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Omh Instinct Ledger

CommunityPopular
rlaope
omh-instinct-ledger

[omh] Instinct Ledger workflow: turn repeated project or cross-project lessons into atomic, confidence-scored instinct candidates with scoped promotion and export boundaries. Use when the user says: instinct-ledger, instinct ledger, project instincts, project-scoped instincts, project scoped instincts, global instincts, instinct review, instinct candidate.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-instinct-ledger
Stars
2.7K
Forks
194
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by rlaope on GitHub. Read the source before you install it.

Installation

Install the Omh Instinct Ledger AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rlaope/oh-my-hermes.git /tmp/oh-my-hermes
mkdir -p .claude/skills
cp -r /tmp/oh-my-hermes/agent-skills/omh-instinct-ledger .claude/skills/omh-instinct-ledger
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Instinct Ledger in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Omh Instinct Ledger on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Omh Instinct Ledger is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Instinct Ledger

This is an OMH instinct-ledger workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).

Why This Exists

instinct-ledger exists so Hermes users can ask for this workflow in chat and receive a structured, evidence-bounded OMH operating surface instead of ad hoc narration.

Do Not Use When

  • The request is already handled by a narrower explicit skill with stronger evidence.
  • The user asks OMH to secretly run external platforms, connectors, schedulers, file exports, or runtime agents.
  • The only safe answer is to ask for missing authority, credentials, target, or observed evidence first.

Examples

Good example:

  • Prompt: instinct-ledger turn these repeated OMH review lessons into project-scoped instincts and show which ones could be promoted globally.
  • Expected behavior: Produce prepare_instinct_ledger with required context, wrapper actions, and not-evidence boundaries.
  • Why: The prompt names a real workflow surface that Hermes can orchestrate without hiding execution.

Bad example:

  • Prompt: instinct-ledger silently install hooks, learn from every prompt, and mutate all skills globally.
  • Expected behavior: Report the missing observed evidence or authority instead of claiming the external step happened.
  • Why: Prepared OMH guidance is not platform, runtime, connector, file, memory, or delivery evidence.

Completion Checklist

  • Each instinct is atomic: one trigger, one action, one scope, confidence, evidence refs, and review state.
  • Project-specific conventions, global practices, project/global promotion candidates, imports, and exports are separated.
  • No hooks, memory writes, skill edits, global promotion, import/export, or behavior-change claims are made without observed approval and implementation evidence.

Recovery Notes

  • If the request is a single missed route or run trace, route to workflow-learning first.
  • If the request is to mutate durable rules, prompts, skills, or AGENTS guidance, route to rules-distill or implementation after review approval.
  • If evidence comes from a stuck run, use agent-debug before converting lessons into instincts.

Use When

Use when Hermes should review repeated observations, user corrections, workflow lessons, or failure patterns as atomic project-scoped or global instinct candidates with confidence, evidence, promotion, import, or export decisions.

Strong routing signals: `instinct-ledger`, `instinct ledger`, `project instincts`, `project-scoped instincts`, `project scoped instincts`, `global instincts`, `instinct review`, `instinct candidate`, `instinct candidates`, `instinct promotion`, `promote instinct`, `promote learning`, `confidence scored learning`, `confidence-scored learning`, `project learning patterns`, `cross-project learning`, `export instincts`, `import instincts`, `학습 본능`, `프로젝트별 학습`, `프로젝트 스코프 학습`, `전역 학습 승격`, `학습 승격`, `학습 패턴 승격`

Catalog Metadata

Category: optimization Phase: instinct-ledger Quality tier: workflow-surface-gated Reasoning demand: heavy

Quality bar:

  • Name the user-facing workflow objective, required context, next action, and stop condition.
  • Separate prepared guidance from observed platform, runtime, connector, file, memory, or delivery evidence.
  • Expose missing tools, credentials, targets, or observations as user-visible gaps.

Required inputs:

  • user request
  • target context
  • delivery or status expectation
  • known missing evidence

Expected outputs:

  • instinct_ledger_plan/v1
  • instinct_candidate/v1
  • project_instinct_scope_map/v1
  • instinct_promotion_review/v1
  • instinct_export_review/v1 when requested

Artifact expectations:

  • instinct_candidate/v1 with trigger, action, confidence, domain, scope, source evidence, non-goals, and review state
  • project_instinct_scope_map/v1 separating project, global, imported, and promotion-candidate instincts
  • instinct_promotion_review/v1 with repeated evidence, confidence threshold, conflicts, and approval state
  • instinct_export_review/v1 with redaction, destination, import/export trust gaps, and raw-observation exclusion when requested

Safety rules:

  • An instinct ledger is not hook installation, automatic observation, model training, hidden memory mutation, skill mutation, prompt mutation, global rule promotion, import, export, or proof that future behavior changed. Record only reviewed candidate instincts, confidence, scope, promotion state, and evidence gaps.
  • Do not claim connector, gateway, runtime, file generation, memory mutation, or host automation evidence from prepared guidance.

Runtime Evidence

Use the current host's own tools and subagent/task mechanism when available; otherwise run the same lanes sequentially or name the unavailable capability. A prepared plan, handoff, checklist, or skill installation is not execution, review, CI, merge-readiness, or merge evidence. Report actual tool results or not_observed / not_available; never invent dispatch or host accounting. Treat supplied context as advisory, not proof of hidden memory reads or writes. State scope, constraints, verification, and the stop condition before work. Supporting paths are relative to this skill directory; sibling skill paths are relative to its parent. Resolve them from the host-provided skill base directory ({baseDir} on hosts that provide it), never a hardcoded install location. A named workflow not installed here is unavailable, not permission to emulate its host-specific capabilities. Verify through the real surface before done.

Frequently asked questions

What does the Omh Instinct Ledger AI skill do?

[omh] Instinct Ledger workflow: turn repeated project or cross-project lessons into atomic, confidence-scored instinct candidates with scoped promotion and export boundaries. Use when the user says: instinct-ledger, instinct ledger, project instincts, project-scoped instincts, project scoped instincts, global instincts, instinct review, instinct candidate.

Why use Omh Instinct Ledger on TypingMind?

Because you install it once and use it with any model. Omh Instinct Ledger is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Omh Instinct Ledger in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-instinct-ledger. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Omh Instinct Ledger?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Omh Instinct Ledger?

As many as you like. As long as a model supports skills, you can use Omh Instinct Ledger with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Omh Instinct Ledger AI skill free?

Yes. It is published on GitHub by rlaope under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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