Diego ImbertandClaude Opus 5
a74f73ccb1
Putting it inside `custom_instance_pg_databases` was the wrong call, and it cost two ways. The catalog serializes a generated Postgres password per role, and that row is the operator-facing instance config, so the passwords reached `get_instance_config` and its YAML editor — a live cluster credential in a response body, a UI field and any log of either. Worse in the other direction: `to_settings_map` strips the catalog, so a full-row upsert of that key writes the row back without it and the catalog is gone, while the cluster keeps every login it described. `custom_instance_replication_pwd` is the precedent and says exactly why — a generated secret, written only by the server, never operator-authored, hidden so the config machinery cannot read, rewrite or drop it. The catalog is the same thing, so it now has the same shape: `datatable_roles`, in `HIDDEN_SETTINGS`, `PROTECTED_SETTINGS` and the agent-worker denylist. No redaction to keep in step with three code paths, and no way for a neighbouring write to take it out. Two races on the same shared documents. `edit_datatable_config` read the stored data tables outside its transaction and then wrote the whole `datatable` document, so a permissions save committing in between was silently rolled back; it now reads under `FOR UPDATE`. And `set_datatable_permissions` validated role ids against the catalog before opening its transaction, so a deletion in between let it write a deleted role back — including as the default, which every later job then fails on; it now holds the catalog lock and the settings row across validation and write. Completes the authorization contracts the previous commit claimed but did not finish: `read_datatable_entry` (which it named and missed), `resolve_governing_datatable`, whose whole job is to answer for a workspace the caller may not belong to, and `converge_connect_grants_with`, which had not inherited its wrapper's. Also the generic Python SDK reference: `_format_py_params` learned the bare `*` last time, but `extract_py_functions` is a second formatter and still rendered `datatable(name, role)`, so code written from that page passed a keyword-only argument positionally. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012ti5HyeTikPMYyW8YSdiHR
System Prompts
This directory contains the single source of truth for AI system prompts used by both the frontend copilot and CLI guidance.
Structure
system_prompts/
├── base/ # Core instruction templates (manually written)
│ ├── flow-base.md # Shared OpenFlow structure guidance
│ └── flow-cli.md # CLI/local-agent workflow guidance for write-flow skill
├── languages/ # Language-specific instructions (manually written)
└── auto-generated/ # Auto-generated files (DO NOT EDIT)
├── sdks/ # SDK documentation
├── cli/ # CLI command documentation
├── prompts.ts # TypeScript exports
└── index.ts # Helper functions
Usage
Regenerating Prompts
When SDK methods or the OpenFlow schema change, run:
python system_prompts/generate.py
To also refresh the standalone skills in a Claude plugin checkout:
python system_prompts/generate.py --plugin-dir ~/windmill-claude-plugin
--plugin-dir accepts:
- the
windmill-claude-pluginrepo root - a plugin root such as
plugins/windmill - a direct
skills/directory
To regenerate the public docs repo (consumed by context7):
python system_prompts/generate.py --context7-dir ~/windmill-cli-docs
--context7-dir writes a fully-rendered snapshot (AGENTS.md,
cli-commands.md, skills/<name>/SKILL.md, README.md, manifest.json
with the Windmill version) with all template placeholders resolved —
suitable for ingestion by docs aggregators. In CI this runs from
.github/workflows/publish-cli-docs.yml on every release tag. The
generator refuses to wipe the target directory unless it's empty or has
a context7 marker (context7.json, manifest.json, or a
windmill-cli-docs git remote), so a typo can't delete unrelated files.
This will:
- Parse TypeScript and Python SDK files to extract function signatures
- Parse the OpenFlow YAML schema
- Parse the CLI commands
- Assemble complete prompts from markdown files
- Generate TypeScript exports in
auto-generated/ - Optionally refresh plugin-ready standalone
SKILL.mdfiles in the target directory
Scope
These system prompts contain ONLY:
- How to write Windmill scripts (language syntax, conventions, SDK usage)
- How to structure Windmill flows (OpenFlow schema, module types, data flow)
- Resource type handling, S3 operations
They DO NOT contain:
- Tool usage instructions (edit_code, set_flow_json, etc.)
- IDE/editor specific commands
- Testing tool invocations
Tool instructions are added separately by the frontend and CLI.
CLI-only workflow instructions live in base/flow-cli.md and are included in the
generated write-flow skill for wmill init. They are intentionally excluded
from the frontend flow chat prompt.
Integration
Frontend
Uses Vite path alias $system_prompts pointing to auto-generated/:
import { FLOW_GUIDANCE } from "$system_prompts/flow";
import { getLangContext } from "$system_prompts/languages";
CLI
Generates /cli/src/guidance/skills.gen.ts with embedded skill content for wmill init.
Editing Guidelines
- Edit markdown files in
base/,languages/ - Never edit files in
auto-generated/directly - After editing, run
generate.pyto update exports