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. It discloses key behavioral traits: it scans for specific code smells, uses multiple analysis methods (comment scanning, symbol body analysis), and includes false-positive filtering. It mentions what it finds but doesn't cover output format, performance implications, or error handling, leaving some gaps.

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 front-loaded with the core purpose in the first sentence, followed by additional context. It's efficient with two sentences, but could be slightly more structured by separating use cases from methodology. No wasted words, but minor room for improvement in clarity.

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 and no output schema, the description provides good purpose and method details but lacks information on return values, error cases, or performance characteristics. For a tool with 6 parameters and complex functionality, this leaves gaps in understanding how results are delivered or what failures might occur.

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 documents all parameters thoroughly. The description adds minimal parameter semantics by listing examples like 'IPs, URLs, credentials, magic numbers, feature flags' for hardcoded values, but this is redundant with the schema's enum values. Baseline 3 is appropriate as the 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: 'Find deferred work and shortcuts' with specific examples (TODO/FIXME/HACK/XXX comments, empty functions & stubs, hardcoded values). It distinguishes itself from grep by mentioning 'combining comment scanning, symbol body analysis, and context-aware false-positive filtering.' This is specific and differentiates it from simple text search tools.

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 detecting technical debt that 'grep alone misses,' suggesting it's for more sophisticated code analysis. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_tech_debt' or 'detect_antipatterns' from the sibling list, nor does it mention prerequisites or exclusions.

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