SKILLEMALL.ai
GitHub ↗ RU Sign in

BF huo15-comic-orchestrator

一键生成 3-5 分钟国风 AI 漫剧。主题→分幕剧本→角色卡→分镜关键帧→图生视频→TTS 配音→对口型→BGM→字幕→拼接成片。自带三级成本熔断（硬限/预警/降级建议），支持失败续跑。触发词：AI 漫剧、生成漫剧、国风漫剧、仙侠短剧、comic drama、做漫剧。

ClawHub Agent Skills author: Job Zhao v0.1.0 MIT-0 9 files body ≈ 923 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 33/100 · Will not run — References files that are not bundled: scripts/script_gen.py, examples/demo-xianxia-180s.json

ProcedureInfrastructuretype 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
B
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
64
Run on models
none yet
Process rating
F
33/100
Will not run
References files that are not bundled: scripts/script_gen.py, examples/demo-xianxia-180s.json
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. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token scripts/_shared/config.py:104
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "male_mature":   "zh_m…tts",      # 京腔侃爷（成熟磁性）
    quoted

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: scripts/script_gen.py
  • warning missing-ref reference to a missing file: examples/demo-xianxia-180s.json
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "aliases"

Process rating: all ten parameters 33/100

Will not run. References files that are not bundled: scripts/script_gen.py, examples/demo-xianxia-180s.json
  • 0Tools and files. 2 referenced file(s) missing: scripts/script_gen.py, examples/demo-xianxia-180s.json
  • 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
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 923 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 135: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (5 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: suspicious
The skill is a coherent AI comic-generation orchestrator, but it can launch paid external generation through unreviewed sibling skills and its cost-control documentation is stronger than the included runtime code.
LLM: suspicious (high) · VirusTotal: · 29 May 2026