extract_keywords

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

With no annotations, the description fully discloses the tool's behavior: deterministic, tokenizes, filters filler words, recognizes skills and phrases, ranks by frequency with boosting. It also states the return format, leaving no ambiguity about what the tool does.

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 and well-structured: a lead sentence explaining the purpose, a sentence on the algorithm, a sentence on the output format, and a final usage recommendation. Every sentence adds value with no redundancy.

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 tool has two parameters and no annotations, the description covers purpose, algorithm, output, and usage. It lacks details on error handling or input constraints (e.g., what happens with empty text or extreme top_n values), but for a straightforward extraction tool, it is largely complete.

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 has 0% parameter description coverage, so the description must compensate. It only implicitly covers job_text (the text to tokenize) but does not mention top_n at all, leaving a parameter undocumented. Although the output format is described, the optional parameter's effect on ranking is omitted.

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 extracts skills/tools/keywords from job postings using a deterministic method. It specifies the exact verb 'pull' and resource 'job posting', and distinguishes itself from siblings by focusing on keyword extraction for ATS scanning.

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 explicitly recommends using the output as input to a sibling tool (ats_gap_check), providing clear usage context. However, it does not specify when not to use this tool or mention any prerequisites like using fetch_job_posting first.

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