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

Beyond the annotations (which only declare it a safe, idempotent, closed-world read), the description discloses substantial behavior: outputs are verbatim quotes, 'no model writes anything', a four-value status taxonomy is never guessed, results are deterministic, and it is free with no payment or account required. This is exactly the extra 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?

Single front-loaded paragraph that leads with what the tool does and then piles on return and status detail. Dense but every clause carries information; the inline status enumeration makes it slightly heavy to scan, keeping it short of a 5.

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?

With no output schema, the description correctly shoulders the return-value burden by describing quoted passages with source/section/link plus the set of status outcomes. It omits the conversational continuation behavior of trace_id, but that is covered by the schema, so the gap is minor.

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 question, limit, product, agent_id and trace_id are all already documented (including the product enum mapping to board/verifier/scores). The description adds no syntax or semantics beyond the schema and never mentions the trace_id conversation-continuation parameter, so baseline 3 applies.

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 (answers a question) and a tightly bounded resource corpus (SarnAI's published documents for the Agent Discovery Board, Agent Output Verifier, and Agent Scores), and specifies the output form (verbatim passages with source, section and link). This is clearly distinguishable from siblings like find_agents or search_listings, which operate over live agent/listing data rather than product documentation.

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?

Usage is implied rather than stated: the tool is for questions about the three named products. It adds useful signal about question types ('what is' gets the defining passage first; price/free-path questions get a direct answer), but never says when to prefer this over sibling tools like how_to_pay or get_listing, nor any exclusions.

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