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CD 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: BinKes v1.0.10 MIT-0 13 files · 8 scripts body ≈ 1 166 tokens Open the sourceclawhub.ai↗ analyzed 8 d ago

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

As a process D 41/100 · Unfinished process — References files that are not bundled: scripts/*.py

GeneratorMedia 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
89/100
safety, quality, tests
Safety 60%
94
Quality 40%
81
Run on models
none yet
Process rating
D
41/100
Unfinished process
References files that are not bundled: scripts/*.py
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: chanjing-customised-person (ClawHub)

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 · 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:143
    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:152
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    --id "C-ef…7ec"
    quoted

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

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: scripts/*.py
  • note frontmatter-key unknown frontmatter key "credential"
  • note frontmatter-key unknown frontmatter key "openclaw_primary_env"
  • note frontmatter-key unknown frontmatter key "environment"
  • note frontmatter-key unknown frontmatter key "legacy_environment"
  • note frontmatter-key unknown frontmatter key "machine_readable"
  • note frontmatter-key unknown frontmatter key "requires_ffmpeg"
  • note frontmatter-key unknown frontmatter key "requires_ffprobe"
  • note frontmatter-key unknown frontmatter key "notes"

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: scripts/*.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/*.py
  • 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. 15 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1166 tokens
  • low 13 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 129: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 36 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +3All 8 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: suspicious
The skill appears purpose-aligned, but it handles API secrets, uploads private videos to dynamic URLs, and can delete remote digital-human resources without enough safety checks.
LLM: suspicious (high) · VirusTotal: · 12 Sept 2026