tdg-personal/video-editing
AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.
88
88%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly communicates what the skill does (AI-assisted video editing covering cutting, structuring, and augmenting footage through a specific tool pipeline) and when to use it (explicit 'Use when' clause with natural trigger terms). The inclusion of specific tool names adds both distinctiveness and trigger term coverage. Uses appropriate third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'cutting, structuring, and augmenting real footage' plus names the full pipeline with specific tools (FFmpeg, Remotion, ElevenLabs, fal.ai, Descript, CapCut). This goes beyond naming a domain and provides a comprehensive picture of capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (AI-assisted video editing workflows for cutting, structuring, augmenting footage through a named tool pipeline) and 'when' with an explicit 'Use when...' clause listing trigger scenarios (edit video, cut footage, create vlogs, build video content). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'edit video', 'cut footage', 'create vlogs', 'build video content', plus tool names like FFmpeg, Remotion, Descript, CapCut that users might reference. Good coverage of both general and specific terms. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly occupies a distinct niche around video editing workflows with specific tool names (FFmpeg, Remotion, ElevenLabs, fal.ai, Descript, CapCut). The combination of 'real footage' editing and these specific tools makes it highly unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, comprehensive video editing skill with excellent actionability — nearly every section includes executable code or commands. The main weakness is the lack of validation checkpoints in the multi-step pipeline (no verification after FFmpeg cuts, no error handling guidance), and some philosophical/motivational content that doesn't add operational value for Claude. The progressive disclosure and overall structure are well done.
Suggestions
Add validation steps after FFmpeg operations, e.g., checking output file size/duration with `ffprobe` after cuts and concatenation to catch silent failures.
Trim the 'Core Thesis' section and reduce repeated 'edit don't generate' messaging — state it once in the intro and remove redundant mentions in Layer 5 and Key Principles.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with good code examples, but includes some unnecessary philosophical framing ('Core Thesis' section, repeated emphasis on 'edit don't generate'), and the 'What Each Tool Does Best' table partially duplicates information already conveyed in each layer's description. The 'When to Activate' section is somewhat verbose for Claude. | 2 / 3 |
Actionability | Excellent executable code throughout — FFmpeg commands are copy-paste ready, the Remotion TSX composition is complete, the ElevenLabs API call is fully functional with proper headers and file writing, and the bash scripts for batch cutting are immediately usable. Every layer has concrete, specific guidance. | 3 / 3 |
Workflow Clarity | The pipeline is clearly sequenced across 6 layers with a visual diagram, but there are no validation checkpoints or feedback loops. For a workflow involving batch FFmpeg operations and file concatenation, there should be explicit verification steps (e.g., checking segment integrity after cuts, validating concat output). The instruction 'Do not skip layers' is stated but not enforced with checks. | 2 / 3 |
Progressive Disclosure | Content is well-structured with clear sections per pipeline layer, appropriate references to external skills (fal-ai-media, videodb, content-engine) and external docs (Remotion docs). No deeply nested references. The layered structure itself serves as natural progressive disclosure, and related skills are clearly signaled at the end. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
Reviewed
Table of Contents