HyperFrames Audio
heygen-com/hyperframes
Mixes audio already placed in a HyperFrames composition: fades, gain, ducking under a voiceover, effect chains, automation and shared submix buses.
Inspect generated images, video and audio before delivery using deterministic metadata, contact-sheet, black-frame and silence checks plus visual and listening review.
MITAuto-check passed
Install AI Media Quality Review
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins ai-media-quality-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/magichourhq/skills/skills/ai-media-quality-review .claude/skills/ai-media-quality-review && rm -rf skills-srcUse ~/.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/
Install the "ai-media-quality-review" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-review into .claude/skills/ai-media-quality-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-media-quality-review", 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 install https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-reviewType 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.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins ai-media-quality-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/magichourhq/skills/skills/ai-media-quality-review .agents/skills/ai-media-quality-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-media-quality-review" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-review into .agents/skills/ai-media-quality-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-media-quality-review", 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.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins ai-media-quality-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/magichourhq/skills/skills/ai-media-quality-review .cursor/skills/ai-media-quality-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-media-quality-review" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-review into .cursor/skills/ai-media-quality-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-media-quality-review", 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 https://github.com/hashgraph-online/awesome-codex-plugins.git --path plugins/magichourhq/skills/skills/ai-media-quality-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins ai-media-quality-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/magichourhq/skills/skills/ai-media-quality-review .gemini/skills/ai-media-quality-review && rm -rf skills-srcUse ~/.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/
Install the "ai-media-quality-review" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-review into .gemini/skills/ai-media-quality-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-media-quality-review", 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.
$ gh skill install hashgraph-online/awesome-codex-plugins ai-media-quality-reviewInstalls 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).
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/magichourhq/skills/skills/ai-media-quality-review .github/skills/ai-media-quality-review && rm -rf skills-srcUse ~/.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/
Install the "ai-media-quality-review" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-review into .github/skills/ai-media-quality-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-media-quality-review", 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.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins ai-media-quality-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/magichourhq/skills/skills/ai-media-quality-review .opencode/skills/ai-media-quality-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-media-quality-review" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/magichourhq/skills/skills/ai-media-quality-review into .opencode/skills/ai-media-quality-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-media-quality-review", 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
ai-media-quality-review- GitHub stars
- 1.3k
- Token cost
- ~715 tokens
- SKILL.md length
- 339 words
- Files
- 4 (incl. scripts)
- Skills in repo
- 716
- Repo updated
- First seen
- Licence
- MIT
At a glance
Inspect generated images, video and audio before delivery using deterministic metadata, contact-sheet, black-frame and silence checks plus visual and listening review.
- Repair Magic Hour media outputs
- Runs Python scripts from its folder; calls python3
- It does not generate media
- Predict audience performance
What it does
AI Media Quality Review is an agent skill from hashgraph-online/awesome-codex-plugins. Inspect generated images, video and audio before delivery using deterministic metadata, contact-sheet, black-frame and silence checks plus visual and listening review. Use to accept, reject or repair Magic Hour media outputs; it does not generate media or predict audience performance.
Its SKILL.md is about 720 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `agents/openai.yaml` and `scripts/inspect_media.py`).
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 MIT.
When your agent uses it
- Repair Magic Hour media outputs
- It does not generate media
- Predict audience performance
Example prompts
- “/ai-media-quality-review”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 3e1456a. 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/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
AI Media Quality Review loads about 715 tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 339 words of instructions outside code blocks.
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 3e1456a, republished under its MIT licence (© hashgraph-online). 339 words, ~715 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-media-quality-review/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- ai-media-quality-review
- description
- Inspect generated images, video and audio before delivery using deterministic metadata, contact-sheet, black-frame and silence checks plus visual and listening review. Use to accept, reject or repair Magic Hour media outputs; it does not generate media or predict audience performance.
- license
- MIT
- metadata.author
- magichourhq
- metadata.version
- 1.0.1
AI media quality review
Review the actual downloaded file against its brief and source media. Run the bundled inspection script when FFmpeg and FFprobe are available:
python3 scripts/inspect_media.py /absolute/path/to/output.mp4 --output-dir /absolute/path/to/reviewThe script creates probe.json, review.json and a contact sheet or waveform. It reports technical signals; it does not decide whether the creative result is good. A diagnostic failure stops the script and removes an earlier review.json in that output directory. Treat a nonzero exit or missing report as unverified, never as a clean result.
Apply the acceptance criteria
Read the original request and list the few required outcomes and protected details. Inspect the generated artifacts at full size and the intended delivery size.
- Image: composition, crop, identity, anatomy, hands, geometry, product/character details, required text and logos, unwanted text and visible artifacts.
- Video: first and last frames, intended action and camera, identity/object continuity, flicker, warping, abrupt cuts, actual dimensions, frame rate, duration and audio streams.
- Speech/music: listen through the full export; check intelligibility, pronunciation, last word or phrase, clipping, silence, mouth timing, cut points and synchronization.
Inspect the actual last frame as well as the contact sheet. A gradual fade can darken a face without crossing the black-frame threshold; an empty black_segments list does not rule it out. Review contact-sheet flags in context. Intentional black or silent sections are not defects. A clean diagnostic report cannot prove smooth motion, accurate lip sync, good music or a compelling result. Full-speed viewing and listening remain required for those claims.
Return a compact verdict for each requirement: pass, fail or unverified, with the observed evidence. A successful request, valid file or plausible thumbnail is not a quality pass.
