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CD project-daily-recap

项目进度定时复盘提醒 — 每晚8点自动推送复盘消息到微信，零LLM依赖，cron触发，适合工控/自动化/制造项目用

Not recommendedcritical or high security findings
ClawHub Agent Skills author: lynnsudo v1.2.0 MIT-0 7 files · 2 scripts body ≈ 643 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

项目进度定时复盘提醒 — 每晚8点自动推送复盘消息到微信，零LLM依赖，cron触发，适合工控/自动化/制造项目用

As a process D 48/100 · 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
C
60/100
safety, quality, tests
Safety 60%
59
Quality 40%
62
Run on models
none yet
Process rating
D
48/100
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

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 7

  • high Dangerous commands cmd-persistence setup.sh:132
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    CURRENT_CRON=$(crontab -l 2>/dev/null || true)
  • high Dangerous commands cmd-persistence setup.sh:141
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    (echo "$CLEANED_CRON"; echo "$CRON_LINE") | crontab -
Medium and low: 5
  • low Secrets in code secret-high-entropy-token setup.sh:99
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    CURRENT_TARGET="o9…@….wechat"
    detector
  • low Dangerous commands cmd-cron-mention setup.sh:132
    Mentions editing / listing crontab
    CURRENT_CRON=$(crontab -l 2>/dev/null || true)
  • low Dangerous commands cmd-cron-mention setup.sh:156
    Mentions editing / listing crontab (string literal in code, not executed)
    echo "  编辑 cron: crontab -e"
    code literal
  • low Dangerous commands cmd-cron-mention SKILL.md:121
    Mentions editing / listing crontab
    crontab -e
  • low Dangerous commands cmd-cron-mention SKILL.md:190
    Mentions editing / listing crontab (quoted — discussed, not commanded)
    → 检查 cron 是否运行：`crontab -l`
    quoted

Files scanned: 7. 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 "publisher"

Process rating: all ten parameters 48/100

  • 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
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 643 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)
  • +3Description length 57: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -229 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 16 items
  • +4Has examples (9 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
This is a real scheduled reminder skill, but it can install a persistent cron job and send project recap content to hardcoded messaging recipients that are not clearly controlled by the installer.
LLM: suspicious (high) · 12 Jul 2026