get_metrics_summary

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

No annotations are provided, so the description carries the full burden. It discloses the data source (log file paths), the metrics computed (call count, latency percentiles, token usage, cache hit rate, error count), and the parameter's effect (days with default/max). It does not mention failure modes, but for a read-only metrics tool this is sufficient.

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 well-structured: a one-line summary, purpose, a bullet list of metrics, log file paths, and Args. It is slightly detailed but every part adds value, especially the log locations which are crucial for understanding where the data comes from.

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?

With one parameter, no annotations, and an output schema present, the description provides sufficient context: what metrics are returned, what the 'days' parameter does, and where the data is read from. A minor ambiguity remains about whether results are a single aggregate or a per-day breakdown, but the output schema would clarify that.

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 input schema only gives 'days' with type integer and default 1, with 0% schema description coverage. The description fully compensates by explaining the meaning ('조회할 일수' — number of days to query), the default behavior ('기본 1, 오늘만' — today only), and the maximum ('최대 30').

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's function: '사용량통계 — 최근 N일간 MCP 도구 사용량을 집계해서 보여줍니다' (aggregate and show MCP tool usage for the last N days). It distinguishes itself from all siblings, none of which are about tool usage metrics.

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 labels the tool as '디버깅/최적화용' (for debugging/optimization), giving clear context on when it is appropriate to use. It does not explicitly mention alternatives or exclusions, but no sibling tool serves the same purpose.

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