SKILLEMALL.ai

BD ai-video-studio

FableForge 通用视频生成流水线 SOP。支持两种生产模式(图片流、视频 B-roll 流)和三种体裁(叙事寓言、商业分析、产品宣发)。包含从概念生成、剧本创作、TTS 配音、素材采集、到 HyperFrames 视频渲染的完整工业化 SOP,以及视觉风格指南与技术陷阱手册。v1.2.0 新增 VAD 物理声学平铺匹配、语速自动健康度审计(防脱节门禁)、大分镜 GSAP 变量解耦与生命周期显隐控制。

ClawHub Agent Skills author: LucasL v1.2.0 MIT-0 15 files body ≈ 2 025 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureMedia and videoInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
70
Run on models
none yet
Process rating
D
41/100
Unfinished process
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: 15. 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 41/100

  • 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
  • 40Consistency. Frontmatter name (ai-video-studio) differs from the folder (fableforge)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 56 steps
  • 100Execution cost. Instruction body is 2025 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
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 205: enough signal without eating the budget
  • +4Structure: 25 headings
  • +3Step-by-step instructions: 56 items
  • +4Has examples (3 code blocks)

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

External checks

ClawHub: suspicious
This is a legitimate video-production workflow, but it needs Review because it can install tools, use a personal voice clone, and commit or push project files without enough consent gates.
LLM: suspicious (high) · 28 May 2026