SKILLEMALL.ai
GitHub ↗ RU Sign in

AF dmaf

Set up and operate DMAF (Don't Miss A Face) — automated WhatsApp photo and video backup with face recognition and Google Photos upload. Use when a user wants to: (1) install and configure DMAF from scratch on GCP, (2) set up the OpenClaw WhatsApp media sync pipeline so group photos and videos flow automatically into Google Photos, (3) add or remove people from the face recognition database, (4) trigger a manual scan or check pipeline status, (5) troubleshoot face recognition misses, upload failures, or alerting issues.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files · 1 script body ≈ 692 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Set up and operate DMAF (Don't Miss A Face) — automated WhatsApp photo and video backup with face recognition and Google Photos upload.

As a process F 35/100 · Will not run — References files that are not bundled: ../mcp-setup.md

ProcedureWhatsAppGoogle CloudInfrastructureMedia 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
A
93/100
safety, quality, tests
Safety 60%
98
Quality 40%
85
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: ../mcp-setup.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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
  • low Dangerous commands cmd-cron-mention references/ops.md:92
    Mentions editing / listing crontab
    crontab -l | grep dmaf
  • low Dangerous commands cmd-cron-mention references/setup.md:193
    Mentions editing / listing crontab
    crontab -e

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../mcp-setup.md

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: ../mcp-setup.md
  • 0Tools and files. 1 referenced file(s) missing: ../mcp-setup.md
  • 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. 2 mutating operations with no state check
  • 100Steps. 13 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 692 tokens
  • 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 524: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.