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BC huo15-img-test

火一五文生图提示词 v2.3 — 文生图&视频六件套：(1) enhance_prompt.py 文生图：88 风格预设 + 混合预设 (-p A+B --mix 0.6) + 五锁一致性 + 角色设定图 + 系列批量 + basic/pro/master 三档；(2) enhance_video.py 视频提示词：9 模型规格（Sora/Kling/Runway/Pika/Luma/Hailuo/即梦/Wan）+ 30 镜头运动 + 关键帧三段式；(3) reverse_prompt.py 参考图反解：A1111/ComfyUI/NovelAI metadata 自动识别 + VLM fallback；(4) render_prompt.py 直出图片：ComfyUI/SD-WebUI/DALL-E 三后端；(5) claude_polish.py ⭐v2.3 Claude API 智能润色：把粗糙描述转专业摄影/绘画术语 + 推荐预设/相机/光影；(6) safety_lint.py ⭐v2.3 平台合规润色：识别会被 SD/MJ/DALL-E 误判的艺术词汇并给出合法艺术化替代（仅服务合规艺术创作，拒绝违法/未成年/真人色情）。适配 Midjourney/SD/SDXL/Flux/DALL-E 3。触发词：文生图、火一五文生图提示词、文生视频、提示词、生成图片、生成视频、img-test、text to image、text to video、enhance prompt、提示词增强、图片一致性、系列图、角色一致、批量出图、混合风格、原神+敦煌、参考图反解、reverse prompt、提示词反解、ComfyUI 直出、SD WebUI、DALL-E、视频提示词、Sora、可灵、Runway、即梦、Hailuo、Claude 润色、智能润色、平台合规、艺术化重写。

ClawHub Agent Skills author: Job Zhao v2.3.0 MIT-0 11 files body ≈ 2 814 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentstype 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
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
C
58/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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
  • medium Exfiltration net-redirectable-api-key scripts/claude_polish.py:42
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment

Files scanned: 11. 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")
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "aliases"

Process rating: all ten parameters 58/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 25 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2814 tokens
  • 100Running it twice. No mutating operations
  • 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)
  • +3Output format is not stated: the model decides each time
  • -217 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 798: enough signal without eating the budget
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 6 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.

External checks

ClawHub: suspicious
This skill is transparent about its image-prompt features, but its “safety” mode intentionally rewrites sensitive prompts to improve acceptance by image platforms.
LLM: suspicious (high) · VirusTotal: · 29 May 2026