d_find_similar_code

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, making safety traits clear. Description adds that it returns semantically similar code chunks but does not disclose performance, size limits, or other behavioral traits beyond annotations.

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?

Extremely concise: two sentences total, no filler. First sentence states purpose, second gives use cases. Every word adds value.

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 3 parameters, no output schema, and rich annotations, the description covers purpose and typical use cases. Could mention return format (code chunks) but the description already implies that. Mostly complete for a simple search tool.

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?

Input schema has 100% description coverage for all three parameters, so the schema already clarifies parameter meaning. Description reiterates 'Given a code snippet' but does not add new semantics beyond the schema.

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?

Clearly states verb 'find', resource 'similar code patterns', and outcome 'returns other code chunks that are semantically similar'. Distinguishes from sibling tools like a_semantic_search (general search) and b_index_codebase (indexing) by focusing on code pattern similarity.

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?

Provides explicit use cases: 'finding duplicate code, understanding patterns, and refactoring opportunities'. However, lacks explicit when-not-to-use guidance or comparison with siblings (e.g., a_semantic_search for non-code text).

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