Rules Distill

This is a Hermes-native rules-distill workflow skill.

Why This Exists

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.

Do Not Use When

• The user wants a single workflow route regression; use omh-workflow-learning.
• The user wants durable factual project memory; use omh-wiki or memory curation.
• The user already approved a concrete code/doc change; use the implementation workflow.
• The ask is writing or keeping current the file an agent reads at startup -- AGENTS.md, CLAUDE.md, a Cursor rule; use omh-agent-instructions, which updates only its marked region.

Examples

Good example:

• Prompt: rules-distill 최근 실패 trace와 스킬들을 보고 OMH AGENTS에 넣을 만한 반복 원칙 후보만 뽑아줘.
• Expected behavior: Prepare principle_candidate_set/v1, duplication/conflict report, review queue, and approved patch handoff only after approval.
• Why: The request is meta-guidance learning and needs review before mutating rules.

Bad example:

• Prompt: rules-distill 한 번 본 실패를 바로 모든 스킬 규칙으로 써버려.
• Expected behavior: Keep it as a low-confidence candidate or regression case until repeated evidence and review approval exist.
• Why: Rule distillation should not turn one-off anecdotes into global behavior.

Completion Checklist

• The durable fact, source evidence, retrieval hint, and staleness risk are recorded.
• Uncertain or conflicting knowledge is marked as review-needed rather than permanent truth.
• Separate coding or docs tasks are extracted instead of buried in notes.

Recovery Notes

• If source evidence conflicts, route to memory or knowledge review before writing durable guidance.
• If the fact may be stale, record the staleness warning and next refresh action.

Workflow Lane

• Current lane: Automation and status (achievements, workspace-audit, production-audit, live-incident-response, automation-blueprint, github-event-ops, github-issue-intake, buzz, +40 more) - schedules, status, health, and ops review.
• If intent belongs to another lane, hand back to oh-my-hermes or name the adjacent workflow.
• Shared product, routing, compatibility, and evidence rules: skill_view(name='omh-routing', file_path='references/skill-common-rail.md').

When to Use

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`

Catalog Metadata

Category: knowledge Phase: rules-distillation Hermes role: memory-keeper Quality tier: rules-distillation-gated Reasoning demand: light

Quality bar:

• Collect repeated evidence before proposing a rule.
• Deduplicate against existing guidance and name conflicts or narrower scopes.
• Use imperative, testable wording and include non-goals for each candidate.
• Require review approval before any patch handoff or generated-skill update.
• On Hermes, read a curator run report (logs/curator/<run>/REPORT.md and run.json under the active profile's Hermes home) as a source like a review or a trace: it records which skills the curator consolidated, archived, or created in that run, and one report is one observation, never repeated evidence by itself.

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:

• source corpus: skills, prompts, traces, reviews, failures, or docs
• destination boundary: AGENTS, skill catalog, prompt, docs, memory, or no-write review
• rule granularity and acceptance criteria
• reviewer or approval requirement

Expected outputs:

• rules_distillation_plan/v1
• principle_candidate_set/v1
• duplication_conflict_report/v1
• review_queue/v1
• approved_patch_handoff/v1 when approved
• not-evidence boundary

Artifact expectations:

• principle_candidate_set/v1 with source references, repeated pattern, candidate wording, scope, non-goals, and risk
• duplication_conflict_report/v1 with already-covered rules, conflicts, and stale guidance
• review_queue/v1 separating proposed, approved, rejected, deferred, and needs-evidence candidates

Safety rules:

• Do not silently mutate skills, prompts, AGENTS.md, docs, memory, or catalog data from a distillation result.
• Do not promote one-off preferences, weak anecdotes, or stale traces into global rules.
• Keep observed sources, inferred principles, candidate wording, review state, and implementation patches separate.
• On Hermes, when the destination is the user's own Hermes skills, an approved candidate lands through skill_manage: report it landed only from a result that succeeded without staged: true, with the matching skill audit ledger entry as its record while the ledger is on, and report a staged write as waiting in /skills pending for the person's own /skills approve <id> under their skills.write_approval setting. OMH-managed skills are generated from OMH's catalog and are never the destination; a lesson about one goes to omh-workflow-learning. An OMH-managed skill is one OMH installed, under a label OMH's catalog renders such as omh-plan or ulw-work; a companion skill the person or an agent created is theirs, whatever its name.

Runtime Evidence

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.

• Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. 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 (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.

Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.

Shared product, compatibility, topology, memory, harness, and execution rules: skill_view(name='omh-routing', file_path='references/skill-common-rail.md'). Load it when applicable; otherwise name an unavailable capability.