SKILLEMALL.ai

AC ai-video-shot-sequence

设计连贯的镜头序列(Shot Sequence),构建场景的完整叙事弧线。适用于:从剧本到成片阶段,将单帧分镜扩展为有节奏、有情绪、有叙事张力的镜头序列。触发关键词:镜头序列, 分镜设计, 叙事节奏, 镜头衔接, 成片, 节奏曲线, 景别节奏, 序列设计, sequence, 序列模板, 情绪曲线, 镜头衔接, 叙事张力。当用户提到"这个场景怎么排镜头"、"这场戏的节奏怎么设计"、"镜头怎么衔接"、"分镜序列"、"叙事节奏"、"镜头sequence"时使用。本技能建立在 cinematic-storyboard-generator(七要素框架)基础之上,专注于序列层面的设计而非单帧设计。

ClawHub Agent Skills author: beermanzz v1.0.0 MIT-0 4 files body ≈ 938 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
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
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: 4. 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. 31 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 938 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

  • +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
  • +5Description quotes 4 example trigger phrases
  • +3Description length 297: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

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

External checks

ClawHub: clean
This is a markdown-only creative skill for planning AI video shot sequences, with no executable behavior or hidden access.
LLM: benign (high) · VirusTotal: · 29 May 2026