omh-jev-ask

omh-jev-ask is a skill for Claude Code, Codex from rlaope/oh-my-hermes. It costs 72 tokens per session (691 once invoked), scanned A, original, MIT.

An AI judging tool that sends text and typed questions to Jev and returns probabilities, the model used, cost information, or a non-answer status.

In plain words
What is it for?
Use it to ask yes-or-no, choice, or ordered-score questions about supplied text and report the returned confidence and model details.
Why use it?
It provides a recorded, uncertainty-aware judgment rather than presenting an AI answer as a definite fact.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to ask yes-or-no, choice, or ordered-score questions about supplied text and report the returned confidence and model details.

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Install with agentmods
npx agentmods add skills/rlaope/oh-my-hermes/omh-jev-ask
About the project

oh-my-hermes is an operating layer for Hermes Agent that organizes requests into workflows for planning, research, creation, coding handoffs, operations, and project memory. Hermes users run these workflows through the desktop app, CLI, or messenger app, while the catalogue add-ons extend its native capabilities.

rlaope/oh-my-hermes · 3,392 stars · on GitHub · rlaope.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add rlaope/oh-my-hermes --skill omh-jev-ask
Clone the repo
git clone --depth 1 https://github.com/rlaope/oh-my-hermes

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for omh-jev-ask

README.md
[![agentmods](https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-jev-ask/github.svg)](https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-jev-ask)
Your own site
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-jev-ask"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-jev-ask/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for omh-jev-ask

Your own site · 80×15
<a href="https://agentmods.dev/skills/rlaope/oh-my-hermes/omh-jev-ask"><img src="https://agentmods.dev/badge/skills/rlaope/oh-my-hermes/omh-jev-ask.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 691 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.00691
Opus 5.5 $0.00029 $0.00276
Sonnet 5.5 $0.00014 $0.00138
Haiku 4.5 $0.00007 $0.00069

Measured 3d ago against content hash c6f20e55034a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

omh-jev-ask scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/omh-jev-ask/SKILL.md · 46 lines

How it starts

The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Jev Ask

Required: text to judge and independent typed questions. Output: Jev's probabilities, served model, and cost, or a non-answer status.

Read skill_view(name='omh-routing', file_path='references/jev-rail.md') before the first ask: consent, what leaves the machine, limits, and non-answer statuses. Prepared OMH routing is not execution or approval. Shared product, routing, compatibility, and evidence rules: skill_view(name='omh-routing', file_path='references/skill-common-rail.md').

Contract: references/full-contract.md.

Procedure

  1. Check the rail: the user asked for Jev in this turn, and say in one line what state will carry.
  2. Write independent, self-contained questions over one state: Noul with criteria.true/criteria.false, Choice with an unknown option, Score with ordered levels.
  3. Call omh_jev_ask with questions (default model jev-latest; pin jev-1.13.0 when a threshold was tuned).
  4. Report each number verbatim with the served model, attempts, and cost_usd plus cost_source; 0.4 to 0.6 is uncertain.

Completion Checklist

  • Preserve workflow intent and stop conditions; load the full contract before claiming completion.
  • Reply in the user's own words and the host's own voice: its SOUL.md persona owns reply language, tone, speech level, and sentence endings, progress updates included (where it sets no language, use the one the user wrote in), and OMH shapes structure and content only; OMH's record terms (surface, lane, wrapper, handoff, evidence boundary, not_observed) stay in records and tool calls, never in the sentence the user reads unless they ask about one; and when a stop condition or a decision the user owns ends the turn, offer the next action as a question rather than declaring what will not be done.
  • Report the tool's status, ask_id, served model, and cost source; a non-answer is reported as its status and is never an answer.
  • Record observed delegation results; use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.

Read the full file on GitHub · 46 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago Changed · +3 lines c6f20e55034a
  2. 16d ago Changed b5c11c9d4a97
  3. 20d ago Changed · +1 tokens per session 76b59cf48f2c
  4. 21d ago Changed · +11 tokens per session 469b19ffe999
  5. 23d ago First seen · 43 lines · 60 tokens per session scan A 144c47792736

Subscribe to this mod's changes

omh-jev-ask is a skill published in the GitHub repository rlaope/oh-my-hermes (3,392 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 691 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-24.

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