research_record_verification

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

Annotations declare a non-read-only, non-destructive write. The description adds real behavioral context beyond that: historical attempts are retained (append-only history), and judgments are never auto-escalated, which tells the agent the write is additive and non-inferential. It does not cover permissions or error behavior, keeping it below 5.

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 compact clauses with no filler, and the core action is front-loaded before the constraints. The semicolon-separated rules are dense but readable, though the evidence and no-escalation rules could be ordered more helpfully.

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?

For a five-required-parameter mutation tool with no output schema and 20% schema coverage, the description covers the evidence-citation rule and append semantics but omits the identity parameters and how this differs from research_add_verification. It is minimally viable rather than complete.

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 only 20%, with study_id the lone documented property, so the description must carry most of the burden. It partially compensates by tying evidence_ids to passed/failed outcomes and naming the observed content, but explains nothing about the required study_id/verification_id linkage or the status enum semantics.

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?

States a specific verb (记录/record) and resource (人工验证的实际观察与通过/失败/阻塞状态), so an agent knows it writes a manual verification outcome rather than a claim or evidence. It does not differentiate itself from the closely-named sibling research_add_verification, leaving ambiguity about which one to call.

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 implies when the tool applies (recording manual verification results) and states a precondition (passed/failed must cite evidence), which is usable guidance. However, it never addresses the obvious alternative, research_add_verification, nor when a blocked status is appropriate versus passed/failed.

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