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Omh Skill Health

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rlaope
omh-skill-health

[omh] OMH skill portfolio health overview: prepare a metadata-only OMH skill portfolio dashboard with stale surfaces, observed failure signals, pending amendments, and top actions. Use when the user says: skill-health, skill health, skill portfolio health, skill dashboard, skill health dashboard, skill failure pattern dashboard, skill failure patterns, pending skill amendments.

Overview

Publisherrlaope
Repositoryoh-my-hermes
Skill nameomh-skill-health
Stars
3.6K
Forks
269
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 Skill Health 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.
    https://github.com/rlaope/oh-my-hermes/tree/main/agent-skills/omh-skill-health
  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-skill-health .claude/skills/omh-skill-health
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Omh Skill Health 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 Skill Health 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 Skill Health 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.

Skill Health

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

Why This Exists

skill-health exists because a skill portfolio drifts in ways no single run shows -- a managed skill changed in place, an authoring finding nobody fixed, an update waiting on its hub -- and use counts measure none of that: it gathers the observed signals into one card with an owner lane and a safe next action for each, and changes nothing itself.

Do Not Use When

  • OMH setup, install, or a skill that does not load.
  • One run that missed a route or went wrong.
  • Finding a new skill to adopt; use omh-skill-scout.

Examples

Good example:

  • Prompt: skill-health show the OMH skill portfolio dashboard with stale surfaces, failure patterns, pending amendments, and top improvement actions.
  • Expected behavior: Produce prepare_skill_health 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: skill-health claim every skill is working and patch the failures automatically without observed signals or review.
  • 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

  • Dashboard scope, source surfaces, stale/duplicate criteria, and stop condition are explicit.
  • Install/setup health, catalog operations, and failure retrospectives stay out of the health card.
  • No skill, prompt, doc, memory, or model behavior is claimed changed until a reviewed implementation records evidence.
  • Never present use, view, or load counts, .usage.json included, as a health, prune, archive, or retire signal: a rarely used skill is not an unhealthy one, and no health card recommends removing, archiving, or pruning a skill for being used little.
  • On Hermes, read the skill audit ledger read-only (that skill's entries in skills/.curator_ledger.jsonl under the active profile's Hermes home, or hermes curator ledger --skill <name> --limit <n>, which lists only the 20 newest entries by default): an entry against an OMH-managed skill means Hermes changed that managed copy outside OMH, so it may no longer match its generated body; report it as drift with the entry's action and actor (agent, user, or curator, which covers Hermes' curator and its background review). 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. An empty ledger is unknown, not clean, because skills.ledger: false turns it off.
  • On Hermes, record an authoring finding only from the lint_warnings a skill_manage write returned, which are advisory and never proof a skill works; only some writes return them (an edit never does), so a write without them is not a clean lint. Record an available update for a hub-installed skill only from hermes skills check output that was seen; that hub request is Hermes' own, not OMH's.

Recovery Notes

  • If the request is about OMH setup, install, stale package paths, or command availability, it is outside this skill.
  • If the request is a missed-route or self-improvement trace, it is outside this skill.

When to Use

Use when operators need portfolio-level skill health without treating it as install repair, live execution success, or automatic skill mutation.

Strong routing signals: `skill-health`, `skill health`, `skill portfolio health`, `skill dashboard`, `skill health dashboard`, `skill failure pattern dashboard`, `skill failure patterns`, `pending skill amendments`, `skill amendments`, `스킬 헬스`, `스킬 상태`, `스킬 대시보드`, `스킬 실패 패턴`, `스킬 개선 후보`, `스킬 보류 수정`

Catalog Metadata

Category: operations Phase: skill-health Quality tier: workflow-surface-gated Reasoning demand: light

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:

  • catalog, generated, reference, harness, and capability-surface status
  • observed failure signals, or an explicit statement that none were supplied
  • pending amendment review slots and top safe actions with owner lane and verification path

Artifact expectations:

  • skill_health_card/v1 metadata-only wrapper card recording surface status, observed-only failure signals, pending amendments, and the non-mutation boundary

Safety rules:

  • A skill health dashboard is not install/setup health, live skill execution success, automatic skill mutation, model training, verification, review, CI, or proof that future routing is fixed.
  • 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. Record actual tool results, or not_observed / not_available, in the record; 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. Reply in the user's own words and the host's own voice: the host's 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 real unresolved user decision or a useful briefing discussion remains, offer one specific, content-linked question. Completed work needs no question; omit unrelated non-action footers and generic offers to continue. 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 Skill Health AI skill do?

[omh] OMH skill portfolio health overview: prepare a metadata-only OMH skill portfolio dashboard with stale surfaces, observed failure signals, pending amendments, and top actions. Use when the user says: skill-health, skill health, skill portfolio health, skill dashboard, skill health dashboard, skill failure pattern dashboard, skill failure patterns, pending skill amendments.

Why use Omh Skill Health on TypingMind?

Because you install it once and use it with any model. Omh Skill Health 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 Skill Health in TypingMind?

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

Which AI models can use Omh Skill Health?

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 Skill Health?

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

Is the Omh Skill Health 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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