Audit Local Codebase (20+ Schema.org & 14+ AI Bot Rules) & Generate /llms.txt + ai-catalog.json

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=true, openWorldHint=false, so safety posture is covered by structured data. The description usefully adds that files are actively written into public/ or targetDir and enumerates what is scanned, but is silent on the key write risk: whether an existing /llms.txt or ai-catalog.json is overwritten, merged, or skipped.

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?

Front-loaded with the audit-and-generate purpose, and every clause carries substantive detail (category count, file types, artifact names). It is a single dense sentence with a heavy nested parenthetical, which costs a bit of readability but not enough to be wasteful.

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?

With no output schema, the description must carry the burden of explaining what comes back, and it only gestures at '6 weighted categories' without describing the report shape (scores, violations, per-category breakdown) or how results differ when outputAll is true. Adequate to call the tool, incomplete for interpreting its return.

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 100%, so both parameters (outputAll, targetDir) are already documented with defaults and examples. The description restates the generation behavior that outputAll controls but adds no syntax or edge-case detail beyond the schema, so the baseline 3 applies.

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?

Specific verb+resource: a local structural compliance audit across named categories (robots.txt vs 14+ AI crawler directives, Schema.org JSON-LD in HTML/TSX/JSX, /llms.txt syntax, /.well-known/ai-catalog.json) plus generation of two artifacts. The scope is concrete and the title reinforces it, but nothing distinguishes it from siblings 'audit_ai_readiness' or 'generate_ai_manifests', which sound like overlapping capabilities.

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?

'Local filesystem' implies usage context, and the description makes clear it both audits and writes files. However, there is no guidance on when to pick this over 'audit_ai_readiness' (audit-only?) or 'generate_ai_manifests' (generation-only?), and no prerequisites (e.g., project must have a robots.txt or Next.js-style public dir) are stated.

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