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BF leio-sdlc

强制指令：执行 Software Development Life Cycle (SDLC)。所有的代码修改、Bug 修复和功能实现，必须且只能通过启动本技能中的 orchestrator.py 来完成。严禁主 Agent (你) 绕过本技能直接去操作源码工作区。

ClawHub Agent Skills author: leio9511 v1.0.0 MIT-0 80 files · 5 scripts body ≈ 275 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 43/100 · Will not run — References files that are not bundled: scripts/orchestrator.py

ProcedureAI and agentstype 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
B
81/100
safety, quality, tests
Safety 60%
99
Quality 40%
54
Run on models
none yet
Process rating
F
43/100
Will not run
References files that are not bundled: scripts/orchestrator.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token docs/PRDs/PRD_075_Robust_Git_State_Management.md:1
    High-entropy token-like string (may be an id, hash or a credential)
    # PRD_…ent

Files scanned: 78. 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")
  • warning missing-ref reference to a missing file: scripts/orchestrator.py

Process rating: all ten parameters 43/100

Will not run. References files that are not bundled: scripts/orchestrator.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/orchestrator.py
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 100Steps. 6 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 275 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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)
  • +4Structure: 2 headings, hard to scan
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -41 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +3Description length 132: enough signal without eating the budget
  • +3Step-by-step instructions: 6 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

External checks

ClawHub: suspicious
The skill is a real SDLC automation framework, but it gives agents broad code, Git, deployment, external-sync, hook, and service-restart authority that is not fully bounded or disclosed in the main skill instructions.
LLM: suspicious (high) · VirusTotal: · 29 May 2026