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AC chanjing-customised-person

Use Chanjing customised person APIs to create, inspect, list, poll, and delete custom digital humans from uploaded source videos.

ClawHub Agent Skills author: zuoyuting214 v0.2.0 MIT-0 5 files body ≈ 625 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 54/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

GeneratorMedia and videoInfrastructuretype 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
92/100
safety, quality, tests
Safety 60%
94
Quality 40%
90
Run on models
none yet
Process rating
C
54/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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 · 6

    ✓ No critical or high findings

    Medium and low: 6
    • low Secrets in code secret-high-entropy-token examples.md:33
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file; quoted — discussed, not commanded)
      --id "C-ef…7ec"
      fixturequoted
    • low Secrets in code secret-high-entropy-token examples.md:40
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file; quoted — discussed, not commanded)
      --id "C-ef…7ec" \
      fixturequoted
    • low Secrets in code secret-high-entropy-token examples.md:54
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file; quoted — discussed, not commanded)
      --id "C-ef…7ec"
      fixturequoted
    • low Secrets in code secret-high-entropy-token reference.md:163
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "id": "C-ef…7ec"
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:98
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      --id "C-ef…7ec"
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:107
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      --id "C-ef…7ec"
      quoted

    Files scanned: 5. 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 54/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 8 mutating operations with no state check
    • 40Consistency. Frontmatter name (chanjing-customised-person) differs from the folder (zyt-customised-person)
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 25 steps
    • 100Execution cost. Instruction body is 625 tokens

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 129: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 25 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This is a disclosed Chanjing API helper, but it handles local API credentials and deletion of digital-human assets, so users should install it only with careful credential and deletion controls.
    LLM: benign (high) · VirusTotal: · 29 May 2026