kg_stats

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

With no annotations provided, the description carries the full burden. It does disclose what the tool returns ('total chunks, KG nodes/edges, entity type breakdown, most-connected nodes'), which conveys the behavior of producing aggregate counts and summaries. However, it does not disclose performance considerations, data freshness, or what 'most-connected' threshold is used, so transparency is reasonable but incomplete.

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 a single sentence that front-loads the action ('Return corpus statistics') and then lists the specific statistics. Every item appears relevant and there is no filler or redundant wording.

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?

For a zero-parameter statistics tool, the description covers the main use case and expected output categories. Without an output schema, the description should ideally clarify the response structure, and it doesn't fully specify the format of 'entity type breakdown' or 'most-connected nodes', but the enumeration of returned stats provides most of the needed context.

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?

The tool has 0 parameters, so there is no parameter meaning to add. The description appropriately explains what the tool does given its no-argument signature, making it clear that it is a zero-configuration aggregate query.

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 uses specific verbs ('Return') and identifies a precise resource ('corpus statistics') with a clear list of content categories. It distinguishes itself from siblings like search_kg or get_doc by indicating it is a summary/aggregate operation rather than a retrieval or search function.

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 implies when to use this tool: when the agent needs corpus-level statistics rather than specific document or entity retrieval. However, it provides no explicit exclusions or comparison to siblings, so the usage guidance relies on inference from the listed return contents.

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