get_known_issues

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

With no annotations, the description fully covers behavioral traits: cost of $0.05, payment via USDC on Base through x402, compute-first billing preventing charges for errors, refusal below 15 complaints with free partial data, and the requirement for EVM_PRIVATE_KEY in live mode. It even discloses hallucination-gating and complaint citation verification.

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 a single dense paragraph but every sentence adds value, explaining outputs, costs, refund logic, and requirements. It is longer than average but justifiably so given the complexity; a bulleted format could improve scannability.

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?

The description covers all major aspects: the main outputs, the bundled reliability block, recall counts, decoded vehicle, sample size, cost, payment method, refund policy, threshold behavior, and key requirements. Even without an output schema, it gives enough detail for an agent to understand what will be returned and what side effects may occur.

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?

The schema already provides a clear description of the only parameter (vin) with an example. The tool description does not add further semantic detail about the parameter beyond what the schema offers, so the score is at the baseline.

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 uses a specific verb (get) and resource (known failure modes for a VIN) and clearly differentiates the tool from siblings by detailing its bundled reliability aggregates, recall counts, and decoded vehicle. It is unambiguous about what the tool returns and its grounding in NHTSA ODI complaints.

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 provides clear context for when to use the tool: for VIN-level failure modes, reliability aggregates, recall counts, and a decoded vehicle. It mentions the 15-complaint threshold and free partial return, but does not explicitly state when to prefer alternatives like get_recalls or decode_vin, so it falls short of a 5.

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