check_knowledge_quality

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

No annotations provided, so description carries full burden. It declares read-only and no modification of files or vector index. It details return values but does not mention rate limits or auth requirements, though these may not be critical for this tool.

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?

Concise and well-structured: purpose, behavioral guarantee, usage guidance, parameter documentation, and return description in a logical order with no unnecessary words.

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?

Comprehensive given the context: describes return values (quality score, issue counts, per-file list) and output schema exists. Differentiates from siblings adequately.

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 0%, but the description explicitly documents the project parameter as an optional target project name, adding meaning beyond the schema's default string type.

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 validates the knowledge base for consistency and structural correctness, with a specific verb and resource. It distinguishes from siblings like validate_doc (single document) and get_index_stats (chunk counts).

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 when to use (periodically or after adding documents) and when not to use, providing alternatives: validate_doc() for single documents and get_index_stats() for chunk counts.

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