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Hermes Skill

Community
AlexAI-MCP
hermes-skill

Create, improve, inventory, and audit Claude Code skills. Use when turning a solved workflow into a reusable skill, expanding an existing skill, checking trigger quality, or standardizing a skill pack.

Overview

PublisherAlexAI-MCP
Repositoryhermes-CCC
Skill namehermes-skill
Stars
134
Forks
22
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 AlexAI-MCP on GitHub. Read the source before you install it.

Installation

Install the Hermes Skill 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/AlexAI-MCP/hermes-CCC/tree/master/skills/hermes-skill
  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/AlexAI-MCP/hermes-CCC.git /tmp/hermes-CCC
mkdir -p .claude/skills
cp -r /tmp/hermes-CCC/skills/hermes-skill .claude/skills/hermes-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hermes Skill 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 Hermes Skill 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 Hermes Skill 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.

Hermes Skill

Purpose

  • Convert repeated workflows into reusable Claude Code skills.
  • Keep skills operational rather than descriptive.
  • Improve trigger quality so the right skill activates at the right time.
  • Audit skill packs for overlap, drift, and incomplete instructions.
  • Preserve working patterns after a successful task.

Required Skill Anatomy

  • one folder per skill
  • one SKILL.md file per folder
  • YAML frontmatter at the top
  • Markdown instructions below the frontmatter
  • commands, outputs, and failure handling in the body

Frontmatter Schema For This Package

  • name
  • description
  • version
  • author
  • license
  • metadata

Description Rules

  • State what the skill does.
  • State when to use it.
  • Mention trigger contexts directly.
  • Avoid vague phrasing such as "general helper".
  • Include important boundaries when the skill is domain-specific.

Naming Rules

  • use lowercase letters, digits, and hyphens only
  • keep names short and concrete
  • prefer operational nouns or verb-noun pairs
  • avoid project-specific private jargon unless the package is private
  • do not rename a stable public skill casually

Create Workflow

  1. Identify a repeated workflow that was just solved.
  2. Extract the reusable steps, not the chat narrative.
  3. List the exact tools, commands, and files involved.
  4. Identify preconditions and failure modes.
  5. Write the frontmatter with strong trigger language.
  6. Write the body as an operator playbook.
  7. Include output contracts where consistency matters.
  8. Include examples only when they sharpen execution.

Improve Workflow

  1. Read the full skill.
  2. Ask what failed or felt ambiguous in actual usage.
  3. Tighten the description if triggering was weak.
  4. Add missing commands or environment assumptions.
  5. Add decision rules where the old version left too much ambiguity.
  6. Add failure handling if the skill assumed a happy path.
  7. Remove stale instructions and dead commands.

Audit Dimensions

  • trigger clarity
  • instruction quality
  • command accuracy
  • line-count sufficiency
  • duplication with nearby skills
  • presence of decision rules
  • presence of output contracts
  • presence of verification steps

What Makes A Good Skill

  • It reduces repeated thinking.
  • It includes exact actions for non-obvious steps.
  • It names the right tools and commands.
  • It narrows ambiguity without overfitting one repo.
  • It handles the common failure path.
  • It is faster to use than rediscovering the workflow.

What Makes A Bad Skill

  • It repeats generic advice the base model already knows.
  • It has weak frontmatter and never triggers.
  • It explains philosophy but omits execution.
  • It contains stale paths or commands.
  • It is so narrow that it only matches one past task.
  • It has no failure modes or verification guidance.

Skill Extraction Questions

  • What exact problem was solved?
  • What sequence of actions worked?
  • What tools or connectors were essential?
  • What surprised us during execution?
  • What constraints would another agent need to know up front?
  • What output structure made the result useful?

Standard Sections To Include

  • purpose
  • activation signals
  • inputs
  • preflight
  • step-by-step procedure
  • decision rules
  • output contract
  • failure modes
  • examples
  • checklist

Inventory Workflow

  1. List all skill folders.
  2. Verify that each folder contains SKILL.md.
  3. Read frontmatter fields.
  4. Produce a compact table of name, description, and health.
  5. Flag missing or malformed skills.

Overlap Rules

  • Two skills may overlap in domain but should differ in operating goal.
  • Merge skills if their triggers, commands, and outputs are nearly identical.
  • Keep separate skills if one is strategic and the other is procedural.
  • Prefer smaller focused skills over one giant omnibus skill.

Updating From Real Usage

  • Capture friction immediately after using a skill.
  • Update the skill while the failure mode is fresh.
  • Preserve examples that encode real mistakes.
  • Replace speculative guidance with validated instructions.

Example Improvement Targets

  • add missing prereq checks
  • tighten "when to use" language
  • replace obsolete CLI flags
  • add a markdown response template
  • split one overloaded skill into two

Audit Output Template

markdown
Skill audit report:
- systematic-debugging: Healthy - clear phases, explicit outputs, and verification loop
- old-review-skill: Outdated - stale GitHub CLI commands and no failure handling
- duplicate-debug-skill: Redundant - overlaps heavily with systematic-debugging

Creation Output Template

markdown
Created skill: my-new-skill
Path: ~/.claude/skills/my-new-skill/SKILL.md
Why it should trigger: handles repeated workflow for ...
Key sections: purpose, procedure, failure modes, output contract

Decision Rules

  • Create a new skill only when the workflow is truly repeatable.
  • Improve an existing skill when the use case matches its current mission.
  • Split a skill when one body now serves multiple unrelated triggers.
  • Keep package-wide conventions consistent across all skills.

Failure Modes

  • encoding one conversation instead of the general workflow
  • omitting commands because they felt obvious during the original task
  • bloating a skill with reference material that belongs elsewhere
  • letting frontmatter drift away from actual body content
  • failing to update package docs after adding or removing skills

Recovery Moves

  • If the skill reads like a postmortem, rewrite it as instructions.
  • If the skill is too abstract, add commands and examples.
  • If the skill is too long but still coherent, split by purpose not by arbitrary size.
  • If the trigger is too weak, rewrite the description before changing anything else.

Good Triggers

  • "turn this workflow into a skill"
  • "improve this skill"
  • "audit our skill pack"
  • "list installed skills"
  • "this keeps repeating, save it"

Checklist

  1. Confirm the workflow is reusable.
  2. Choose the right skill name.
  3. Write strong frontmatter.
  4. Add exact commands and decision rules.
  5. Add failure handling and verification.
  6. Check for overlap with existing skills.
  7. Update package docs if necessary.
  8. Validate structure before shipping.

Frequently asked questions

What does the Hermes Skill AI skill do?

Create, improve, inventory, and audit Claude Code skills. Use when turning a solved workflow into a reusable skill, expanding an existing skill, checking trigger quality, or standardizing a skill pack.

Why use Hermes Skill on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AlexAI-MCP/hermes-CCC/tree/master/skills/hermes-skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hermes Skill?

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 Hermes Skill?

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

Is the Hermes Skill AI skill free?

Yes. It is published on GitHub by AlexAI-MCP 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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