Files
windmill/system_prompts/base/flow-base.md
T
GuilhemandClaude Opus 5 2b4369d7cb fix: reject invalid AI agent tool names when the chat writes a flow (#10756)
* fix: reject invalid AI agent tool names when the chat writes a flow

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

* fix: address review nits on agent tool name validation

Share one AI-agent walk between the providerless-agent and invalid-tool-name
collectors, drop the unused validateToolName, and list every reserved id in the
tool naming rules.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

* fix: describe an agent tool's summary as the name the agent calls it by

The OpenFlow schema described `AgentTool.summary` as a short description of
the tool, which is the same schema the flow write tools hand the model, so it
pulled against the naming rules. Narrow those rules to flowmodule tools, since
websearch and mcp tool names are never regex-checked, and let `kind` take
either vocabulary its callers resolve.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

* fix: name-check only the agent tools whose summary the agent calls

An mcp tool exposes the MCP server's own tool names and a websearch tool's
summary is a plain label, so neither reaches the worker's name check. Both
default to an empty summary in the editor, which the chat then refused to
write back.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-20 10:49:01 +02:00

407 lines
13 KiB
Markdown

# Windmill Flow Building Guide
## OpenFlow Schema
The OpenFlow schema (openflow.openapi.yaml) is the source of truth for flow structure. Refer to OPENFLOW_SCHEMA for the complete type definitions.
## Reserved Module IDs
- `failure` - Reserved for failure handler module
- `preprocessor` - Reserved for preprocessor module
- `Input` - Reserved for flow input reference
## Hard Structural Rules
These are strict Windmill schema rules. Follow them exactly.
- `value.modules` is only for normal sequential steps
- `value.preprocessor_module` and `value.failure_module` are special top-level fields inside `value`, not entries in `value.modules`
- If a flow needs a preprocessor, create `value.preprocessor_module` with `id: preprocessor`
- If a flow needs a failure handler, create `value.failure_module` with `id: failure`
- Do NOT create regular modules inside `value.modules` named `preprocessor` or `failure`
- `preprocessor_module` and `failure_module` only support `script` or `rawscript`
- `preprocessor_module` runs before normal modules and cannot reference `results.*`
- `failure_module` can use the `error` object with `error.message`, `error.step_id`, `error.name`, and `error.stack`
Correct shape:
```yaml
value:
preprocessor_module:
id: preprocessor
value:
type: rawscript
...
failure_module:
id: failure
value:
type: rawscript
...
modules:
- id: process_event
value:
type: rawscript
...
```
Incorrect shape:
```yaml
value:
modules:
- id: preprocessor
...
- id: process_event
...
- id: failure
...
```
## Module ID Rules
- Must be unique across the entire flow
- Use underscores, not spaces (e.g., `fetch_data` not `fetch data`)
- Use descriptive names that reflect the step's purpose
## AI Agent Modules
An `aiagent` module runs an LLM that can call tools. Each entry of `value.tools` is a module-shaped
object with an extra `value.tool_type`: `flowmodule` for a script/flow tool, `mcp` for an MCP server
tool, `websearch` for web search.
```json
{
"id": "support_agent",
"summary": "AI agent for customer support",
"value": {
"type": "aiagent",
"input_transforms": {
"provider": {
"type": "static",
"value": { "kind": "openai", "resource": "$res:f/ai_providers/openai", "model": "gpt-4o" }
},
"output_type": { "type": "static", "value": "text" },
"user_message": { "type": "javascript", "expr": "flow_input.query" },
"system_prompt": { "type": "static", "value": "You are a helpful assistant." }
},
"tools": [
{
"id": "search_docs",
"summary": "search_documentation",
"description": "Search the product documentation. Use it whenever the user asks how a feature works.",
"value": {
"tool_type": "flowmodule",
"type": "rawscript",
"language": "bun",
"content": "export async function main(query: string) { return ['doc1', 'doc2']; }",
"input_transforms": { "query": { "type": "static", "value": "" } }
}
}
]
}
}
```
- `provider` is a static object, not a bare resource string: `{ "kind": <provider kind>,
"resource": "$res:<path>", "model": <model id> }`. Required unless the module links to a saved
agent through `value.agent`
### Tool Naming Rules
These rules cover `flowmodule` tools, the ones the agent calls by name. A `websearch` tool's
`summary` is a plain label (`Web Search`), and an `mcp` tool exposes the MCP server's own tool
