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SKILL verified MIT Self-run

Jev Use

skill-shitianfang-jev-use-jev-use · by shitianfang

Use before ANY step that is a decision rather than writing: labelling, filtering or triaging MANY items; checking whether a command, test or build succeeded; picking the next action from options you can list; judging safety, quality or severity; or risk-checking each command of a checklist or pipeline before it runs. Route by where the facts already are: facts already in your context go to the je…

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Install

$ agentstack add skill-shitianfang-jev-use-jev-use

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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● 4d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

Handing off to Jev

Jev answers a typed judgment in ~250 ms at a judgment-model rate ($0.042/Mtok in, $0 out) instead of LLM reasoning. It is a RATE win, not a token win: Jev spends more tokens per decision, not fewer. So the saving is real only when the decision leaves the conversation — which is what the routing below is for. You stay the planner and the writer.

Route each decision: where are the facts × does it block?

| Where the facts are | Nothing is blocked — you can keep working | Blocked — nothing proceeds until this is decided | | --- | --- | --- | | Already in your context | jev_judge, every question about that state batched into ONE call (noul yes/no, choice next action, score quality) | jev_gate on that one action before you run it — and if it is every tool call, wire jev-use hook gate as a PreToolUse hook once and the decision leaves the conversation for good: 24 gated commands, 17.1 s, zero LLM tokens, vs 46.9 s / $0.2366 through a supervisor LLM | | Sitting in a file or tool output | a script pipes the file to jev-use judge — the items never enter your context | same CLI, from the script, then act on the verdicts it prints | | To be written by you (new text, code, options you cannot enumerate) | yours | yours |

Rules that make it pay off

  • Route bulk data by reference. When the items sit in a file or in tool

output, have a script pipe them to jev-use judge — data pasted into a jev_judge call travels through your context twice, as tool input and as the verdict block back. Or route only the handful you genuinely cannot settle yourself.

  • Batch. Measured: 12 questions about one state in ONE call took 224 ms;

the same 12 one at a time took 2,662 ms. Never one call per item.

  • State is everything Jev sees. Put the relevant facts (tool output, file

excerpts, task intent) into state; Jev has no other context.

  • Honor escalations. A verdict with escalate: true hands that question

back to you: writing/open_ended mean it was structurally yours; oversized means the state was too big to judge; unsure means Jev's answer is only a prior (it's still in answer — use it as a hint); unreachable means proceed as if Jev didn't exist.

  • Don't route trivia. If you already know the answer, just act; a Jev

call you didn't need is still a call.

Numbers, lanes, variance and caveats: bench/RESULTS.md.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.