trace-mcp

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

With no annotations provided, the description carries full burden and does an excellent job explaining behavioral traits: it describes fuzzy search behavior (trigram + Levenshtein), semantic search requirements (AI provider + embed_repo), fusion ranking methodology (BM25 + PageRank + embeddings + identity match), and default behaviors (auto-enable fuzzy when exact search returns 0). It doesn't mention rate limits or authentication needs, but covers most operational aspects well.

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 with each sentence adding distinct value: purpose statement, Grep comparison, filter types, fuzzy search explanation, semantic search requirements, and fusion ranking details. While comprehensive, it remains focused without unnecessary repetition, though it could be slightly more front-loaded.

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 tool with 17 parameters, no annotations, and no output schema, the description provides substantial context about behavior, usage scenarios, and parameter relationships. It explains the different search modes (fuzzy, semantic, fusion) and their requirements. The main gap is lack of information about return format or result structure, but otherwise it's quite complete.

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?

With 100% schema description coverage, the baseline is 3. The description adds significant value by explaining the semantic meaning and relationships between parameters: it clarifies that fuzzy=true enables typo-tolerant search, semantic='on' enables AI-powered search with prerequisites, and fusion=true enables multi-channel ranking. This provides context beyond the schema's technical descriptions.

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 searches for symbols (functions, classes, methods, variables) in source code using name, kind, or text criteria. It specifically distinguishes this from Grep for code-specific searches and mentions multiple filter types, making the purpose specific and differentiated from siblings.

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 guidance on when to use this tool ('Use instead of Grep when looking for functions, classes, methods, or variables in source code') and offers clear alternatives for different scenarios (fuzzy search for typos, semantic search for conceptual queries, fusion for multi-channel ranking). This gives comprehensive usage context.

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