Agent skill

Muapi AI Clipping

by hashgraph-online in hashgraph-online/awesome-codex-plugins

Turn a long video into N viral-ready short clips with a single managed API call.

Apache-2.0Auto-check passedMedia & Creative

Install Muapi AI Clipping

skills CLI

$ npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install hashgraph-online/awesome-codex-plugins muapi-ai-clipping --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping .claude/skills/muapi-ai-clipping && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "muapi-ai-clipping" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping into .claude/skills/muapi-ai-clipping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "muapi-ai-clipping", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install hashgraph-online/awesome-codex-plugins muapi-ai-clipping --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping .agents/skills/muapi-ai-clipping && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "muapi-ai-clipping" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping into .agents/skills/muapi-ai-clipping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "muapi-ai-clipping", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install hashgraph-online/awesome-codex-plugins muapi-ai-clipping --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping .cursor/skills/muapi-ai-clipping && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "muapi-ai-clipping" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping into .cursor/skills/muapi-ai-clipping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "muapi-ai-clipping", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/hashgraph-online/awesome-codex-plugins.git --path plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install hashgraph-online/awesome-codex-plugins muapi-ai-clipping --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping .gemini/skills/muapi-ai-clipping && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "muapi-ai-clipping" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping into .gemini/skills/muapi-ai-clipping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "muapi-ai-clipping", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install hashgraph-online/awesome-codex-plugins muapi-ai-clipping

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping .github/skills/muapi-ai-clipping && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "muapi-ai-clipping" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping into .github/skills/muapi-ai-clipping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "muapi-ai-clipping", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install hashgraph-online/awesome-codex-plugins muapi-ai-clipping --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping .opencode/skills/muapi-ai-clipping && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "muapi-ai-clipping" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping into .opencode/skills/muapi-ai-clipping/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "muapi-ai-clipping", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: muapi-ai-clipping
GitHub stars: 1.3k
Token cost: ~1.7k tokens
SKILL.md length: 672 words
Files: 2 (incl. scripts)
Skills in repo: 714
Repo updated: Oct 9, 2026
First seen: Oct 9, 2026
Licence: Apache-2.0

At a glance

Turn a long video into N viral-ready short clips with a single managed API call.

Works in 3 steps: Collect Inputs → Verify Prerequisites → Run the Skill
Tasks that involve Speech recognition and synthesis
SKILL.md covers When to Use, Agent Execution Protocol, What Happens Server-Side and Quick Invocation Patterns, plus 5 more sections
Runs Shell scripts from its folder; calls bash and jq; needs MUAPI_API_KEY

What it does

Muapi AI Clipping is an agent skill from hashgraph-online/awesome-codex-plugins. 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.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/run-ai-clipping.sh`).

It sits in Media & Creative, covering Speech recognition and synthesis, Backend development and Transcription. The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.

When your agent uses it

Tasks that involve Speech recognition and synthesis
Tasks that involve Backend development
Tasks that involve Transcription

Example prompts

“/muapi-ai-clipping”

Requirements

A Bash shell
A credential in MUAPI_API_KEY

Workflow steps

3 steps, taken from the step headings in SKILL.md.

Collect Inputs
Verify Prerequisites
Run the Skill

What it can do on your machine

Read from SKILL.md and the folder at commit 9e7b281. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Shell), which the agent can run.
Shell commands in SKILL.md call:
- bash
- jq
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- muapi.ai
- github.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- MUAPI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Muapi AI Clipping loads about 1.7k tokens when it runs. Until then it costs about 107 tokens; SKILL.md has 672 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~107
When it runs · the whole SKILL.md, loaded when a task matches: ~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from hashgraph-online/awesome-codex-plugins at commit 9e7b281, republished under its Apache-2.0 licence (© hashgraph-online). 672 words, ~1,690 tokens.

Download SKILL.mdSave it as .claude/skills/muapi-ai-clipping/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: muapi-ai-clipping
description: 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.
slug: muapi-ai-clipping
version: 1.0.0
acceptLicenseTerms: true

AI Clipping

One API call: long video in → ranked vertical short clips out.

Each clip ships with a viral score (0–100), an opening hook line, a one-sentence "why it works" reason, and a hosted mp4 URL.

Underlying API: https://muapi.ai/playground/ai-clipping Reference implementation (open source): https://github.com/SamurAIGPT/AI-Youtube-Shorts-Generator

When to Use

Auto-clip a podcast, interview, lecture, vlog, or stream into TikTok / Reels / Shorts.
Extract the best 30–75s moments from any hosted video URL.
Get face-tracked vertical (9:16), square (1:1), or portrait (4:5) crops without running ffmpeg locally.

