SKILLEMALL.ai

AC qa-retrospective

当一个迭代结束、一个项目完成、或者发生线上事故需要事后分析时使用此技能。通过系统性的回顾会议和数据复盘,把个人和团队的经验教训转化为可复用的组织资产。不要沦为"说说好话走个形式"——有效的复盘需要有数据支撑(缺陷趋势/漏测分析/效率数据)、有根因分析(为什么出问题)和有 action items(下次怎么做不一样)。输出复盘报告和改进项追踪表。 触发场景:测试复盘、迭代复盘、项目复盘、经验沉淀、漏测分析、回顾总结、事后分析、反复出现同类问题需要根因改进时。 Use when the user asks about: test retrospectives and post-incident review — defect trends, escaped-defect analysis, efficiency data, and turning lessons into reusable assets.

ClawHub Agent Skills author: kokxi v1.8.0 MIT-0 3 files body ≈ 328 tokens Open the sourceclawhub.ai↗ analyzed 5 d ago

当一个迭代结束、一个项目完成、或者发生线上事故需要事后分析时使用此技能。通过系统性的回顾会议和数据复盘,把个人和团队的经验教训转化为可复用的组织资产。不要沦为"说说好话走个形式"——有效的复盘需要有数据支撑(缺陷趋势/漏测分析/效率数据)、有根因分析(为什么出问题)和有 action…

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerOperations and projectsInfrastructureLearningtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 59/100

    • 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
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 328 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 406: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a documentation-style QA retrospective skill with low runtime authority, though users should review the optional unpinned skill-set install command before running it.
    LLM: benign (high) · VirusTotal: · 29 Sept 2026