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AD worktree-codex

使用 git worktree 隔离多个 Codex 实例，由 OpenClaw 主控器并行调度完成同一项目的不同编码模块。 适用场景：将一个编码项目拆分为独立子任务，让多个 Codex 实例并行实现，最后合并 PR。 触发条件：用户要求"多个 Codex 协作"、"并行编码"、"worktree 编码"、"多 Codex 编排"、"并行完成项目"时激活。

modbender/skill-library-mcp Agent Skills author: modbender MIT 6 files · 3 scripts body ≈ 907 tokens Open the sourcegithub.com↗ analyzed 2 d ago

使用 git worktree 隔离多个 Codex 实例，由 OpenClaw 主控器并行调度完成同一项目的不同编码模块。 适用场景：将一个编码项目拆分为独立子任务，让多个 Codex 实例并行实现，最后合并 PR。 触发条件：用户要求"多个 Codex 协作"、"并行编码"、"worktree 编码"、"多…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureGitHubSoftware 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
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
D
43/100
Unfinished process
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: 6. 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")

Process rating: all ten parameters 43/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 9 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 907 tokens

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
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 4 example trigger phrases
  • +3Description length 179: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 9 items
  • +4Has examples (10 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.