SKILLEMALL.ai
GitHub ↗ RU Sign in

AC qa-release-risk-governance

当版本要发布了、需要决定"能不能发"、或者需要设计灰度/回滚方案时使用此技能。系统化评估变更风险（变更范围/影响面/回退成本），设计灰度发布策略（按用户/区域/流量比例），制定回滚方案和线上监控计划。不要问"这个版本稳不稳"——要问"如果出问题了，我们能在几分钟内发现并回滚"。产出发布风险评估报告和灰度发布方案。 本技能属于 QA Test Skills 技能集（49 个技能之一），完整工作流体验需安装全套：npx skills add Kokxi/qa-test-skills

ClawHub Agent Skills author: kokxi v1.7.6 MIT-0 2 files body ≈ 851 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

当版本要发布了、需要决定"能不能发"、或者需要设计灰度/回滚方案时使用此技能。系统化评估变更风险（变更范围/影响面/回退成本），设计灰度发布策略（按用户/区域/流量比例），制定回滚方案和线上监控计划。不要问"这个版本稳不稳"——要问"如果出问题了，我们能在几分钟内发现并回滚"。产出发布风险评估报告和灰度发布方案。…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
53/100
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "related_skills"
  • note frontmatter-key unknown frontmatter key "input_format"
  • note frontmatter-key unknown frontmatter key "output_format"
  • note frontmatter-key unknown frontmatter key "categories"
  • note frontmatter-key unknown frontmatter key "depth_requirement_quantification"
  • note frontmatter-key unknown frontmatter key "error_recovery_guidance"

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. Tools declared in frontmatter
  • 100Steps. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 851 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 2 example trigger phrases
  • +3Description length 241: enough signal without eating the budget
  • +4Structure: 21 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (9 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill provides a Chinese-language release risk checklist and planning template without hidden execution, data export, or persistence.
LLM: benign (high) · VirusTotal: · 1 Sept 2026