search_docs

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

Despite no annotations, the description fully discloses behavior: returns verbatim evidence, never fabricates, returns 'no confident match' on miss, and notes it is faster than web search. This provides complete transparency for an AI agent.

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 lengthy but well-structured and front-loaded with key purpose and usage guidelines. Each sentence adds value, though some redundancy could be trimmed. Still effective.

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 presence of an output schema, the description does not need to detail return values. It covers use cases, triggers, and behavioral guarantees. Sibling tools are not discussed, but the description is self-contained for this tool's purpose.

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 0% description coverage, so the description should compensate by explaining the parameters. However, it only mentions the query implicitly; there is no explanation of 'limit' or 'effort'. This leaves ambiguity for the agent.

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 that the tool searches an indexed corpus for embedded/firmware/hardware references and returns verbatim, page-cited evidence. It lists specific topics covered, making the purpose highly specific and distinguishable 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 explicitly tells when to call this tool, listing specific triggers (hex literals, Modbus codes, etc.) and states it is preferred over web search. It also warns against guessing and indicates it is cheap and safe to call multiple times.

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