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

The description discloses rich behavioral traits beyond the readOnly/openWorld/idempotent annotations: it always returns a specific shape with verbatim evidence, and refuses explicitly with enumerated refusal_reason values (not_in_source, no_tool_match, tool_error, data_truncated, llm_error). It also reveals the extra LLM call cost and the 'ONLY what the tool result contains' extraction constraint. No contradiction with 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 front-loaded with the core purpose, and every sentence carries distinct value: mechanism, return shape, refusal behavior, usage timing, and cost tradeoff. The inline enumeration of refusal reasons is lengthy but earns its place given there is no output schema to carry that contract.

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?

Despite having no output schema, the description fully specifies the success and failure return contracts, all refusal reasons, cost implications, routing scope, and evidence format. For a complex tool backed by thousands of sources, an agent has everything needed to invoke it correctly and interpret its results without guessing.

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% — the single semantic parameter 'question' is fully documented along with all six aliases (q, text, input, query, prompt). The description adds context about how the question gets routed across tools, but no syntax or formatting requirements beyond the schema, so the baseline 3 for full schema coverage is appropriate.

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+resource: 'Hallucination-resistant answer mode for high-stakes reads' — a grounded Q&A tool that routes through 5,798 tools and extracts answers only from tool results. It clearly differentiates from siblings by stating 'Same routing as ask_pipeworx' while adding the extraction/evidence contract that makes it distinct from both ask_pipeworx and ask_pipeworx_beta.

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?

Explicit when-to-use guidance: 'Use whenever an answer will be quoted, cited, or acted on... must not invent facts (financial verdicts, legal claims, medical lookups, public statements)'. It also gives the exclusion condition — 'prefer ask_pipeworx for casual lookups' — naming the alternative directly and supplying the cost-based reason for the choice.

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