pipeline_summary

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

With no annotations, the description carries the full burden and does well: it declares 'Read-only' and describes the return shape (interview stages in pipeline order, each with active candidates, names, source, days in current stage, days since last activity), plus the efficiency note that one call replaces 5-10 sequential calls. It omits limits such as pagination, caps on candidates per stage, or the definition of 'active'.

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-loads purpose, then usage, then return contents in a logical order. The quoted user phrasings are slightly verbose but earn their place as trigger guidance; overall it is tight and skimmable.

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 return values needn't be re-explained, yet the description helpfully summarizes them anyway. Combined with the read-only declaration and the job_id discovery path, an agent has everything needed to invoke it 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 coverage is 100% and the single job_id parameter is already documented as 'Greenhouse job ID — list_jobs → match by name'. The description repeats that same discovery path, adding no meaning beyond the schema, so the baseline 3 applies.

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 and resource ('Complete pipeline view for a job — candidates grouped by stage') and clearly distinguishes itself from analytics siblings like pipeline_metrics or stale_applications by emphasizing the per-job grouped-by-stage view. An agent can tell what this returns without opening the schema.

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 phrasings that should trigger it ('show me the pipeline for Backend Engineer', 'how many candidates are in each stage') and explains how to obtain the required job_id (list_jobs → match by name). It does not explicitly state when to prefer a sibling such as pipeline_metrics or candidates_needing_action, so it stops short of full alternative routing.

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