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audit_config

Scan AI agent configuration files to identify stale references, dead paths, and token bloat, with optional fix suggestions for optimization.

Instructions

Scan AI agent config files for stale references, dead paths, and token bloat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
config_filesNoSpecific config files to audit (default: auto-detect)
fix_suggestionsNoInclude fix suggestions (default true)
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'scan' implies a read-only analysis operation, the description doesn't clarify whether this tool makes any changes, requires specific permissions, has rate limits, or what format the results take. For a diagnostic tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that immediately communicates the tool's purpose without any wasted words. It's appropriately sized for a scanning/auditing tool and front-loads the essential information about what gets scanned and what problems are detected.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a diagnostic tool with no annotations and no output schema, the description is incomplete. It doesn't explain what format the audit results take, whether the scan is comprehensive or sampling-based, what constitutes 'token bloat', or how results should be interpreted. The description leaves too many contextual questions unanswered for effective tool selection and use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the schema already documents both parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'scan' and the resource 'AI agent config files', specifying three concrete outcomes: 'stale references, dead paths, and token bloat'. It distinguishes itself from siblings like 'scan_code_smells' or 'scan_security' by focusing specifically on configuration file analysis rather than code quality or security issues.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools performing various scans and analyses (e.g., 'scan_code_smells', 'scan_security', 'self_audit'), there's no indication of when configuration file auditing is preferred over other diagnostic tools or what prerequisites might be needed.

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

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