Pipeline counts for each PUBLISHED job, as the dashboard shows them: how many candidates are at each status and stage, rejections by reason, and the CV score spread. Counts only, no candidates.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, closed-world. The description adds real behavioral context beyond them: results are restricted to PUBLISHED jobs, output is aggregate counts only, and no candidate records are returned — which tells an agent this cannot be used to drill into individuals.
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 the resource and scope, then enumerates the three content dimensions, then closes with the key constraint "Counts only, no candidates." Every clause carries information; nothing is padding.
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?
With zero parameters, an output schema present, and annotations covering safety and idempotency, the description supplies everything still needed: population (published jobs), content dimensions, and the aggregate-only limitation.
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?
The tool takes zero parameters, so the baseline is 4. The description correctly implies a fixed, unfiltered scope (all published jobs) rather than suggesting any filtering options exist.
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 concrete resource and scope: pipeline counts per PUBLISHED job, broken down by status/stage, rejection reasons, and CV score spread. It is clearly distinct in kind from sibling list/get tools like list_candidates and get_review_queue_summary, though it never names an alternative explicitly.
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 usage context is implied by "as the dashboard shows them" and "Counts only, no candidates" — an agent can infer this is for aggregate overviews rather than per-candidate work. However there is no explicit when-to-use/when-not statement nor a pointer to list_candidates for detail.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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