SKILLEMALL.ai
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AC faces

Use this skill when the user wants to create, compile, or chat through a Face (a persona compiled from source material), compose personas with boolean formulas, compare minds by semantic similarity, import YouTube videos into a Face, or manage their Faces Platform account (API keys, billing, quotas). Also use when the user mentions the Faces Platform, the `faces` CLI, or asks about persona compilation, cognitive primitives, or mind arithmetic — even if they don't use those exact terms.

ClawHub Agent Skills author: sybileak v1.6.5 MIT-0 10 files body ≈ 2 163 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorYouTubeSoftware developmentMedia 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
96/100
safety, quality, tests
Safety 60%
99
Quality 40%
92
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Broad scope meta-dynamic-shell SKILL.md:21
      Shell command executed automatically when the skill loads (Claude Code !`cmd` preamble)
      !`faces config:show 2>/dev/null || echo "(no config saved)"`

    Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 63/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 9 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
    • 100Steps. 20 steps
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2163 tokens
    • low The response is described with custom markup (3 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
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 490: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 20 items
    • +4Has examples (11 code blocks)
    • +4Reference files are cited in the instructions (8 of 8)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: suspicious
    The skill is a coherent Faces Platform integration, but it needs review because it encourages remote persona-building with sensitive personal data and weak credential-handling examples.
    LLM: suspicious (high) · VirusTotal: benign · 28 May 2026