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

With no annotations provided, the description fully carries the disclosure burden. It states the tool returns verbatim, page-cited text, never fabricates, returns 'no confident match' on a miss, and is 'cheap and safe to call several times per task.' This goes well beyond basic operation details and gives the agent a clear trust model.

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 very long, but the density is largely justified by the broad corpus coverage and detailed usage triggers. The first sentence states the core purpose, though the massive trigger list appears later in the paragraph, making it less front-loaded than ideal. Every section adds value, but the structure could be tightened with headings or a more prominent 'when to use' callout.

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 complexity and the presence of an output schema, the description covers all necessary decision points: what the corpus contains, when to use it over alternatives, what behavior to expect, and how to treat misses. The only minor gap is parameter-level detail, but that does not hinder tool selection or basic invocation.

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 schema has 0% description coverage, so the description must compensate. It does elaborate on the query parameter by listing many example search triggers (hex literals, protocol codes, register names, etc.). However, it gives no explanation of the 'limit' or 'effort' parameters, leaving their semantics to be inferred from defaults and names alone.

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 opens with a specific verb and resource: 'Search the indexed embedded / firmware / hardware reference corpus; return verbatim, page-cited evidence.' This clearly distinguishes it from siblings by naming the corpus and the nature of the returned evidence, and the later list of concrete search triggers reinforces what the tool does.

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 instructs when to use the tool ('Call search_docs the moment you see any of these - before answering from memory and before any web search'), provides comprehensive examples of triggering content, and names the alternative (web search) with reasoning for preference. It also explains behavior on no match, making the usage decision unambiguous.

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