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AB facial-consultant

Analyze skin tone and facial attributes from a single selfie using YouCam (Perfect Corp) AI. Returns skin/eye/eyebrow/lip/hair colors plus facial feature shapes and golden-ratio proportions, as a readable report. Use for "測膚色", "臉型分析", "facial attributes". Do NOT use for skin-condition scoring (that's skin-analysis-expert), makeup, or hair try-on.

ClawHub Agent Skills author: YouCam API v1.0.1 MIT-0 11 files body ≈ 669 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Analyze skin tone and facial attributes from a single selfie using YouCam (Perfect Corp) AI.

As a process B 74/100 · Nearly there — weak spots: consistency

AnalyzerData and analyticsInfrastructuretype 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
95/100
safety, quality, tests
Safety 60%
98
Quality 40%
91
Run on models
none yet
Process rating
B
74/100
Nearly there
Consistency w 8
40
Failures and branches w 10
50
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

    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 Secrets in code secret-high-entropy-token scripts/api-fallback.yaml:34
      High-entropy token-like string (may be an id, hash or a credential)
      example: pfNK…Hjv+KoBIxbE=
    • low Secrets in code secret-high-entropy-token scripts/api-fallback.yaml:72
      High-entropy token-like string (may be an id, hash or a credential)
      example: pfNK…Hjv+KoBIxbE=

    Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "requirements"

    Process rating: all ten parameters 74/100

    • 40Consistency. Frontmatter name (facial-consultant) differs from the folder (youcam-facial-consultant)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 10 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 669 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
    • -34 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 349: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 10 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    The skill is mostly coherent, but it should be reviewed because it sends face images to a third-party API and its helper code exposes broader inputs and facial-analysis options than the stated single-selfie flow.
    LLM: suspicious (medium) · 4 Sept 2026