trace-mcp

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

No annotations are provided, so the description carries full burden. It mentions the tool provides time-series data and that metrics are populated by predict_bugs runs, which adds some context about data sources. However, it fails to disclose critical behavioral traits such as whether this is a read-only operation, performance characteristics, rate limits, authentication needs, or what happens if file_path/module parameters are invalid. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 brief and front-loaded, efficiently stating the tool's purpose and key metrics in one sentence, followed by a note on data population. There's no wasted text, but it could be slightly more structured (e.g., separating purpose from prerequisites).

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 no annotations, 100% schema coverage, and no output schema, the description provides adequate basic purpose but lacks completeness. It doesn't explain return values (e.g., format of time-series data), error conditions, or behavioral nuances needed for a tool with potential data dependencies. For a tool with moderate complexity and no structured safety hints, this is minimally viable but leaves 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?

Schema description coverage is 100%, so the schema already fully documents the three parameters (file_path, module, limit). The description adds no additional semantic meaning about parameters beyond what's in the schema, such as how file_path and module interact or the implications of the limit parameter. Baseline 3 is appropriate when the schema does all the heavy lifting.

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 retrieves 'time-series health metrics' for files or modules, listing specific metrics like bug score, complexity, coupling, and churn. It distinguishes from siblings by focusing on historical trends rather than current snapshots (e.g., vs. get_complexity_report). However, it doesn't explicitly contrast with similar tools like get_complexity_trend or get_coupling_trend, which slightly reduces differentiation.

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 for analyzing historical health metrics over time, and mentions data is 'populated by predict_bugs runs,' suggesting a prerequisite or data dependency. However, it lacks explicit guidance on when to use this tool versus alternatives like get_complexity_trend or get_coupling_trend, and doesn't specify exclusions or edge cases.

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