Crush Configuration
charmbracelet/crush
Explains how to configure the Crush coding agent with crushrc or crush.json, covering providers, models, LSPs, MCP servers, hooks, permissions and config precedence.
Route enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jevjudge and jevgate MCP tools, batched into one call per state.
$ npx skills add majiayu000/claude-skill-registry --skill jev-use -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install majiayu000/claude-skill-registry jev-use --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/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/bash/jev-use .claude/skills/jev-use && 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-use" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-use into .claude/skills/jev-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-use", 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/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-useType 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 majiayu000/claude-skill-registry --skill jev-use -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install majiayu000/claude-skill-registry jev-use --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/bash/jev-use .agents/skills/jev-use && 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-use" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-use into .agents/skills/jev-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-use", 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 majiayu000/claude-skill-registry --skill jev-use -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install majiayu000/claude-skill-registry jev-use --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/bash/jev-use .cursor/skills/jev-use && 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-use" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-use into .cursor/skills/jev-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-use", 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/majiayu000/claude-skill-registry.git --path skills/bash/jev-use--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 majiayu000/claude-skill-registry --skill jev-use -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install majiayu000/claude-skill-registry jev-use --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/bash/jev-use .gemini/skills/jev-use && 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-use" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-use into .gemini/skills/jev-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-use", 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 majiayu000/claude-skill-registry jev-useInstalls 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 majiayu000/claude-skill-registry --skill jev-use -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/bash/jev-use .github/skills/jev-use && 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-use" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-use into .github/skills/jev-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-use", 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 majiayu000/claude-skill-registry --skill jev-use -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install majiayu000/claude-skill-registry jev-use --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/bash/jev-use .opencode/skills/jev-use && 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-use" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/bash/jev-use into .opencode/skills/jev-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "jev-use", 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.
jev-useRoute enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jevjudge and jevgate MCP tools, batched into one call per state.
Jev Use is an agent skill from majiayu000/claude-skill-registry. Route enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jevjudge and jevgate MCP tools, batched into one call per state.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).
It sits in Agent Workflows, covering MCP servers. It works with Bash. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
npxFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
TYPESAFE_API_KEYOPENROUTER_API_KEYAI_GATEWAY_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Jev Use loads about 2.5k tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 1,148 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.
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.
The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 1,148 words, ~2,491 tokens.
.claude/skills/jev-use/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Splits an agent loop by whether a step must produce text. Steps that only produce a decision - is the build done, which of these 30 elements to click, is this shell command safe, keep or drop this message - are handed to Jev, TypeSafe's judgment model, which answers typed yes/no, pick-one and score questions about a state in one forward pass instead of generating tokens. The agent stays the planner and the writer; Jev takes the quick calls.
Everything Jev should not decide comes back under a typed escalation contract, so the handoff is explicit in both directions rather than a guess.
npx -y jev-use installinstall wires the stdio MCP server into Claude Code, Codex and pi through each harness's own CLI - whichever it finds - and npx -y jev-use doctor verifies backend resolution with one live round trip. Set a provider credential in the environment the agent runs in (TYPESAFE_API_KEY, OPENROUTER_API_KEY or AI_GATEWAY_API_KEY, auto-detected in that order), or set JEV_BACKEND=mock to run keyless with no network calls.
| The step is... | Route |
|---|---|
| Producing new content: text, code, free-form tool args | You |
| A judgment, but the options can't be enumerated | You |
| A yes/no or "did it work?" over context you already have | jev_judge (noul) |
| Picking the next action from options you can list | jev_judge (choice) |
| Rating quality/severity/urgency on levels you can describe | jev_judge (score) |
| "Is this action safe to run?" before something risky | jev_gate |
jev_judge takes a single state string plus a questions[] array. Latency is flat in question count, and the cost of the shared state amortizes across the batch, so 13 batched questions cost far less than 13 separate calls. Never call it once per question.
