CB chatcut-plugin-basics
Must read before using the hosted ChatCut plugin in Grok Bot, including creating projects, opening the editor, or editing/creating videos. Also use whenever video editing or creation should stay editable in ChatCut, even if the user does not mention ChatCut: edit or cut a video (剪视频、剪辑), add captions or subtitles (加字幕), clean up a talking-head recording (剪口播), add B-roll, music or motion graphics, or recreate, clone or remake a viral video with the user's own footage (复刻爆款、做同款). Also use when ChatCut tools are missing or need authentication. For ChatCut Desktop, follow its own instructions unless the user explicitly chooses the hosted plugin/web surface.
Must read before using the hosted ChatCut plugin in Grok Bot, including creating projects, opening the editor, or editing/creating videos.
As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, running it twice
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6993 tokens (recommended < 5000); move details to references/ - note
edit-residuethe text marks something as outdated (lines 213): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 72/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 18 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Execution cost. Instruction body is 6993 tokens
- 100Steps. 17 steps
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- low 12 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
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)
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 662: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 17 items
- +3Output format is stated explicitly
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.