trigger_full_pipeline

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

With no annotations, the description reveals that the tool is asynchronous and returns a jobId. However, it does not disclose potential side effects, required permissions, or what happens to existing data. More behavioral context is needed.

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 a single sentence that front-loads the core purpose and includes essential async/polling guidance. No unnecessary words.

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 covers the return value (jobId) and the async workflow, but lacks details on the pipeline's steps, output artifacts, or how to interpret results. Given the lack of output schema, slightly more context would be beneficial.

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 coverage is 100%, so the description adds limited value beyond what is already in the schema. It does not elaborate on optional parameters like specialInstructions or platform beyond their names.

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 starts the full pipeline for an existing business profile, runs use cases through implementation plan generation, and returns a jobId for polling. This verb+resource combination is specific and distinguishes from siblings like generate_use_cases or get_generation_status.

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 explains the asynchronous nature and suggests polling for status, but does not provide explicit when-not-to-use guidance or alternatives for similar tasks. It is clear but lacks exclusion criteria.

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