bulk_score

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

No annotations are provided, so the description must carry full burden. It discloses enrichment, ranking, and output format, but does not mention side effects, rate limits, authentication needs, or whether it is read-only. Adequate but with gaps.

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 concise, front-loaded with the main action, and uses a structured Args format. Every sentence adds value, no wasted 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?

Given the complexity and that an output schema exists, the description adequately explains return format and main parameters. However, it lacks details on error handling, scoring methodology, and sorting behavior, which would improve completeness.

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?

With 0% schema coverage, the description fully compensates by describing each parameter: usernames (max 100), job_description (optional), export_format (markdown/csv), top_n (default 100). Adds constraints and enum guidance not in schema.

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 scores a batch of GitHub usernames and returns a ranked table. It specifies batch processing and enrichment with activity score or JD fit, distinguishing it from siblings like score_against_jd which likely handles single users.

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 implies usage for batch scoring (explicitly says 'batch') but does not explicitly name when to use this versus alternatives like rank_candidates or score_against_jd. It provides clear context but no exclusions.

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