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 performs 'cross-repo impact analysis' and resolves to 'symbol level', which suggests it's a read-only analysis tool, but doesn't disclose important behavioral traits like whether it requires specific permissions, how it handles large codebases, what the output format looks like, or any rate limits. For a complex analysis tool with zero annotation coverage, this is a significant 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?

The description is perfectly concise with two sentences that each earn their place: the first establishes the core functionality, and the second adds important behavioral context about resolution depth. There's zero waste or redundancy, and it's front-loaded with the main purpose.

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 complex impact analysis tool with 3 parameters, no annotations, and no output schema, the description is incomplete. While it clearly states what the tool does, it lacks crucial information about what the output looks like, how results are structured, whether there are limitations or prerequisites (like requiring per-repo indexes), and behavioral constraints. The description doesn't compensate for the missing structured data.

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 three parameters (endpoint, method, service) with their types and constraints. The description doesn't add any parameter-specific information beyond what's in the schema, such as examples of endpoint patterns beyond '/api/users' or how these filters interact. The baseline score of 3 is appropriate when 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 with specific verbs ('find all client code', 'resolves down to symbol level') and resources ('across subprojects', 'endpoint changes'), distinguishing it from siblings like get_subproject_clients (which likely lists clients without impact analysis) or get_cross_service_impact (which focuses on service-level rather than subproject-level analysis).

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 ('when an endpoint changes', 'when per-repo indexes exist') but doesn't explicitly state when to use this tool versus alternatives like get_change_impact (which might be more general) or get_cross_service_impact. It provides some guidance but lacks explicit exclusions or named alternatives.

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