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

With no annotations to fall back on, the description carries the full burden and does so very well: it states the data is 'signed', 'ledger-derived', 'read from the live ledgers', and 'never fabricated'. It also discloses the no-charge `insufficient_subject` error behavior and the $0.01 per-call cost, which is exactly the kind of behavioral context an agent needs.

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 efficient: purpose, field scope, data provenance, error behavior, exclusions, alternatives, and cost are all packed into three well-organized sentences. It is front-loaded with the core purpose and every sentence adds useful information.

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 the tool's domain, data sources, error behavior, cost, and alternatives impressively. However, the lack of an output schema combined with the unresolved `subject` vs `task` parameter mismatch means an agent still cannot reliably construct a valid request. This is a noticeable completeness gap for a tool with no annotations.

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 description instructs callers to pass the agent name or erc8004 id as `subject`, but the input schema only defines a `task` parameter. The `task` description is generic ('Task/query text for this SKU') and the description never explains that `task` must carry the subject value. This active mismatch between the described parameter and the actual schema makes the parameter semantics misleading.

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 clearly identifies a specific resource (trust evidence about a NAMED BlindOracle agent), a specific action (return signed, ledger-derived trust evidence), and enumerates the concrete fields returned. It also differentiates itself from the related external-company research tools by explicitly naming what it does not do.

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 gives an explicit when-not-to-use and alternative tools for external company research: 'It does NOT research external companies; use procurement.vendor-vetting or ops.due-diligence-scan for that.' However, it does not distinguish itself from other close sibling trust tools like agent.trust-badge or reputation.lookup, so guidance is good but not fully comprehensive.

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