CtrlK
BlogDocsLog inGet started
Tessl Logo

muapi-ai-clipping

Turn a long video into N viral-ready short clips with a single managed API call. Wraps muapi.ai's `/ai-clipping` endpoint, which handles transcription, highlight ranking through a virality framework (hook / emotional peak / opinion bomb / revelation / conflict / quotable / story peak / practical value), overlap dedupe, and vertical face-tracking auto-crop server-side. No local Whisper, no local LLM, no GPU.

58

Quality

67%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.opencode/skills/muapi-ai-clipping/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is well-structured, actionable, and workflow-oriented with concrete commands and a clear execution protocol. It would improve by tightening the redundant server-side explanation, reconciling the script-path references, and adding validation guidance for the batch pattern.

Suggestions

Reconcile the script path — use one consistent form (either the full `library/edit/ai-clipping/scripts/run-ai-clipping.sh` or bare `run-ai-clipping.sh`) throughout.

Tighten or shorten the "What Happens Server-Side" virality-framework list since it duplicates the description.

Add a per-item validation note for the batch (`xargs`) pattern, e.g. checking each run's exit code and surfacing failures.

DimensionReasoningScore

Conciseness

Mostly efficient and free of general-knowledge padding, but the "What Happens Server-Side" section re-enumerates the virality framework already summarized in the description, which could be tightened.

3 / 5

Actionability

Provides concrete, mostly copy-paste-ready bash invocations covering common cases (defaults, podcast, square, coords-only, async, local, batch) plus a real output schema; minor gap is the inconsistent script path (full vs. bare) and the referenced script not being present as a bundle file.

4 / 5

Workflow Clarity

Clear three-step Agent Execution Protocol with prerequisite verification (Step 2) and explicit Done Criteria as checkpoints; the optional batch pattern lacks a per-item validation/feedback loop, a minor gap.

4 / 5

Progressive Disclosure

Well-organized into clear sections functioning as an overview, with the executable artifact clearly signaled; however no bundle files exist in references/scripts/assets, and the script path is referenced inconsistently.

4 / 5

Total

15

/

20

Passed

Description

67%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, action-oriented, and highly distinctive, with strong concrete coverage of the server-side pipeline. Its main weakness is the missing explicit "Use when..." trigger guidance and the absence of platform synonyms that users naturally say.

Suggestions

Add an explicit trigger clause, e.g. "Use when turning a podcast, interview, lecture, or vlog into TikTok / Reels / Shorts."

Surface natural platform keywords (TikTok, Reels, Shorts, highlights) directly in the description rather than only in the body.

Consider trimming the inline virality-framework enumeration (hook / emotional peak / ...) since it duplicates the body and pads the description.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "transcription, highlight ranking through a virality framework..., overlap dedupe, and vertical face-tracking auto-crop" — giving comprehensive coverage of the pipeline rather than vague claims.

5 / 5

Completeness

The "what" is clearly stated (turn a long video into ranked short clips via a managed endpoint), but there is no explicit "Use when..." trigger clause, so completeness is capped at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

Contains natural terms like "long video" and "viral-ready short clips" but omits common platform synonyms users actually say (TikTok, Reels, Shorts, highlights), which only appear in the body, not the description.

3 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (muapi.ai `/ai-clipping` for viral vertical shorts) with distinct triggers and minimal overlap risk against general video or document skills.

5 / 5

Total

16

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
SamurAIGPT/Generative-Media-Skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.