AC self-eval
自我评估 / rubric 评分器（元认知闭环核心）。让 agent 对自己的输出做结构化、可复现的评分，而非凭感觉"我觉得不错"。提供多维度评分表（相关性/完整性/结构/准确性/可执行性）、自动 rubric 生成、可选参考答案重叠比对，输出打分 JSON + 改进建议。当用户需要"评估一下这段输出""给自己的回答打分""做个 rubric 评分""self-evaluation""检查质量"时调用。
自我评估 / rubric 评分器（元认知闭环核心）。让 agent 对自己的输出做结构化、可复现的评分，而非凭感觉"我觉得不错"。提供多维度评分表（相关性/完整性/结构/准确性/可执行性）、自动 rubric 生成、可选参考答案重叠比对，输出打分 JSON +…
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "visibility"
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 14 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 355 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 203: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 14 items
- +4Has examples (3 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.