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skill_feedback

Report skill execution outcomes and ratings to update bandit/Elo ranking and improve alternate retrieval through a continuous feedback learning loop.

Instructions

报告执行结果与评分,驱动 bandit/Elo 排名与备选检索(学习闭环;会覆盖同一次 skill_run 的自动记账,不重复计数)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskNo
runIdNoskill_run 返回的 runId;缺省时自动关联最近一次同 skill 的执行
skillYes
ratingNo
outcomeYes
beatenByNo
costCentsNo
latencyMsNo
workflowIdNo
Behavior4/5

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

没有 annotations,描述承担了行为披露责任:它明确说明会覆盖同一 skill_run 的自动记账,且不重复计数,还说明会影响 bandit/Elo 排名与备选检索。这比“提交反馈”这类模糊表达透明得多,但未提权限、失败条件或响应行为。

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?

一句话就传达执行目的、学习影响、覆盖语义和不重复策略,信息密度高且没有冗余。括号内的副作用说明是对主要用途的必要补充,而不是堆砌。

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

Completeness3/5

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

工具用途和最重要的副作用都已覆盖,但 9 个参数的实际取值范围和含义仍依赖 schema,而 schema 覆盖又很低;无输出 schema、无 annotations,描述也缺少对如 rating 刻度和 beatenBy 委托等字段的解释。整体可执行,但有关参数语义的缺口明显。

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

Parameters2/5

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

schema 覆盖率只有 11%,描述也没有对 skill、outcome、rating、costCents、latencyMs 等参数做补充说明。描述中的“结果与评分”和“覆盖自动记账”只能间接关联到 outcomlights/rating/cost/latency,无法弥补 9 个参数中 8 个缺少描述的问题。

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?

描述以“报告执行结果与评分”这个具体动词+对象开头,并说明它“驱动 bandit/Elo 排名与备选检索”,清楚定义了工具的核心职责。它与 skill_run、skill_search 等兄弟工具区分明显,不是对工具名的同义重复。

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?

描述通过“学习闭环”和“覆盖同一次 skill_run 的自动记账”暗示了应在 skill_run 之后用于提交反馈,并明确说明不会重复计数。虽然没有逐个对照兄弟工具给出 when-not-to-use,但已给出足够的调用时机与副作用边界。

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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