pipeline_metrics

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

With no annotations supplied, the description still carries the safety profile by declaring 'Read-only', and it discloses a great deal about the response shape (ever-reached count, current count, % of all applications, stage-to-next conversion, average days from stage history). It does not mention permissions or limits, but for a read-only metric endpoint the disclosure is strong.

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?

Front-loaded with the purpose and the read-only guarantee, then user phrasing, then the identifier workflow, then return contents — a logical order with almost no wasted words. The job_id lookup hint is slightly redundant with the schema, costing it a point.

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?

An output schema exists, so the description is not obligated to explain returns, and it still does so usefully while covering call prerequisites. The only gap is sibling disambiguation among the other pipeline analytics tools, which an agent may need to choose correctly.

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% for the single job_id parameter, so baseline is 3. The description's 'To find job_id: list_jobs → match by name' merely restates the schema's own parameter description rather than adding format or type semantics.

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?

States a specific verb+resource combination ('Conversion rates and stage metrics for a job') and enumerates exactly what is returned per stage, which is far more informative than a tautology. It does not, however, distinguish itself from close analytics siblings such as pipeline_summary, time_to_hire, or source_effectiveness, so an agent still has to infer the boundary.

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?

Gives concrete user-intent phrasings ('what are our conversion rates for the Backend role?', 'where are we losing candidates?') and the prerequisite resolution path (list_jobs → match by name). It is clear on when to use it but offers no exclusion telling the agent when a sibling analytics tool is the better choice.

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