Identifies candidate organizational patterns (P01–P14) to review using benchmark metrics, stage gaps, and observation tags, supporting hypothesis screening for diagnostics.
P01~P14 중 검토할 패턴 후보를 찾습니다. benchmark: benchmark_metrics 결과. stage_gap: assess_stage 결과의 stage_gap. observation_tags: rules의 tags 값(예: management_lag).
| Name | Required | Description | Default |
|---|---|---|---|
| benchmark | No | ||
| stage_gap | No | ||
| observation_tags | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. '찾습니다' (find) hints at a read operation, but nothing confirms read-only status, side effects, auth needs, or whether results are persisted. For a screening tool in a case workflow, this is a meaningful gap.
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?
Three terse lines with the purpose front-loaded and one line per parameter. No filler, and the structure mirrors the input list. Appropriate for a small utility tool.
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 3-parameter tool with 0% schema coverage, no annotations and no output schema, the description covers purpose and input provenance but omits behavior, output expectations, and when-to-use relative to siblings. Adequate but incomplete for the tool's complexity.
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?
Schema coverage is 0%, so the description must compensate, and it does: it maps each of the three parameters to its source (benchmark_metrics result, assess_stage's stage_gap, rules tags) and even gives a sample tag value (management_lag). It stops short of describing expected shapes, but the origin mapping is genuinely useful.
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?
States a specific verb (찾습니다/find) and resource (pattern candidates among P01~P14) to be reviewed. An agent can tell this is a screening step distinct from compute_metrics or recommend_actions. The only weakness is that 'P01~P14' is opaque without the catalog, but the core action is clear.
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 wires the inputs to their producing tools (benchmark from benchmark_metrics, stage_gap from assess_stage, tags from rules), which implies where this sits in the pipeline. However, it never states when to call this versus siblings like assess_hypotheses or next_best_evidence, so usage is only inferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.