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

The description adds substantial behavioral context beyond annotations: it costs one extra LLM call, extracts answers only from tool result contents, and returns either a success payload or an explicit refusal with enumerated reasons. It clearly describes the refusal reasons and the evidence/confidence fields. This goes well beyond the structural readOnlyHint/idempotentHint annotations.

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 dense but every sentence earns its place: purpose, routing mechanics, return/refusal shapes, use cases, and cost tradeoff. It front-loads the core purpose and ends with actionable guidance for choosing between this tool and ask_pipeworx. No filler or redundant restatement.

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 there is no output schema, the description fully compensates by specifying the exact success return shape and refusal shapes with reasons. It covers routing scale, the extraction guarantee, when to use it, and the cost tradeoff. An agent has all decision-relevant context to invoke the tool correctly.

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%, with the question parameter fully described in natural language and aliases listed. The description adds no parameter-level details because none are needed; the schema already covers parameter semantics. Baseline of 3 is appropriate since the structured schema handles this dimension.

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 states a specific verb and resource: a grounded, hallucination-resistant answer mode that routes through Pipeworx and extracts answers only from tool results. It clearly distinguishes itself from ask_pipeworx by emphasizing evidence-backed answers and explicit refusal behavior. Sibling differentiation is explicit with 'Same routing as ask_pipeworx'.

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 states when to use the tool: high-stakes reads where answers will be quoted, cited, or acted on and facts must not be invented. It also gives concrete examples (financial verdicts, legal claims, medical lookups, public statements). It explicitly says to prefer ask_pipeworx for casual lookups, covering when not to use this tool.

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