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BC overnight-worker

Autonomous overnight work agent — assign tasks before sleep, get structured results by morning. Supports smart task decomposition, web research, multi-format output, progress logging, error recovery, and push notifications. (中文) 夜间自主工作 Agent：智能任务拆解、多格式输出、进度日志、错误恢复、通知推送。

ClawHub Agent Skills author: fullstackcrew-alpha v1.0.1 MIT-0 7 files · 2 scripts body ≈ 1 580 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentsInfrastructuretype 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
86/100
safety, quality, tests
Safety 60%
94
Quality 40%
74
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write Edit Grep Glob WebSearch WebFetch Task Agent
  • low Exfiltration exfil-webhook-url scripts/notify.sh:75
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    -X POST "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/sendMessage" \
    placeholder

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 "user_invocable"

Process rating: all ten parameters 60/100

  • 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
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 74 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1580 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (12 tags): a typed call is more reliable

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
  • -5TODO / placeholder text left in the skill
  • +2Single-language instructions
  • +3Description length 270: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 74 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 2 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
This skill is an unattended productivity assistant with broad but disclosed tools, local report output, web research, and optional external notifications.
LLM: benign (high) · VirusTotal: · 29 May 2026