audit_config

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds value by confirming read-only behavior and specifying the return format (JSON with issues array, fields file, line, category, etc.). This provides useful behavioral context beyond 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?

The description is two sentences, front-loading the purpose and key behaviors. Every sentence adds value with no redundancy or fluff. It efficiently covers what the tool does, how it works, and what it returns.

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 4 parameters, no output schema, and strong annotations, the description is largely complete. It specifies return format and issue categories, but could elaborate on what constitutes 'stale references' or 'dead paths'. Still, it provides enough for an agent to invoke correctly.

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 100% with detailed parameter descriptions. The description adds context like default values (auto-detect, true, false), version references (E14), and implications (drift_only implies include_drift). This enhances understanding beyond the schema alone.

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 the tool's purpose: scanning AI agent config files for stale references, dead paths, token bloat, and drift. It uses specific verbs and resources, and distinguishes itself from similar tools like check_claudemd_drift by covering multiple issue types and offering optional drift detection.

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 context for use (e.g., default behaviors, drift_only usage) but does not explicitly say when to use this tool versus alternatives like check_claudemd_drift. It lacks exclusions or comparative guidance.

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