get_index_stats

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

Declares read-only and no side effects. Lists return fields in detail: total documents, chunks, embedding model name, BM25 status, cache hit rate, file watcher status. With no annotations provided, the description fully carries the burden of transparency.

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?

Very concise and well-structured. Opens with purpose, then read-only note, then lists return values, then usage guidance with alternatives. Every sentence is informative with no 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 zero parameters and an output schema, the description explains what the tool returns and its safe, read-only nature. It is completely adequate for an AI agent to understand and 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?

No parameters exist, so schema coverage is 100%. The description adds no parameter info because none are needed. Baseline of 4 is appropriate for zero parameters.

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 gets statistics and health metrics for the knowledge base index. It uses specific verb+resource and distinguishes from sibling tools like list_categories and evaluate_retrieval.

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?

Provides explicit usage scenarios: system health checks, verifying embedding model, checking index population, monitoring cache efficiency. Also tells when not to use by naming alternatives (list_categories for per-category counts, evaluate_retrieval for search quality).

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