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

No annotations are present, so the description carries the burden. It discloses the indexed sources and the return shape (ID, source type, URL, title, matched passages in markdown), which is valuable. It does not state read-only semantics, rate limits, freshness, or pagination behavior beyond k, leaving meaningful gaps for a no-annotation tool.

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 tight sentences with zero waste; the source scope is front-loaded and the return shape follows naturally. Every sentence earns its place.

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 3-parameter search tool with no output schema, the description covers both the searchable corpus and the return fields, which is what an agent needs to call it correctly. Minor gaps (pagination, freshness) remain but are not blocking.

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 description coverage is 100%, so the baseline is 3. The description's mention of library/error-message/API phrasing echoes what the query parameter already documents, and the 'skills' enum parameter is not explained in the description.

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?

Specifies a clear verb (Search) and a well-scoped resource: an index of public repos, GitHub issues, merged PRs, READMEs, and code documentation. This distinguishes it thematically from firecrawl_search (general web) and firecrawl_research_search_papers (papers), though it stops short of naming those siblings explicitly.

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 phrase 'for programming questions that need external documentation or upstream evidence' gives useful when-to-use context. However, there is no explicit when-not guidance and no named alternative (e.g., firecrawl_search) to route between, leaving selection partly to inference.

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