pipeline_metrics

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

With no annotations, the description states 'Read-only' explicitly, which is a key safety trait, and describes the return content (per-stage counts, conversion percentages, time-in-stage metrics). This adds valuable behavioral context beyond the tool name, though it does not cover error behavior or auth requirements.

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 four sentences, each earning its place: purpose, read-only status, example queries, and return details. It is front-loaded and free of fluff.

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 a simple one-parameter tool with an output schema, the description provides sufficient context: purpose, usage examples, prerequisite, and return metrics. It does not over-explain or omit critical operational details, though it could mention potential limitations (e.g., only for active jobs) but that is not necessary.

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% (job_id has a description). The tool description repeats the 'list_jobs → match by name' guidance already present in the schema, adding no new parameter-level semantics. Baseline of 3 is appropriate because the schema handles the parameter meaning.

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 it provides 'Conversion rates and stage metrics for a job' and specifies 'Returns per-stage counts, conversion percentages, and time-in-stage metrics.' It uses a specific resource (pipeline metrics) and is distinct from sibling tools like time_to_hire or source_effectiveness.

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?

It gives concrete example user queries ('what are our conversion rates for the Backend role?' or 'where are we losing candidates?') and explicit prerequisite instructions ('To find job_id: list_jobs → match by name'). It does not mention alternative tools or exclusions, but the usage context is clear.

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