names, so neither is name-checked at all — leave those summaries as they are.
- A flowmodule tool's `summary` is the **name the agent calls it by**, not a human label. Put the
human-readable explanation in `description`
- `summary` must match `^[a-zA-Z0-9_]+$`: letters, numbers and underscores only. No spaces, dashes,
dots or accents — `search_documentation`, never `Search documentation`
- Always set `summary`. It must be unique among that agent's tools, and must not be one of the
reserved ids (`do`, `bg`, `ctx`, `state`, `if`, `else`, `for`, `delete`, `while`, `new`, `in`,
`failure`, `preprocessor`, `as`, `Input`, `Result`, `Trigger`)
- A tool name outside that character set is rejected: flow write tools refuse it, and a flow that
reaches the worker with one fails every run with `Invalid tool name`
- Tool `id` follows the same rules as any module ID — unique across the flow, underscores not spaces
- `description` is optional free text telling the agent when and how to call the tool. Set it
whenever the name alone does not make that obvious; it overrides the description derived from the
underlying script
## Common Mistakes to Avoid
- Missing `input_transforms` - Rawscript parameters won't receive values without them
- Referencing future steps - `results.step_id` only works for steps that execute before the current one
- Duplicate module IDs - Each module ID must be unique in the flow
- AI agent flowmodule tool names with spaces - `summary` is the tool name and only accepts letters, numbers and underscores
## Data Flow Between Steps
- `flow_input.property` - Access flow input parameters
- `results.step_id` - Access output from a previous step only when that step result is in scope
- `results.step_id.property` - Access specific property from a previous step output only when that step result is in scope
- `flow_input.iter.value` - Current iteration value inside a `forloopflow`; in a `whileloopflow` it is just the iteration index (a plain number, same as `flow_input.iter.index`)
- `flow_input.iter.index` - Current loop index when inside a loop (`forloopflow` or `whileloopflow`)
## Loop Structure Rules
- For `whileloopflow`, break the loop with a module-level `stop_after_if`: on the loop module itself, or on an inner step (required when that step carries state via its own `results` — see below)
- `stop_after_if` is always a sibling of `id` and `value` on a flow module — never a direct key of the loop's `value` object
- `stop_after_all_iters_if` is for checks after the whole loop finishes, not the normal per-iteration break condition
- `flow_input.iter.value` in a `whileloopflow` is just the iteration index (same number as `flow_input.iter.index`) — it never carries state, so `flow_input.iter.value.<field>` is always undefined and a loop whose stop condition depends on it never terminates
- To carry state across iterations, a step reads its own previous-iteration result via `results.<its_own_id>` with a first-iteration fallback (e.g. `results.b ?? flow_input.start`) — but then the loop's `stop_after_if` MUST sit on that inner step, not on the loop module: a body that is exactly one plain step with the stop condition on the loop module runs on a fast path where `results.<step_id>` is null on every iteration and the loop never terminates (bodies with 2+ steps, or whose single step has its own `stop_after_if`, retry or similar, resolve `results` across iterations regardless of stop placement)
- For state that is just a counter, derive it from the index instead (e.g. `flow_input.iter.index + 1`) — that works in every configuration, including with `stop_after_if` on the loop module
- If the user asks for a final scalar/object after a loop, add a normal step after the loop that extracts the final value from the loop result instead of returning the whole loop result array
Correct `whileloopflow` shape:
```yaml
- id: loop_until_done
stop_after_if:
expr: result.done === true
skip_if_stopped: false
value:
type: whileloopflow
skip_failures: false
modules:
- id: advance_state
value:
type: rawscript
input_transforms:
count:
type: javascript
expr: flow_input.iter.index + 1
- id: return_final_state
value:
type: rawscript
input_transforms:
final_state:
type: javascript
expr: results.loop_until_done[results.loop_until_done.length - 1]
```
Correct `whileloopflow` shape carrying state via `results` (stop condition on the inner step):
```yaml
- id: loop_until_done
value:
type: whileloopflow
skip_failures: false
modules:
- id: advance_state
stop_after_if:
expr: result.done === true
skip_if_stopped: false
value:
type: rawscript
input_transforms:
state:
type: javascript
expr: results.advance_state ?? flow_input.initial_state
```
Incorrect `whileloopflow` patterns:
