Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, highly actionable pipeline skill with strong workflow sequencing, validation gates, and clean progressive disclosure into real reference/script files. The only weakness is verbosity in the surrounding prose.
Suggestions
Tighten the narrative prose between commands — e.g. trim asides like 'Hook advice: the first 1.5–2s decides scroll-past' and restate rationales once rather than re-explaining gate philosophy in multiple sections.
Move the phase-based pacing table and cut_plan.json schema details into references/ if the body is meant to stay a lean overview, keeping only the essential flag usage inline.
Consolidate repeated environment-variable mentions (GEMINI_API_KEY / GOOGLE_AI_API_KEY / GOOGLE_API_KEY) to a single definition in Requirements rather than restating across Step 6 and Step 7.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Operational and free of basic-concept padding, but ~240 lines of narrative prose around each command (rationale, asides like 'the first 1.5–2s decides scroll-past') could be tightened without losing clarity. | 2 / 3 |
Actionability | Fully executable, copy-paste-ready commands with exact flags throughout, plus concrete JSON plan examples and per-step script invocations. | 3 / 3 |
Workflow Clarity | A clearly sequenced 7-step pipeline with two explicit human gates, automated QC checkpoints (check_cuts.py), staleness enforcement, and fix-and-re-render feedback loops for a batch/destructive workflow. | 3 / 3 |
Progressive Disclosure | SKILL.md is an operational overview with one-level-deep, clearly signaled references (ffmpeg-recipes.md, captions-and-gemini.md, brand-style.md) and a scripts/ bundle; referenced paths are real files. | 3 / 3 |
Total | 11 / 12 Passed |