get_index_stats

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

Despite no annotations, the description clearly states 'Read-only, no side effects' and details the return values (chunk count, docs path, embedding provider/model, etc.), fully disclosing behavioral traits beyond what annotations would provide.

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 concise, well-structured with clear sections, and front-loads the main purpose. Every sentence adds necessary information without fluff.

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?

Given the tool's simplicity and the presence of an output schema, the description covers return values and the single parameter adequately. No gaps remain for an agent to invoke the tool 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?

Input schema has 0% coverage but only one parameter. The description adds 'Target project name (optional)' which clarifies the parameter's meaning and optionality, adding value beyond the schema's default and 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 explicitly states 'Show vector index statistics for the active project,' clearly indicating the verb and resource. It distinguishes itself from sibling tool check_knowledge_quality by noting that the latter is for quality issues, not stats.

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 explicit guidance on when to use this tool (check chunk count, verify reindex, inspect configuration) and when not to use it (use check_knowledge_quality for quality issues), making the usage context very clear.

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