```yaml
- id: loop_until_done
value:
type: whileloopflow
stop_after_if:
expr: result.done === true
```
```yaml
input_transforms:
state:
type: javascript
# iter.value is a number (the iteration index); there is no previous-iteration state
expr: flow_input.iter.value.count
```
```yaml
input_transforms:
final_state:
type: javascript
expr: results.loop_until_done
```
## Approval / Suspend Structure
An approval step is a normal **script** step (`type: rawscript` or `type: script`) that is turned into an approval by adding a module-level `suspend`. Its script calls `wmill.getResumeUrls(approver)` to generate the secret resume/cancel URLs and returns them so they can be sent to the approver(s) (Slack, email, etc.) or approved from the run page.
- `suspend` belongs on the flow module object itself, as a sibling of `id` and `value`
- Never put `suspend` inside `value`
- Do NOT use `type: identity` for an approval step. An identity step suspends but never produces the resume URLs, so approvers have no link to act on — it is not a functional approval.
Correct shape:
```yaml
- id: request_approval
suspend:
required_events: 1
resume_form:
schema:
type: object
properties:
comment:
type: string
required: [comment]
value:
type: rawscript
language: bun
input_transforms:
approver:
type: static
value: ''
content: |
import * as wmill from "windmill-client"
export async function main(approver?: string) {
const urls = await wmill.getResumeUrls(approver)
// send urls.resume / urls.cancel to the approver(s), e.g. via Slack or email
return urls
}
```
Incorrect shape (suspend misplaced inside `value`):
```yaml
- id: request_approval
value:
type: rawscript
suspend:
required_events: 1
```
Incorrect shape (identity has no resume URLs — not a real approval):
```yaml
- id: request_approval
suspend:
required_events: 1
value:
type: identity
```
## Branch Result Scope Rules
- Inside a branch, you may reference earlier outer steps and earlier steps in the same branch
- Outside a `branchone`, do NOT reference ids of steps that only exist inside its branches or default branch. Use `results.<branchone_module_id>` instead
- Outside a `branchall`, do NOT reference ids of steps inside its branches. Use `results.<branchall_module_id>` instead
- If downstream steps need a stable shape after a branch, make each branch return the same fields
- When needed, add a normalization step immediately after the branch and consume `results.<branch_module_id>` there
Correct after `branchone`:
```yaml
- id: route_order
value:
type: branchone
...
- id: send_confirmation
value:
input_transforms:
routed:
type: javascript
expr: results.route_order
```
Incorrect after `branchone`:
```yaml
expr: results.create_shipment
expr: results.create_backorder
```
Correct after `branchall`:
```yaml
- id: enrich_parallel
value:
type: branchall
parallel: true
...
- id: combine_data
value:
input_transforms:
enrichments:
type: javascript
expr: results.enrich_parallel
```
## Input Transforms
Every rawscript module needs `input_transforms` to map function parameters to values:
Static transform (fixed value):
{"param_name": {"type": "static", "value": "fixed_string"}}
JavaScript transform (dynamic expression):
{"param_name": {"type": "javascript", "expr": "results.previous_step.data"}}
## Resource References
- For flow inputs: Use type `"object"` with format `"resource-{type}"` (e.g., `"resource-postgresql"`)
- For step inputs: Use static value `"$res:path/to/resource"`
## Final Structural Self-Check
Before finalizing a flow, verify:
- any preprocessor is in `value.preprocessor_module`
- any failure handler is in `value.failure_module`
- any approval step has module-level `suspend`
- no downstream step references inner branch step ids from outside the branch
- every AI agent flowmodule tool has a unique `summary` made only of letters, numbers and underscores
## S3 Object Operations
Windmill provides built-in support for S3-compatible storage operations.
To accept an S3 object as flow input:
```json
{
"type": "object",
"properties": {
"file": {
"type": "object",
"format": "resource-s3_object",
"description": "File to process"
}
}
}
```
## Using Resources in Flows
On Windmill, credentials and configuration are stored in resources. Resource types define the format of the resource.
### As Flow Input
In the flow schema, set the property type to `"object"` with format `"resource-{type}"`:
```json
{
"type": "object",
"properties": {
"database": {
"type": "object",
"format": "resource-postgresql",
"description": "Database connection"
}
}
}
```
### As Step Input (Static Reference)
Reference a specific resource using `$res:` prefix:
```json
{
"database": {
"type": "static",
"value": "$res:f/folder/my_database"
}
}
```