Fork (copy) a community flow into your workspace. After forking, the flow is yours — you can run it with run_flow, modify it, or use it as a starting point. Get post_id from search_community results.
| Name | Required | Description | Default |
|---|---|---|---|
| post_id | Yes | The community post ID to fork (from search_community results). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-readOnly, non-idempotent, and non-destructive. The description adds meaningful context by explaining that the fork becomes user-owned ('the flow is yours') and can be run/modified, implying the original is unaffected (as a copy). This goes beyond the basic annotation flags.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded. The first sentence immediately states the action and target. The second sentence adds use-case context and a pointer to fetching the ID. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no nested objects) and the annotations describing mutation characteristics, the description covers the essential context: what forking does, post-fork capabilities, and where to get the ID. It lacks explicit mention of return values or further side effects, but that is not critical for such a straightforward operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the only parameter (post_id) and its source ('from search_community results'). The description repeats this guidance, adding no new semantic value. Per the rubric, with 100% schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Fork (copy) a community flow into your workspace.' It distinguishes from siblings like fork_template (template vs community flow) and duplicate_flow (existing vs community) by specifying the source as a community flow and the result as a personal copy.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context for when to use the tool: after forking, 'the flow is yours — you can run it with run_flow, modify it, or use it as a starting point.' It also instructs 'Get post_id from search_community results,' but does not explicitly mention alternatives or when not to use it, which keeps it from a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct resource and action, with clear separation between flow lifecycle, execution, model exploration, community, and account tools. Even similar-sounding tools like create_flow, preview_flow, and suggest_flow have clearly different purposes (actually creating, dry-running, and recommending models). Descriptions prevent misselection.
All tools follow a consistent verb_noun pattern in snake_case (e.g., create_flow, list_flows, run_batch, cancel_flow). No mixed conventions or vague verbs like 'process' or 'handle'. The naming is uniform and predictable.
At 33 tools, this is a large surface, but each tool addresses a distinct feature of the cnaps.ai platform, from flow CRUD and execution to community features and notifications. Still, it exceeds the typical well-scoped range and feels heavy, making it a borderline case between appropriate and too many.
The core flow lifecycle (create, read, update, delete, restore, duplicate) and execution (run, batch, cancel) are covered, but structural editing of flow graphs is missing—update_flow only changes parameters, not topology. Additionally, there is no run history, batch list/cancel, or community post update/delete, leaving notable gaps for a platform API.