Extract structured requirements from a job description

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

No annotations are provided, so the description carries the burden of disclosing behavior. It clearly states the transformation that occurs and enumerates the extracted fields, which effectively sets expectations for what the tool returns. It does not mention edge-case behaviors like handling malformed or very short text, but those are relatively minor 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 two sentences with no filler. The main parsing behavior and output fields are front-loaded, and the downstream usage is included as a useful secondary note without bloating the entry.

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?

For a single-parameter tool with no output schema and no annotations, the description provides a solid set of expected output fields and a suggested follow-up action. It is sufficiently complete for an agent to call the tool correctly, though an explicit mention of the input format beyond 'full job description text' would make it fully self-contained.

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 input schema covers the single parameter jdText with a clear description ('The full job description text.'), so schema coverage is 100%. The description adds minimal additional parameter meaning beyond calling it a job posting, which is already implied by the tool name and 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 uses a specific verb ('Parse') and identifies the resource ('a job posting') and the structured output fields. It clearly distinguishes the tool from siblings like extract_resume_text by focusing on job descriptions and structured requirements.

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 provides clear context: use this tool when a job posting needs to be converted into structured data. It also names a downstream tool, optimize_resume, giving the agent a next-step suggestion. However, it does not explicitly state when not to use this tool or compare it with other siblings.

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