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

Adds meaningful behavior beyond annotations: it discloses the research method (live sources: Stack Overflow, GitHub issues, docs), the return format (cause + fix with code, with citations), and the cost model ($0.02 USDC per call via x402). Annotations only say readOnlyHint=true and openWorldHint=true; the cost and sourcing details are valuable additions not derivable from annotations.

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?

Single sentence, front-loaded with purpose, then input form, then output, then sourcing, then pricing. Dense and every clause earns its place.

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 tool with no output schema and 40% param coverage, the description tells the agent what it takes in (error + optional code) and what it returns (cause, fix, citations) plus the price, which is enough to call it. Minor gap: no mention of the async job-id mode or the language/framework hints that would help disambiguate input prep.

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 coverage is 40%, and the description only implies the 'error' and 'optional code' parameters. It does not explain language, framework, or the async flag (which returns a job id) - that behavior is only in the schema's async description. Baseline is 3 for the partial coverage where the schema carries some detail but the description fails to compensate for the low-coverage params like language/framework.

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?

States a specific verb (fix), resource (an error/stack trace), and the exact output (likely cause + concrete fix with code). Distinguishes from generic research/debug siblings by naming it 'error fixer for coding agents' and describing the specific input form (paste error + optional code).

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?

Clearly signals when to use it: when you have an error message or stack trace and want a cause plus a fix. It does not name explicit alternatives (e.g., docs_ask, search, github_issues, ask), so usage is clear but not fully routed relative to siblings.

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