match_job

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose a key behavioral trait: the tool returns raw retrieval scores and resumes chunks WITHOUT synthesizing strengths/gaps/notes, explicitly telling the agent to reason over the evidence itself. This is valuable transparency about the tool's computational behavior (heuristic cosine similarity) and its non-analytical nature. It doesn't cover auth/permissions or failure modes, but for a retrieval-style tool the core disclosure is present and helpful.

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 well-structured with clear sections: purpose sentence, Args list, and Returns paragraph. It's appropriately detailed for a retrieval tool and front-loads the purpose. There is a minor dependency on the job-fit://rubric resource which isn't fully elaborated, and the Args/Returns formatting is somewhat technical, but overall it's concise with no wasted sentences.

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 only 2 parameters (1 required), no enums, and an output schema present, the tool is relatively simple. The description explains what the tool returns (retrieval_score, chunks, similarities) and, crucially, what it does NOT do (synthesize strengths/gaps/notes), directing the agent to the job-fit://rubric. The main gap is that the rubric resource is referenced vaguely without stating what it contains, but the output schema and low parameter count reduce the burden on the description.

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 schema description coverage is 0%, meaning the schema provides only type names (job_description, source_url) with titles but no descriptive help. The description compensates meaningfully: it explains job_description is 'the full text of the job description to match against' and source_url is 'optional URL the job description was pulled from, for reference.' However, it adds no format details for job_description (e.g., expected length, formatting) or when source_url might matter. This is adequate compensation for low coverage but not exhaustive.

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 opens with a specific verb+resource statement: 'Retrieve resume/experience evidence relevant to a job description.' This clearly distinguishes it from its siblings (push_to_tracker, list_applications), which are evident from context to be write/listing operations. The purpose is unambiguous and specifically tied to retrieval matching.

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 clearly implies when to use this tool: when you need evidence retrieval against a job description for fit analysis. It explicitly states what the tool does NOT do ('Does not synthesize strengths/gaps/notes') and instructs the agent to reason over retrieved evidence applying the job-fit://rubric resource. This is strong guidance about how to use the output. However, it doesn't explicitly contrast with sibling tools (e.g., when NOT to use this in favor of list_applications), which would push it to a 5.

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