ask

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

With no annotations, the description carries the full disclosure burden. It usefully reveals the retrieval pipeline and the required LLM credentials, which is real operational context an agent needs. It omits what happens when those env vars are absent (failure mode), expected latency/cost of LLM calls, and whether the call is purely read-only.

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, front-loaded with the core purpose before the pipeline detail and the env prerequisite. No filler, though the pipeline jargon is dense for the value it adds to tool selection.

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?

There is no output schema, and the description does say the result is a cited answer, which covers the most important return-value question. However, the response shape (answer string vs. object with citations), parameter meanings, and failure behavior under missing credentials are all left to guesswork for a 3-parameter 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?

Schema description coverage is 0%, so the description must compensate and it largely does not: site_id, question, and top_k (default 4) are all undocumented. Only 'site_id' is obliquely covered by 'the site's pages'; top_k's meaning (retrieval candidates? reranked results?) is left entirely unexplained.

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 gives a specific verb+resource: answers a question grounded in the site's pages, returning a cited answer, and it names the mechanism (keyword retrieval + graph-neighborhood expansion, embedding rerank). This is far more informative than the bare name 'ask'. It never explicitly contrasts with siblings like search or neighbors, though the 'cited answer' framing implies the distinction.

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?

Usage is only implied: an agent can infer it should use this when it wants a synthesized, cited answer rather than raw pages from search/get_page. The one explicit guideline is an environmental prerequisite (SITE_KG_LLM_BASE / SITE_KG_LLM_KEY), not a when-to-use rule. No exclusions or alternative routing are stated.

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