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

Annotations cover only the read-only and bounded-world profile, and the description adds material behavior the agent could not otherwise infer: a hard cost of $0.75 USDC per call, the x402 payment negotiation flow and exact retry mechanisms, board-count bounding, dedupe behavior, and explicit exclusions for LinkedIn scraping and applicant PII. That is exactly the kind of commercial and failure-mode context annotations cannot carry.

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?

Three tight sentences, zero filler, front-loaded with the payoff (what you get) before the operational constraints (cost, payment retry). Every clause earns its place by conveying capability, output shape, or payment mechanics.

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, so the description compensates by enumerating the returned fields (job IDs, titles, locations, URLs) and their deduped nature. Combined with the explicit cost and payment-retry semantics, an agent has everything needed to call this correctly and to handle the payment-required response.

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%, so both parameters are already documented in the schema (including the 1-to-10 slug/URL constraint). The description reinforces the ten-board cap but adds no new syntax, format, or validation detail for 'keyword' or for how slugs differ from careers URLs. Baseline 3 applies when the schema does the heavy lifting.

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 names a specific verb and resource plus the exact scope: hiring signals across up to 10 Greenhouse, Lever or Ashby boards, and it enumerates what comes back (deduped job IDs, titles, locations, URLs). No sibling in the list covers job postings, so there is no ambiguity in routing. It also states what it does not do (no LinkedIn scraping, no applicant PII).

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?

It clearly implies the use case (batch hiring-signal lookup for named companies) and gives an explicit procedural path for the non-obvious part: payment. It explains that an unpaid call returns the x402 requirements and how to retry (X-PAYMENT / PAYMENT-SIGNATURE header or params._meta["x402/payment"]). It does not, however, name an alternative tool or a condition where a different tool (e.g. lead_list, company_dossier) should be preferred.

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