If you only need raw timestamps for your own renderer, set --coords-only to skip cropping and just get the highlight ranges.

Agent Execution Protocol

Step 1 — Collect Inputs

Input	Required	Default	Notes
`--video`	yes	—	Hosted mp4 URL, or local file path (auto-uploaded), or YouTube URL (if backend supports it)
`--num-clips`	no	`3`	Number of highlights to extract
`--aspect-ratio`	no	`9:16`	`9:16` \| `1:1` \| `4:5`
`--coords-only`	no	off	Return just the highlight time ranges, skip cropping

If the user gave only a video URL, run with defaults — don't block on questions.

Step 2 — Verify Prerequisites

muapi-cli installed and authed (muapi auth configure)
MUAPI_API_KEY available (env var or muapi auth status passes)

That's it. No ffmpeg, no Python, no Whisper install, no LLM keys. Everything runs server-side.

Step 3 — Run the Skill

bash

bash library/edit/ai-clipping/scripts/run-ai-clipping.sh \
  --video "https://example.com/podcast.mp4" \
  --num-clips 5 \
  --aspect-ratio 9:16 \
  --view

The script:

Resolves --video to a hosted URL (uploads local files via muapi upload file if needed).
Calls muapi edit clipping with the supported parameters.
Polls until the job is done (or returns the request_id immediately under --async).
Prints a ranked summary and, if --output-json is set, writes the full result.

What Happens Server-Side

The /ai-clipping endpoint internally runs the full pipeline so the agent doesn't have to:

Transcribe with Whisper.
Classify content type (podcast / interview / tutorial / vlog / lecture / monologue).
Rank highlights through the virality framework:
- Hook moments — strong opening line that stops the scroll
- Emotional peaks — laughter, anger, vulnerability, awe
- Opinion bombs — spicy, contrarian, debate-bait takes
- Revelation moments — "wait, what?" reframes
- Conflict — disagreement, tension, callouts
- Quotable lines — tight, screenshot-worthy phrasing
- Story peaks — climax of a narrative arc
- Practical value — actionable insight a viewer will save
Dedupe overlapping candidates by score.
Top-N select and face-track auto-crop to the requested aspect ratio.

This is why the skill is small: the heavy lifting is on the API.

Quick Invocation Patterns

Defaults — three 9:16 clips:

bash

bash run-ai-clipping.sh --video "https://example.com/long.mp4"

Podcast — more clips, view in player:

bash

bash run-ai-clipping.sh --video "<URL>" --num-clips 8 --view

Square clips for Instagram feed:

bash

bash run-ai-clipping.sh --video "<URL>" --aspect-ratio 1:1 --num-clips 3

Just the timestamps (build your own renderer):

bash

bash run-ai-clipping.sh --video "<URL>" --coords-only --output-json result.json

Async submit (returns request_id, poll later):

bash

REQUEST_ID=$(bash run-ai-clipping.sh --video "<URL>" --async --output-json - | jq -r '.request_id')
muapi predict wait "$REQUEST_ID" --download ./outputs

Local file:

bash

bash run-ai-clipping.sh --video ./recording.mp4 --num-clips 5 --view

Batch — urls.txt with one URL per line:

bash

xargs -a urls.txt -I{} bash run-ai-clipping.sh --video "{}"

Show full SKILL.md (251 more words)Show less

Aspect Ratio Picker

Platform	Ratio	Sweet-spot duration
TikTok / Reels / YouTube Shorts	`9:16`	30–75s
Instagram Feed	`1:1`	15–45s
Pinterest / portrait	`4:5`	30–60s

Default to 9:16 unless the platform is specified.

Output Schema

json

{
  "source_video_url": "...",
  "shorts": [
    {
      "title": "The one mistake that cost me $50K",
      "start_time": 124.3,
      "end_time": 187.6,
      "score": 92,
      "hook_sentence": "Nobody talks about this, but it killed my first startup...",
      "virality_reason": "Opens with a number + regret, peaks on a contrarian lesson",
      "clip_url": "https://.../short_1.mp4"
    }
  ]
}

When --coords-only is set, each entry has start_time/end_time but no clip_url — render locally with ffmpeg.

When reporting back to the user, surface for each clip: rank, score, time range, title, hook, and clip URL.

Common Mistakes to Avoid

Wrong aspect ratio for the platform — Shorts / TikTok / Reels are 9:16. Default to that.
Padding to hit num_clips — if the API returns fewer survivors than requested, return what you have. Don't pretend.
Re-running on a 404'd clip URL — the same request_id can be re-fetched with muapi predict wait <id> rather than re-clipping.
Trying to tune Whisper / chunk size / LLM prompts — those knobs aren't exposed; the endpoint handles them.

