trace-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'detects' patterns and requires git, indicating it's a read-only analysis tool. However, it doesn't specify output format, error conditions, performance characteristics, or any side effects, leaving gaps in behavioral understanding.

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 efficiently structured in two sentences: one defining what it detects and another stating prerequisites. Every sentence adds value without redundancy. It could be slightly more front-loaded by leading with the core purpose more prominently, but overall it's well-constructed.

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 2-parameter analysis tool with no annotations and no output schema, the description provides adequate but incomplete context. It explains what patterns are detected and the git requirement, but doesn't describe the return format, error handling, or how results should be interpreted, leaving the agent with significant 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 both parameters. The description doesn't add any additional parameter semantics beyond what's in the schema descriptions, such as explaining how 'min_confidence' relates to Jaccard confidence in practice. Baseline 3 is appropriate when schema does 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's purpose with specific verbs ('detect architectural drift') and identifies two concrete patterns it looks for: 'cross-module co-change anomalies' and 'shotgun surgery patterns'. It explicitly distinguishes what it detects, making its purpose unambiguous and specific.

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 context by stating 'Requires git', which suggests it should be used in git-based repositories. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'detect_antipatterns' or 'get_co_changes' from the sibling list, leaving the agent to infer appropriate scenarios.

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