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 that the tool computes usage statistics, lists the exact metrics computed, and even mentions the log file location (~/Downloads/kstock/logs/metrics_YYYYMMDD.jsonl). This adds behavioral context beyond a simple read operation.

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 relatively concise, using a title line, bullet list for metrics, and an Args section. It front-loads the purpose. A minor improvement could be to remove redundant phrasing, but overall it's well-structured.

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 output schema exists (not shown here), the description does not need to explain return values. It covers the tool's purpose, parameter, metrics, and even log file location, which is complete for a statistics-summary tool. No obvious gaps.

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 schema has 0% description coverage (only type and default for 'days'). The description adds full semantics: '조회할 일수 (기본 1, 오늘만. 최대 30)' meaning number of days to query, default 1 (today only), maximum 30. This compensates completely for the schema's lack of description.

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 it aggregates and shows MCP tool usage statistics for recent N days, listing specific metrics (call count, execution times, token usage, cache hit rate, error count). This verb+resource combination is distinct from sibling tools, which are mostly about stock data, not 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 explicitly states '디버깅/최적화용' (for debugging/optimization), providing clear context for when to use this tool. It does not explicitly exclude alternatives, but given the unique purpose, this is sufficient guidance.

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