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

Adds valuable behavioral context beyond annotations: discloses cost ('5 credits'), confirms synchronous execution ('no polling needed'), and clarifies dependencies ('Does not require a context or candidate'). Annotations indicate this is not read-only (readOnlyHint: false) and interacts with external systems (openWorldHint: true), which aligns with the description's mention of 'live web search' for salary data. No contradictions present.

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?

Three sentences with zero waste. Front-loaded with specific functionality and cost, followed by execution characteristics, ending with workflow guidance. Every sentence earns its place with dense, actionable information.

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's complexity (multi-dimensional analysis with credit cost) and lack of output schema, the description adequately covers the analysis scope, cost model, and workflow integration. Minor gap: does not describe the return structure or format, though it lists the five analysis dimensions which provides implicit output guidance.

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 50% schema description coverage (industry_hint and location_hint lack schema descriptions), the description partially compensates by referencing 'raw JD text' (supporting jd_text) and 'salary benchmarking' (supporting include_live_search). However, it fails to explain the purpose of industry_hint and location_hint optional parameters, leaving semantic gaps for half the parameter set.

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 provides a specific verb (analyze), clear resource (job description text), and enumerates five specific analysis dimensions (market competitiveness, clarity issues, bias detection, salary benchmarking, skills extraction). It clearly distinguishes this from sibling tools by specifying it works on raw JD text without requiring a context or candidate.

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?

Explicitly states prerequisites ('Does not require a context or candidate'), input format ('accepts raw JD text'), and execution pattern ('Synchronous -- returns results directly'). Critically, it provides clear workflow guidance: 'Use results to refine JDs before running atlas_start_jd_fit_batch,' explicitly naming the sibling tool that depends on this output.

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