codegraph_stats

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

There are no annotations, so the description carries the full burden. It discloses that the tool returns statistics and counts, which implicitly indicates a read-only aggregation, but it does not explicitly state the absence of side effects, potential resource costs, or any error behavior. For a simple stats tool, this is adequate but not rich.

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?

Two compact sentences: the first front-loads the core purpose, the second enumerates the returned metrics. Every word earns its place; no fluff or repetition.

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 no-argument statistics tool with no output schema, the description is complete: it lists the exact categories of counts returned. An agent can predict the shape and intent of the call without needing extra 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 takes zero parameters, so schema coverage is trivially 100%. Baseline for 0 parameters is 4; there is no parameter information needed beyond what is already empty.

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 names a specific verb ('Get') and a concrete resource ('code intelligence graph statistics'), then enumerates exactly what is returned (counts of projects, files, symbols, packages, sessions, edge type breakdown). This clearly distinguishes it from sibling tools like codegraph_query or codegraph_repomap, which target different purposes.

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 usage — if an agent needs aggregate counts or a breakdown of graph elements, this is the tool — but it does not explicitly state when to use it over alternatives or mention any exclusions. No sibling differentiation is provided in the text.

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