model-onboarding
Onboard a new model generation or sibling into oh-my-hermes: probe router recognition,…
[omh] Turn repeated lessons into written rules: extract repeated principles from skills, prompts, traces, reviews, and failures into reviewed rule candidates without auto-mutating guidance. Use when the user says: rules-distill, rules distill, distill rules, rule distillation,
$ npx -y skills add rlaope/oh-my-hermes --skill omh-rules-distill --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/omh-rules-distillContext preview
The summary Claude sees to decide when to auto-load this skill.
[omh] Turn repeated lessons into written rules: extract repeated principles from skills, prompts, traces, reviews, and failures into reviewed rule candidates without auto-mutating guidance. Use when the user says: rules-distill, rules distill, distill rules, rule distillation,
name: "omh-rules-distill"
description: "[omh] Turn repeated lessons into written rules: extract repeated principles from skills, prompts, traces, reviews, and failures into reviewed rule candidates without auto-mutating guidance. Use when the user says: rules-distill, rules distill, distill rules, rule distillation, principle distill, skill principles, extract agent rules, turn traces into rules."
metadata:
hermes:
tags: [workflow, oh-my-hermes, knowledge]
category: knowledge
phase: rules-distillation
role: memory-keeper
quality_tier: rules-distillation-gatedThis is a Hermes-native `rules-distill` workflow skill.
`rules-distill` gives OMH a disciplined way to learn from large skill ecosystems like ECC without wholesale copying: extract principles, review them, then patch OMH only through explicit verified work.
Good example:
Bad example:
Use when Hermes should turn repeated workflow lessons, skill behavior, review comments, or failure traces into candidate rules that humans can review before docs or catalog changes.
Strong routing signals: `rules-distill`, `rules distill`, `distill rules`, `rule distillation`, `principle distill`, `skill principles`, `extract agent rules`, `turn traces into rules`, `policy distill`, `guidance distill`, `규칙 증류`, `원칙 추출`, `스킬 원칙`, `프롬프트 규칙`
Category: `knowledge` Phase: `rules-distillation` Hermes role: `memory-keeper` Quality tier: `rules-distillation-gated` Reasoning demand: `light`
Quality bar:
Handoff policy:
Keep principle extraction and candidate review in Hermes. Editing AGENTS.md, catalog data, prompts, skills, or docs requires explicit approved implementation work and verification.
Required inputs:
Expected outputs:
Artifact expectations:
Safety rules:
Preferred harness for this skill: `rules-distill`.
omh runtime record --skill rules-distill --harness rules-distill --status started
Record observed delegation results; otherwise return `not_available` or `not_observed`. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence.
Preserve workflow intent and stop conditions; verify 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 (surfa
English | 한국어 | 日本語 | 中文 Install once. Keep Hermes. Add a stronger operating layer. Planning, research, creation, coding handoffs, operations, and project memory with explicit evidence boundaries.
Repo: rlaope/oh-my-hermes
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