SKILLEMALL.ai

AC raise-ai-media

RaiseAI 媒体生成工具集 - 生图、生视频、脚本生成、图片解析、视频解析。 当用户提到以下任何关键词时必须触发此技能:生成图片、生成视频、图片生成、视频生成、脚本生成、 图片解析、图生文、反推提示词、视频解析、视频脚本、图片生图、视频生视频、 AI生图、AI生视频、AI创作、Media generation、image generation、video generation、 text-to-image、text-to-video、图片转视频、一键成片。 即使用户没有明确使用上述词汇,只要他们要求制作图片、视频、脚本,或从图片/视频中提取内容,都应使用此技能。 ⚠️ 默认行为(重要):用户没有明确要求"高质量"或"质感好"时,图片必须用 `image_generation` + `fast=false` + `resolution=HD`,视频必须用 `fast_video` + `resolution=HD`。不要擅自升级到 `image_generation_pro`,除非用户明确说了"高质量"、"效果好"、"质感好"等。

ClawHub Agent Skills author: JacobLUXJ v1.0.0 MIT-0 8 files body ≈ 935 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
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 · 0

✓ No critical or high findings

Files scanned: 8. 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")

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 935 tokens
  • 100Running it twice. No mutating operations

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 475: enough signal without eating the budget
  • +4Structure: 14 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
The skill appears to do what it claims, but it asks users to share and persist an API key through chat, which needs careful review before installation.
LLM: suspicious (high) · VirusTotal: · 29 May 2026