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

Annotations already cover readOnly/openWorld/idempotent/non-destructive safety. Beyond that, the description discloses critical runtime behavior: the exact refusal contract with the full refusal_reason enum ('not_in_source'|'no_tool_match'|'tool_error'|'data_truncated'|'llm_error'), the constraint that only tool-result content is used, the evidence-as-verbatim-quote guarantee, and the extra LLM call cost. This is substantial behavioral context that annotations alone could not convey.

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 information-dense and front-loaded with the key differentiator ('Hallucination-resistant'), followed by mechanism, return contract, usage guidance, and cost tradeoff — each sentence earns its place. It is slightly long as a single run-on block with em-dashes, and the refusal-reason list is verbose, but there is no wasted content.

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?

With no output schema, the description fully carries return-value documentation: it specifies the success shape ({answer, evidence, confidence, source, fetched_at, refusal_reason:null}) and the failure shape with enumerated reasons. Combined with cost tradeoffs, routing behavior, and sibling differentiation, nothing an agent needs to invoke this tool correctly is missing.

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 the baseline is 3. The schema already documents the single meaningful parameter (question) and all six aliases. The description mentions 'fills arguments' as part of routing but does not add parameter-specific semantics beyond what the schema provides — which is acceptable since the schema fully covers it.

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 precise purpose: 'Hallucination-resistant answer mode for high-stakes reads.' It names the specific verb ('EXTRACTS the answer using ONLY what the tool result contains'), the resource (routing across 5,798 tools/1517 sources), and explicitly anchors itself relative to a sibling ('Same routing as ask_pipeworx'). An agent can immediately distinguish this grounded mode from casual lookups.

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?

Provides an explicit trigger condition: 'Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts' with concrete domains (financial verdicts, legal claims, medical lookups, public statements). It also states the exclusion: 'prefer ask_pipeworx for casual lookups,' naming the alternative tool and the cost-based rationale. This is textbook when-to-use vs. when-not-to-use guidance.

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