Failure Modes

API key missing or rejected — surface the exact error; never fabricate a key.
Job timed out — bump poll timeout (--poll-timeout) and retry.
Source URL not reachable from the backend — upload locally with muapi upload file <path> first, then pass the returned URL.
Fewer clips returned than requested — the source had fewer rankable highlights. Return what came back with a note.

Done Criteria

The skill is done when:

result.shorts has up to num_clips entries, each with a working clip_url (or start_time/end_time under --coords-only).
The user has been shown the ranked list (score, time range, title, hook, URL).
If --output-json was set, the file exists and parses.

Files

SKILL.md and 1 other file (scripts) in plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping of hashgraph-online/awesome-codex-plugins.

SKILL.md
scripts/run-ai-clipping.sh

Open the folder on GitHubat commit 9e7b281

Compare with similar skills

Muapi AI Clipping next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Muapi AI Clipping compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Muapi AI Clipping this skillhashgraph-online/awesome-codex-plugins	1.3k	—	~1.7k	Automated safety check: Pass	Apache-2.0	today
Audio Transcriptionmitsuhiko/agent-stuff	3.2k	—	~1k	Automated safety check: Pass	Apache-2.0	12 days ago
Speech Recognitiondpearson2699/swift-ios-skills	1.2k	—	~3.7k	Automated safety check: Pass	Custom licence	2 mo ago
Stepfun Asrdaymade/claude-code-skills	1.4k	—	~3k	Automated safety check: Pass	MIT	today
Sttmikeyobrien/rho	372	—	~149	Automated safety check: Pass	MIT	9 days ago
Groq Core Workflow Bjeremylongshore/tons-of-skills-marketplace	2.8k	—	~1.4k	Automated safety check: Pass	MIT	yesterday

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Questions about Muapi AI Clipping

What does Muapi AI Clipping do?

Turn a long video into N viral-ready short clips with a single managed API call. Muapi AI Clipping is an agent skill from hashgraph-online/awesome-codex-plugins. Turn a long video into N viral-ready short clips with a single managed API call.

When should I use Muapi AI Clipping?

Muapi AI Clipping fits situations like: tasks that involve Speech recognition and synthesis; tasks that involve Backend development; tasks that involve Transcription.

How do I install Muapi AI Clipping in Claude Code?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a claude-code`. Or copy the skill folder (plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping in hashgraph-online/awesome-codex-plugins) into .claude/skills/muapi-ai-clipping in your project. Claude Code loads it when a task matches its description.

How do I install Muapi AI Clipping in Codex?

Run `npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a codex`. Or copy the skill folder (plugins/SamurAIGPT/Generative-Media-Skills/library/edit/ai-clipping in hashgraph-online/awesome-codex-plugins) into .agents/skills/muapi-ai-clipping in your project. Codex loads it when a task matches its description.

Can I use Muapi AI Clipping in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill muapi-ai-clipping -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/muapi-ai-clipping, .gemini/skills/muapi-ai-clipping, .github/skills/muapi-ai-clipping and .opencode/skills/muapi-ai-clipping in your project.

What does Muapi AI Clipping need to run?

Going by SKILL.md and its folder, Muapi AI Clipping needs a shell for the scripts in its folder, the command-line tools its instructions call (bash and jq) and credentials named MUAPI_API_KEY. Our summary lists: A Bash shell; A credential in MUAPI_API_KEY.

Does Muapi AI Clipping access the network?

SKILL.md names 2 domains. As links in the text: muapi.ai and github.com. This is read from the text; nothing was executed.

Is Muapi AI Clipping safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Muapi AI Clipping use?

Muapi AI Clipping is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Muapi AI Clipping use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Muapi AI Clipping?

Skills that share tags, products or a category with Muapi AI Clipping: Audio Transcription (mitsuhiko/agent-stuff, 3.2k stars), Speech Recognition (dpearson2699/swift-ios-skills, 1.2k stars), Stepfun Asr (daymade/claude-code-skills, 1.4k stars) and Stt (mikeyobrien/rho, 372 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Muapi AI Clipping?

hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,255 GitHub stars. The repository holds 714 skills in this directory. The repository was last updated on October 9, 2026.

Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Muapi AI Clipping

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

AI Clipping

When to Use

Agent Execution Protocol

Step 1 — Collect Inputs

Step 2 — Verify Prerequisites

Step 3 — Run the Skill

What Happens Server-Side

Quick Invocation Patterns

Aspect Ratio Picker

Output Schema

Common Mistakes to Avoid

Failure Modes

Done Criteria

Files

Compare with similar skills

Similar skills

More from hashgraph-online/awesome-codex-plugins

Related

Questions about Muapi AI Clipping