Each verdict carries {id, type, answer, confidence, escalate}, plus reason and hint exactly when escalate is true. An escalated verdict is handed back to you - it is a normal verdict with a hint, never an exception:
reason | When | What it means for you |
|---|---|---|
writing | pre-call | The step must produce new text or code - structurally yours. |
open_ended | pre-call | Not expressible as noul/choice/score; nothing to enumerate. |
oversized | pre-call | The state exceeds the size limit - shrink it or take the questions over. |
unsure | post-call | The answer is too flat to act on; it stays in answer as a prior. |
unreachable | on failure | Jev could not be reached - proceed as if it did not exist. |
The two pre-call reasons come from a deterministic router, so a step that was never Jev's does not spend a request.
// jev_judge input
{
"state": "CI run #142: build ok, 214 tests passed, 0 failed; 1 test quarantined as flaky last week",
"questions": [
{ "id": "passed", "type": "noul", "question": "Did the run fully succeed?" },
{ "id": "next", "type": "choice", "question": "Next action?",
"options": { "merge": "everything green", "rerun": "looks flaky", "hold": "needs attention" } },
{ "id": "risk", "type": "score", "question": "How risky is merging now?",
"levels": ["routine", "worth a look", "incident"] }
]
}// result (shape exact, values illustrative)
{
"verdicts": [
{ "id": "passed", "type": "noul", "answer": 0.97, "confidence": 0.94, "escalate": false },
{ "id": "next", "type": "choice", "answer": "merge", "confidence": 0.34, "escalate": true,
"reason": "unsure",
"hint": "Treat the answer as a prior, not a decision - reason it out yourself." },
{ "id": "risk", "type": "score", "answer": 0.8, "confidence": 0.81, "escalate": false,
"legend": { "0": "routine", "1": "worth a look", "2": "incident" } }
],
"escalated": true
}Two verdicts are usable immediately. The third came back escalated with reason: "unsure", so that one question - and only that one - returns to you, with Jev's answer kept as a hint.
A score answer is the expected position on your own levels: 0.8 means "between routine and worth a look, closer to the latter", and legend maps the indices back to your words.
// jev_gate input
{
"state": "Cleaning up build output in the project checkout after a failed release build",
"tool": "Bash",
"input": { "command": "rm -rf ./dist" }
}// result
{ "decision": "deny", "confidence": 0.88, "hint": "..." }jev_gate returns allow, deny or escalate for one proposed action. allow is silence: it falls through to the harness's normal permission flow, so the gate can never grant anything - it can only deny or ask. If Jev is unreachable the gate steps aside rather than granting.
jev_judge call.state. Jev sees nothing else about your session.escalate on every verdict before acting on answer.options and levels in your own words; a label -> meaning map sharpens a choice.jev_judge once per question.unsure answer as a decision, or treat allow from jev_gate as authorization.state; it has no view of your conversation, repository or tool history, so a thin state produces a thin judgment.oversized instead of being judged.0.75, but through the Vercel gateway no confidence field is returned and a top-minus-runner-up margin is used instead, with a default threshold of 0.4.state is sent to the provider you configure. Keep secrets, credentials and customer data out of it, or set JEV_BACKEND=mock, which judges locally with no key and no network call.TYPESAFE_API_KEY, OPENROUTER_API_KEY, AI_GATEWAY_API_KEY). Never paste a key into a state string, a prompt, or a committed file.jev_gate is not a permission system. It can deny or ask; it cannot grant. Keep your harness's own approval rules in place, and expect the gate to step aside if the backend is down.npx -y jev-use install edits local harness configuration through each harness's own CLI. Run it on a machine you control and re-run npx -y jev-use doctor afterwards to see what resolved.unsure.
Solution: The state is usually missing the fact the question depends on. Put the concrete tool output or file excerpt into state instead of a summary of it, and give options/levels distinguishable meanings.reason: "oversized".
Solution: Trim state to the evidence the questions actually need, or split one oversized state into two smaller judged states.writing or open_ended.
Solution: That is the router working. The step was structurally yours; do it yourself rather than rephrasing it to get past the check.© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/bash/jev-use of majiayu000/claude-skill-registry.
