a_semantic_search

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds value by revealing the hybrid search approach (semantic + exact matching), which is behavioral insight beyond the 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?

Two sentences: first defines the action, second provides use case and output. Efficient, front-loaded, no unnecessary words. Every sentence 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?

Covers purpose, usage context, output format (snippets with file locations/line numbers). Missing details like result ordering or pagination, but given simplicity and presence of annotations, it is mostly 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?

Schema coverage is 100%, so both parameters are documented. The description does not add extra meaning beyond the schema (e.g., it mentions 'query' implicitly but no new details). Baseline 3 is appropriate.

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 performs 'intelligent hybrid code search combining semantic understanding with exact text matching.' It gives concrete examples like 'authentication logic' and specifies the return format. This distinguishes it from siblings like 'd_find_similar_code', which likely focuses on similarity alone.

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 explains it is 'ideal for finding code by meaning' and works with typos/variations, providing clear usage context. However, it does not explicitly say when not to use it or contrast with alternatives like 'd_find_similar_code'.

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