Remotion Interactivity
remotion-dev/remotion
Structure Remotion markup for interactivity. An agent skill from remotion-dev/remotion.
Use Jev to prune lengthy output from non-interactive build, test, install, and search commands in Codex.
MITAuto-check passed
Install Jev Pruner
$ npx skills add tamaratran/jev-pruner --skill jev-pruner -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tamaratran/jev-pruner jev-pruner --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/tamaratran/jev-pruner.git skills-src && mkdir -p .claude/skills && cp -r skills-src/codex/skills/jev-pruner .claude/skills/jev-pruner && 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 "jev-pruner" agent skill from https://github.com/tamaratran/jev-pruner/tree/main/codex/skills/jev-pruner into .claude/skills/jev-pruner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-pruner", 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/tamaratran/jev-pruner/tree/main/codex/skills/jev-prunerType 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 tamaratran/jev-pruner --skill jev-pruner -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tamaratran/jev-pruner jev-pruner --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tamaratran/jev-pruner.git skills-src && mkdir -p .agents/skills && cp -r skills-src/codex/skills/jev-pruner .agents/skills/jev-pruner && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "jev-pruner" agent skill from https://github.com/tamaratran/jev-pruner/tree/main/codex/skills/jev-pruner into .agents/skills/jev-pruner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-pruner", 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 tamaratran/jev-pruner --skill jev-pruner -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tamaratran/jev-pruner jev-pruner --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tamaratran/jev-pruner.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/codex/skills/jev-pruner .cursor/skills/jev-pruner && 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 "jev-pruner" agent skill from https://github.com/tamaratran/jev-pruner/tree/main/codex/skills/jev-pruner into .cursor/skills/jev-pruner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-pruner", 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/tamaratran/jev-pruner.git --path codex/skills/jev-pruner--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 tamaratran/jev-pruner --skill jev-pruner -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tamaratran/jev-pruner jev-pruner --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tamaratran/jev-pruner.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/codex/skills/jev-pruner .gemini/skills/jev-pruner && 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 "jev-pruner" agent skill from https://github.com/tamaratran/jev-pruner/tree/main/codex/skills/jev-pruner into .gemini/skills/jev-pruner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-pruner", 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 tamaratran/jev-pruner jev-prunerInstalls 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 tamaratran/jev-pruner --skill jev-pruner -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tamaratran/jev-pruner.git skills-src && mkdir -p .github/skills && cp -r skills-src/codex/skills/jev-pruner .github/skills/jev-pruner && 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 "jev-pruner" agent skill from https://github.com/tamaratran/jev-pruner/tree/main/codex/skills/jev-pruner into .github/skills/jev-pruner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-pruner", 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 tamaratran/jev-pruner --skill jev-pruner -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tamaratran/jev-pruner jev-pruner --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tamaratran/jev-pruner.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/codex/skills/jev-pruner .opencode/skills/jev-pruner && 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 "jev-pruner" agent skill from https://github.com/tamaratran/jev-pruner/tree/main/codex/skills/jev-pruner into .opencode/skills/jev-pruner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-pruner", 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
jev-pruner- GitHub stars
- 160
- Token cost
- ~462 tokens
- SKILL.md length
- 230 words
- Files
- 1
- Skills in repo
- 3
- Repo updated
- First seen
- Licence
- MIT
At a glance
Use Jev to prune lengthy output from non-interactive build, test, install, and search commands in Codex.
- Calls node; needs TYPESAFE_API_KEY
What it does
Jev Pruner is an agent skill from tamaratran/jev-pruner. Use Jev to prune lengthy output from non-interactive build, test, install, and search commands in Codex.
Its SKILL.md is about 460 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it. The licence is MIT.
Example prompts
- “/jev-pruner”
Requirements
- A credential in TYPESAFE_API_KEY
What it can do on your machine
Read from SKILL.md and the folder at commit edbc602. 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
Shell commands in SKILL.md call:
node
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 these keys or tokens, usually read from environment variables:
TYPESAFE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Jev Pruner loads about 462 tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 230 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from tamaratran/jev-pruner at commit edbc602, republished under its MIT licence (© tamaratran). 230 words, ~462 tokens.
Download SKILL.mdSave it as
.claude/skills/jev-pruner/SKILL.md (or your agent's skills folder).- name
- jev-pruner
- description
- Use Jev to prune lengthy output from non-interactive build, test, install, and search commands in Codex.
Resolve the plugin root as three directories above this skill's directory.
