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mark_finding

Mark a finding's adoption status to update review memory and adjust model reliability weights for future assessments.

Instructions

标记一条 finding 的采纳情况,写入 Review Memory,供下次 review 模型可信度加权。

finding_id/params_hash 从 review_document 返回取。未传 params_hash 时按 finding_id 反查最近含此 id 的 review(扫 consensus+majority+individual+deduped_ids)。 decision: accepted|rejected|partial。标记后默认失效该 review 缓存,下次同内容审查重算 reliability(该模型该维度按历史采纳率降/升权)。note 是 decision reason 自由文本。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
decisionYes
finding_idYes
params_hashNo
invalidate_cacheNo
Behavior5/5

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

With no annotations provided, the description fully carries the burden. It discloses that the tool writes to Review Memory, affects reliability weighting, and invalidates cache. It also details the decision options (accepted/rejected/partial) and the fallback lookup for params_hash. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with multiple sentences, each providing essential information. It is front-loaded with the main action, then explains details and fallbacks. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters, no output schema, and no annotations, the description covers purpose, input details, effects, and cache behavior. It lacks explicit mention of return value or error cases, but overall is quite complete for a state-updating tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must add meaning. It explains finding_id and params_hash come from review_document, decision values, and note purpose. The invalidate_cache parameter is not explicitly named, but its default behavior (cache invalidation) is described. Overall, it compensates well.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb '标记' (mark) and the resource 'finding', detailing that it records acceptance status into 'Review Memory' for future reliability weighting. This distinguishes it from sibling tools like mark_advice and mark_superseded.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains when to use the tool (after review_document returns finding_id/params_hash) and describes behavior for optional params_hash. It mentions cache invalidation and that it affects future weighting. However, it does not explicitly state when not to use it or compare to alternatives.

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

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