-generated/sdks/typescript.md")
print(f" - auto-generated/sdks/python.md")
print(f" - auto-generated/sdks/wac-typescript.md")
print(f" - auto-generated/sdks/wac-python.md")
print(f" - auto-generated/cli/cli-commands.md (auto-generated from CLI source)")
print(f" - auto-generated/prompts.ts")
print(f" - auto-generated/index.ts")
print(f" - auto-generated/script.md")
print(f" - auto-generated/flow.md")
print(f" - auto-generated/skills/ ({len(skills)} skills)")
print(f" - auto-generated/schemas/ ({len(schema_yaml_content)} schema files)")
print(f"\nGenerated for CLI:")
print(f" - cli/src/guidance/skills.gen.ts")
if args.plugin_dir:
generate_plugin_skills(args.plugin_dir, skills, schema_yaml_content)
if args.context7_dir:
generate_context7_repo(
args.context7_dir, skills, schema_yaml_content, cli_commands
)
print("\nDone!")
if __name__ == '__main__':
main()