The installed plugin must already have dist/codex/run.js built.
For non-interactive commands that may produce lengthy output, use the native Codex shell tool to execute:
node "<plugin-root>/dist/codex/run.js" -- npm testArguments after -- are passed directly to the executable, without evaluation
by a second shell. Preserve their quoting. For a compound shell program, pass
the intended shell explicitly, for example -- bash -c 'command1 && command2'.
Keep the original workdir, sandbox settings, and approval requirements.
Do not request broader permissions solely to make pruning work.
Use the ordinary shell directly for interactive/TTY commands, servers, commands whose live progress is required, whole-file reads, diffs, structured data, and commands involving secrets. Do not wrap nested calls that require machine-readable output. This wrapper buffers stdout until completion (up to 8 MiB), forwards stderr unchanged, and preserves the exit code. It does not intercept other shell calls.
Only stdout over 10,000 estimated tokens is eligible. The trusted PreToolUse
hook records the current transcript path; the wrapper uses CODEX_THREAD_ID to
load that session's user/assistant messages and complete recorded tool results.
Missing history, missing TYPESAFE_API_KEY, blocked Jev network access, failed
commands, archive failures, and scoring failures return the original stdout.
Never claim pruning occurred without seeing an omission marker.
Read or search the archive path in the final footer whenever omitted output is needed. Retained text is verbatim; Jev does not generate a summary.
© tamaratran, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in codex/skills/jev-pruner of tamaratran/jev-pruner.
Open the folder on GitHubat commit edbc602
Compare with similar skills
Jev Pruner 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 |
|---|---|---|---|---|---|---|
| Jev Pruner this skilltamaratran/jev-pruner | 160 | — | ~462 | Automated safety check: Pass | MIT | |
| Remotion Interactivityremotion-dev/remotion | 63k | 5 repos | ~4.8k | Automated safety check: Pass | Custom licence | |
| Firecrawl Interact Integrationfirecrawl/firecrawl | 190k | 1 repos | ~731 | Automated safety check: Pass | ISC | |
| Jev Socialsickn33/agentic-awesome-skills | 47k | 1 repos | ~3.4k | Automated safety check: Pass | MIT | |
| Jev Usesickn33/agentic-awesome-skills | 47k | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Interaction To Next Paintthedaviddias/Front-End-Checklist | 74k | — | ~441 | Automated safety check: Pass | MIT |
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Questions about Jev Pruner
What does Jev Pruner do?
Use Jev to prune lengthy output from non-interactive build, test, install, and search commands in Codex. Jev Pruner is an agent skill from tamaratran/jev-pruner. Use Jev to prune lengthy output from non-interactive build, test, install, and search commands in Codex.
How do I install Jev Pruner in Claude Code?
Run `npx skills add tamaratran/jev-pruner --skill jev-pruner -a claude-code`. Or copy the skill folder (codex/skills/jev-pruner in tamaratran/jev-pruner) into .claude/skills/jev-pruner in your project. Claude Code loads it when a task matches its description.
How do I install Jev Pruner in Codex?
Run `npx skills add tamaratran/jev-pruner --skill jev-pruner -a codex`. Or copy the skill folder (codex/skills/jev-pruner in tamaratran/jev-pruner) into .agents/skills/jev-pruner in your project. Codex loads it when a task matches its description.
Can I use Jev Pruner 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 tamaratran/jev-pruner --skill jev-pruner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/jev-pruner, .gemini/skills/jev-pruner, .github/skills/jev-pruner and .opencode/skills/jev-pruner in your project.
What does Jev Pruner need to run?
Going by SKILL.md and its folder, Jev Pruner needs the command-line tools its instructions call (node) and credentials named TYPESAFE_API_KEY. Our summary lists: A credential in TYPESAFE_API_KEY.
Does Jev Pruner 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 Jev Pruner 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. Review the folder before installing.
What licence does Jev Pruner use?
Jev Pruner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Jev Pruner use?
About 462 tokens (SKILL.md is roughly 1.8k 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 Jev Pruner?
Skills that share tags, products or a category with Jev Pruner: Remotion Interactivity (remotion-dev/remotion, 63k stars), Firecrawl Interact Integration (firecrawl/firecrawl, 190k stars), Jev Social (sickn33/agentic-awesome-skills, 47k stars) and Jev Use (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Jev Pruner?
tamaratran (a GitHub user) maintains it in tamaratran/jev-pruner, which has 160 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on September 30, 2026.
Source: tamaratran/jev-pruner on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.