trace-mcp

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

No annotations are provided, so the description carries the full burden. It describes the tool's behavior as returning a project overview with specific data types (frameworks, languages, file counts, structure) and suggests a usage pattern. However, it doesn't disclose potential limitations like rate limits, authentication needs, or what happens if the project doesn't exist. The description adds some behavioral context but leaves 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 perfectly concise and well-structured in two sentences. The first sentence states the purpose, and the second provides specific usage guidance. Every word earns its place with no redundancy or fluff.

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 the tool's moderate complexity (single parameter, no output schema, no annotations), the description is reasonably complete. It explains what the tool returns, provides usage guidance, and adds parameter semantics. However, without annotations or output schema, it could benefit from more behavioral details like response format or error conditions.

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?

The input schema has 100% description coverage, with the single parameter 'summary_only' well-documented in the schema. The description adds value by explaining the semantic purpose of this parameter: 'to orient yourself before diving into code.' This provides context beyond the schema's technical description, but since schema coverage is high, the baseline is 3.

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: 'Get project overview: detected frameworks, languages, file counts, structure.' It specifies the verb ('Get') and resource ('project overview') with concrete details about what information is returned. However, it doesn't explicitly differentiate from sibling tools like 'get_project_health' or 'get_workspace_map', which prevents a perfect score.

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 provides explicit usage guidance: 'Call with summary_only=true at session start to orient yourself before diving into code.' This clearly indicates when to use the tool (session start) and how to use it (with the summary_only parameter) for orientation purposes, which is excellent guidance for an AI agent.

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