When repair is authorized, identify the smallest failed requirement and return to the last accepted source. Change the relevant reference, prompt, route, interval or deterministic finishing step. Do not regenerate an accepted shot to fix captions, crop or assembly, and do not continue spending beyond the existing limit.
Deliver the accepted file and retain the review folder with it. State any unavailable playback, listening, source comparison or broad-subject validation.
© hashgraph-online, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts) in plugins/magichourhq/skills/skills/ai-media-quality-review of hashgraph-online/awesome-codex-plugins.
- SKILL.md
- LICENSE
- agents/openai.yaml
- scripts/inspect_media.py
Open the folder on GitHubat commit 3e1456a
Compare with similar skills
AI Media Quality Review 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Media Quality Review this skillhashgraph-online/awesome-codex-plugins | 1.3k | — | ~715 | Automated safety check: Pass | MIT | |
| HyperFrames Audioheygen-com/hyperframes | 60k | 1 repos | ~6.5k | Automated safety check: Pass | Apache-2.0 | |
| Node Inspect Debuggeropenclaw/openclaw | 392k | 1 repos | ~894 | Automated safety check: Pass | MIT | |
| Audio Descriptionsthedaviddias/Front-End-Checklist | 74k | — | ~549 | Automated safety check: Pass | MIT | |
| Venice Audio Musicnexu-io/open-design | 100k | — | ~297 | Automated safety check: Pass | Apache-2.0 | |
| Team AudioDonchitos/Claude-Code-Game-Studios | 26k | — | ~4.4k | Automated safety check: Notes | MIT |
Similar skills
Node Inspect Debugger
openclaw/openclaw
Debug Node.js with node inspect, --inspect, breakpoints, CDP, heap, and CPU profiles.
Audio Descriptions
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing rendered HTML, interactive components, or design-system patterns related to Provide audio descriptions for video.
Venice Audio Music
nexu-io/open-design
Music generation queueing, retrieval, and completion endpoints via Venice.ai.
Team Audio
Donchitos/Claude-Code-Game-Studios
Orchestrate the audio team — audio-director, sound-designer, technical-artist, gameplay-programmer — direction through implementation.
Delivery Gate
affaan-m/ECC
Stop hook that blocks Claude from finishing until quality checks pass.
More from hashgraph-online/awesome-codex-plugins
All 715 skills in this repoAnime Reaction Gif
hashgraph-online/awesome-codex-plugins
Create original anime-style reaction stickers as looping GIFs and MP4 previews, using generated character pose sheets and timed key poses.
Calibredb
hashgraph-online/awesome-codex-plugins
Manage and query Calibre libraries with the calibredb CLI (local paths or Calibre Content server URLs).
Rust API Test Harness
hashgraph-online/awesome-codex-plugins
A skill your agent uses when adding, changing, testing, or debugging Rust HTTP APIs and services, especially when Codex needs black-box integration tests, random-port app startup, real database test…
Art
hashgraph-online/awesome-codex-plugins
Make a studio's game look like something at build time — a cover from a real frame of the game (free), painted covers, backdrops, textures and character plates from image models through the…
Calle
hashgraph-online/awesome-codex-plugins
Use CALL-E from Codex through the calle CLI. An agent skill from hashgraph-online/awesome-codex-plugins.
Game Balance Economy
hashgraph-online/awesome-codex-plugins
Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.
Questions about AI Media Quality Review
What does AI Media Quality Review do?
Inspect generated images, video and audio before delivery using deterministic metadata, contact-sheet, black-frame and silence checks plus visual and listening review. AI Media Quality Review is an agent skill from hashgraph-online/awesome-codex-plugins. Inspect generated images, video and audio before delivery using deterministic metadata, contact-sheet, black-frame and silence checks plus visual and listening review.
When should I use AI Media Quality Review?
AI Media Quality Review fits situations like: repair Magic Hour media outputs; it does not generate media; predict audience performance.
How do I install AI Media Quality Review in Claude Code?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a claude-code`. Or copy the skill folder (plugins/magichourhq/skills/skills/ai-media-quality-review in hashgraph-online/awesome-codex-plugins) into .claude/skills/ai-media-quality-review in your project. Claude Code loads it when a task matches its description.
How do I install AI Media Quality Review in Codex?
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill ai-media-quality-review -a codex`. Or copy the skill folder (plugins/magichourhq/skills/skills/ai-media-quality-review in hashgraph-online/awesome-codex-plugins) into .agents/skills/ai-media-quality-review in your project. Codex loads it when a task matches its description.
Can I use AI Media Quality Review 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 ai-media-quality-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-media-quality-review, .gemini/skills/ai-media-quality-review, .github/skills/ai-media-quality-review and .opencode/skills/ai-media-quality-review in your project.
What does AI Media Quality Review need to run?
Going by SKILL.md and its folder, AI Media Quality Review needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does AI Media Quality Review access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is AI Media Quality Review 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 AI Media Quality Review use?
AI Media Quality Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does AI Media Quality Review use?
About 715 tokens (SKILL.md is roughly 2.9k 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 AI Media Quality Review?
Skills that share tags, products or a category with AI Media Quality Review: HyperFrames Audio (heygen-com/hyperframes, 60k stars), Node Inspect Debugger (openclaw/openclaw, 392k stars), Audio Descriptions (thedaviddias/Front-End-Checklist, 74k stars) and Venice Audio Music (nexu-io/open-design, 100k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Media Quality Review?
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,267 GitHub stars. The repository holds 716 skills in this directory. The repository was last updated on October 10, 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.