match_resume_to_job

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

With no annotations provided, the description carries full disclosure burden. It reveals that the tool returns a numeric score plus lists of matched/missing skills, and notes that resumes are parsed automatically if not already cached. This is transparent about core behavior, though it does not mention caching side effects or error handling.

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 front-loaded with the primary action ('Score how well a parsed resume matches...') and is reasonably concise. Minor redundancy exists ('parsed automatically if not cached' repeats the idea), but overall it efficiently conveys key information in under 50 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 no annotations, no output schema, and only 2 parameters, the description adequately covers inputs and outputs. However, it lacks details on error cases (e.g., invalid file path), expected file format, and the structure of the returned score object. This is minimally viable but leaves gaps for an agent to handle unexpected situations.

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 0%, yet the description adds meaningful context for both parameters: file_path is an absolute path to the resume file (with auto-parsing note) and job_description is the job posting text. This provides value beyond the raw type declarations, though more explicit file format constraints could improve clarity.

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 that the tool scores how well a parsed resume matches a job description based on skill-keyword overlap, returning a 0-100 score and lists of matched/missing skills. It distinguishes from siblings like parse_resume (which only parses) and search_and_match (which likely searches jobs broadly) by focusing specifically on pairwise 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 does not provide any guidance on when to use this tool versus alternatives such as search_and_match or parse_resume. It lacks explicit context for usage selection, leaving the agent to infer intent without comparative criteria.

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