run_pipeline

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It indicates the tool is asynchronous (returns run ID) and runs agents sequentially, but lacks details about error handling, blocking behavior, rate limits, or side effects. For a mutation tool, more transparency is expected.

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 (two sentences) and front-loaded with purpose. It could be slightly more structured (e.g., listing steps), but overall efficient and clear.

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?

The description explains the return value (run ID) and indicates status checking is possible. However, it doesn't mention how to check status (e.g., get_run_status tool) or what happens on failure. For an async pipeline, this is good but not fully comprehensive.

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?

Schema description coverage is 100%, so baseline is 3. The description adds valuable context: pipeline_id references list_pipelines, input gives examples, and api_key explains where to obtain it. This goes beyond the schema alone.

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 verb 'execute', the resource 'AI agent pipeline', and the behavior (sequential agent execution with output passing). It also mentions the return value (run ID) and distinguishes from siblings implicitly by specifying 'pipeline' vs 'agent'.

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 a clear use case but does not explicitly state when not to use this tool or guide towards alternatives like run_agent for single agents. It does mention using list_pipelines to get pipeline IDs, which is helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.