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CC Daily Devotional Auto Skill

Automated daily devotional generation for OpenClaw. Fetches news, generates contextual devotionals, creates videos with your voice, and uploads to YouTube automatically.

Not recommendedcritical or high security findings
modbender/skill-library-mcp Agent Skills author: modbender MIT 13 files · 2 scripts body ≈ 2 603 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Automated daily devotional generation for OpenClaw.

As a process C 57/100 · Has gaps — weak spots: when it triggers, consistency, running it twice

GeneratorYouTubeMedia and videotype 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
71/100
safety, quality, tests
Safety 60%
74
Quality 40%
67
Run on models
none yet
Process rating
C
57/100
Has gaps
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
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.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 9

  • high Exfiltration exfil-webhook-url INSTALL.md:270
    Webhook / callback URL commonly used for exfiltration (verify the destination)
    WEBHOOK_URL=https://hooks.slack.com/services/YOUR/WEBHOOK/URL
Medium and low: 8
  • low Exfiltration read-dotenv INSTALL.md:63
    Reads a .env file
    cp .env.example .env
  • low Dangerous commands cmd-cron-mention INSTALL.md:128
    Mentions editing / listing crontab
    crontab -e
  • low Dangerous commands cmd-cron-mention INSTALL.md:164
    Mentions editing / listing crontab
    crontab -l
  • low Exfiltration read-dotenv INSTALL.md:213
    Reads a .env file
    cat .env | grep API_KEY
  • low Exfiltration read-dotenv README.md:22
    Reads a .env file
    cp .env.example .env
  • low Exfiltration read-dotenv SKILL.md:82
    Reads a .env file
    cp .env.example .env
  • low Dangerous commands cmd-cron-mention SKILL.md:100
    Mentions editing / listing crontab
    crontab -e
  • low Dangerous commands cmd-cron-mention SKILL.md:304
    Mentions editing / listing crontab
    # Test crontab: crontab -l

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 57/100

  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 40Consistency. Frontmatter name (Daily Devotional Auto Skill) differs from the folder (daily-devotional-auto)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 85Steps. 93 steps, 1 vague phrases
  • 100Execution cost. Instruction body is 2603 tokens
  • low 17 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)
  • -32 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 169: enough signal without eating the budget
  • +4Structure: 55 headings
  • +3Step-by-step instructions: 93 items
  • +3Output format is stated explicitly
  • +4Has examples (23 code blocks)

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