Open the folder on GitHubat commit 2d14a69
We found 7 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 8, 2026.
Jev Use 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 Use this skillmajiayu000/claude-skill-registry | 666 | 2 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Crush Configurationcharmbracelet/crush | 29k | — | ~3.7k | Automated safety check: Pass | Custom licence | |
| Record Demoapify/mcpc | 983 | — | ~3.3k | Automated safety check: Notes | Apache-2.0 | |
| Releasejgravelle/jcodemunch-mcp | 2.7k | — | ~6.5k | Automated safety check: Pass | Custom licence | |
| Mcpcapify/mcpc | 983 | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Tool Selectiondatabricks-solutions/ai-dev-kit | 1.9k | — | ~519 | Automated safety check: Pass | Custom licence |
charmbracelet/crush
Explains how to configure the Crush coding agent with crushrc or crush.json, covering providers, models, LSPs, MCP servers, hooks, permissions and config precedence.
apify/mcpc
Record or regenerate the mcpc demo GIFs (the README hero docs/images/mcpc-demo.gif and the focused tapes in docs/vhs/) with VHS.
jgravelle/jcodemunch-mcp
Publishing a jMunch release (jcodemunch-mcp, jdocmunch-mcp, jdatamunch-mcp, jragmunch-cli), reviewing/merging/closing PRs, and responding to the community.
apify/mcpc
Use the mcpc CLI to work with MCP (Model Context Protocol) servers from the shell - connect to a server as a persistent session, then list and call tools, read resources, get prompts, and run async…
databricks-solutions/ai-dev-kit
Evaluates whether the agent selected appropriate MCP tools instead of shell workarounds.
okooo5km/Skills4U
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majiayu000/claude-skill-registry
Multi-source deep research using firecrawl and exa MCPs. An agent skill from majiayu000/claude-skill-registry.
majiayu000/claude-skill-registry
Neural search via Exa MCP for web, code, and company research.
majiayu000/claude-skill-registry
Unified media generation via fal.ai MCP — image, video, and audio.
majiayu000/claude-skill-registry
Interact with Zotero reference management libraries using the pyzotero Python client.
majiayu000/claude-skill-registry
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server.
majiayu000/claude-skill-registry
Perform pairwise sequence alignment using Biopython Bio.Align.PairwiseAligner.
Works with
Categories
Route enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jevjudge and jevgate MCP tools, batched into one call per state. Jev Use is an agent skill from majiayu000/claude-skill-registry. Route enumerable judgment steps - did it work, which option, how risky, is this safe to run - to the Jev judgment model through the jevjudge and jevgate MCP tools, batched into one call per state.
Jev Use fits situations like: tasks that involve MCP servers.
Run `npx skills add majiayu000/claude-skill-registry --skill jev-use -a claude-code`. Or copy the skill folder (skills/bash/jev-use in majiayu000/claude-skill-registry) into .claude/skills/jev-use in your project. Claude Code loads it when a task matches its description.
Run `npx skills add majiayu000/claude-skill-registry --skill jev-use -a codex`. Or copy the skill folder (skills/bash/jev-use in majiayu000/claude-skill-registry) into .agents/skills/jev-use in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill jev-use -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-use, .gemini/skills/jev-use, .github/skills/jev-use and .opencode/skills/jev-use in your project.
Going by SKILL.md and its folder, Jev Use needs the command-line tools its instructions call (npx) and credentials named TYPESAFE_API_KEY, OPENROUTER_API_KEY and AI_GATEWAY_API_KEY. Our summary lists: Node.js; A credential in TYPESAFE_API_KEY; A credential in OPENROUTER_API_KEY.
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
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.
Jev Use is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Jev Use: Crush Configuration (charmbracelet/crush, 29k stars), Record Demo (apify/mcpc, 983 stars), Release (jgravelle/jcodemunch-mcp, 2.7k stars) and Mcpc (apify/mcpc, 983 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.
Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.