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开发者自改进核心技能 - 自动错误防重、自检、规则生成、记忆清洗、定时提醒 核心功能： - 每轮回答前：自动错误防重 - 每轮回答后：自动自检 + 生成规则草案 - 累计 10 轮对话/每周：自动记忆清洗扫描 - 自动提醒：每天 9:30 钉钉推送待确认规则 核心原则： - AI 只提议，人类终审 - 绝不自动写入/修改/删除长期记忆 - 用户指令 > 长期规则 > AI 临时草案

ClawHub Agent Skills author: Joe.Lee v1.1.9 MIT-0 10 files · 3 scripts body ≈ 1 171 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

ProcedureInfrastructuretype 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
85/100
safety, quality, tests
Safety 60%
97
Quality 40%
67
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 · 3

✓ No critical or high findings

Medium and low: 3
  • low Dangerous commands cmd-cron-mention README.md:57
    Mentions editing / listing crontab
    crontab -e
  • low Dangerous commands cmd-cron-mention scripts/setup-automation.sh:47
    Mentions editing / listing crontab (string literal in code, not executed)
    echo "   crontab -e"
    code literal
  • low Dangerous commands cmd-cron-mention SKILL.md:79
    Mentions editing / listing crontab
    crontab -e

Files scanned: 10. 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 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. No external tools needed
  • 100Steps. 4 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1171 tokens
  • 100Running it twice. No mutating operations
  • low 11 top-level sections: this looks like several domains in one skill

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
  • -214 emoji in the instructions: noise for the model
  • -31 of 3 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 194: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 4 items
  • +4Has examples (24 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: suspicious
This skill mostly matches its stated memory-helper purpose, but it includes an under-scoped auto-confirm path that can persistently change future agent behavior from free-form message text.
LLM: suspicious (high) · VirusTotal: · 29 May 2026