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AD agent-constraints

给 coding agent 设置和治理约束——决定一条规则该落到 hook、AGENTS.md/CLAUDE.md、Skill、path-scoped rule 还是 prompt。当用户要写或改 AGENTS.md、CLAUDE.md、hooks、权限规则、Skill，或者问"agent 老犯某个错该怎么办"、"这条规则该放哪"、"我的 CLAUDE.md 太长了"、"怎么禁止 agent 动某个目录"、"怎么强制它跑完测试再结束"时使用。

ClawHub Agent Skills author: SnowsonZ v0.1.5 MIT-0 12 files · 1 script body ≈ 1 690 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

给 coding agent 设置和治理约束——决定一条规则该落到 hook、AGENTS.md/CLAUDE.md、Skill、path-scoped rule 还是 prompt。当用户要写或改 AGENTS.md、CLAUDE.md、hooks、权限规则、Skill，或者问"agent…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

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
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
45/100
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
  • 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: 11. 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 45/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 100Steps. 29 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1690 tokens
  • 100Progress reporting. Reports progress
  • low No test case covers injection arriving through data

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
  • +2Single-language instructions
  • +5Description quotes 5 example trigger phrases
  • +3Description length 224: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: clean
This is a disclosed guidance skill for managing agent constraints, with an optional local session-end logging hook that users should install only if they want cross-session review data.
LLM: benign (high) · VirusTotal: · 4 Sept 2026