Faerie Fire

Community

Hmbown

faerie-fire

Overview

Publisher	Hmbown
Repository	`Wizards-of-the-Ghosts`
Skill name	`faerie-fire`
Stars	106
Forks	10
Bundled files	Instructions only
License	CC0-1.0
Links	Skill source Repository

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 Hmbown on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Hmbown/Wizards-of-the-Ghosts/tree/main/generated/hermes/investigation-and-preparation/faerie-fire

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/Hmbown/Wizards-of-the-Ghosts.git /tmp/Wizards-of-the-Ghosts
mkdir -p .claude/skills
cp -r /tmp/Wizards-of-the-Ghosts/generated/hermes/investigation-and-preparation/faerie-fire .claude/skills/faerie-fire

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Faerie Fire 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 Faerie Fire 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 Faerie Fire 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.

Faerie Fire

Make hidden things visible by highlighting, tagging, and marking them for attention.

What This Skill Does

Faerie Fire marks things that are already known. It does not search, discover, explain, translate, or fix. The user has already identified what matters; your job is to make those items impossible to overlook by annotating, tagging, highlighting, or visually surfacing them in context. In this grimoire, Faerie Fire is treated as a metaphorical spell with a shipping-now delivery profile. Canonical reference input: Faerie Fire (spell).

When To Use

"Highlight", "tag", "mark", "annotate", "call out", "flag" applied to specific items the user has already named or located
"Make X visible" where X is a known set of findings, clauses, functions, tickets, or features
"Show me where [specific thing] appears" — location surfacing, not discovery
"Annotate", "add margin notes", "color-code", "produce a summary table of marked items"
The user provides the target list and asks you to apply markers to a document, codebase, dataset, or diagram

Prerequisites

No extra runtime dependencies beyond Hermes Agent and the normal toolset for this session.

Procedure

Restate the target, the success condition, and any no-touch boundaries before taking action.
Confirm the target set: Restate what the user wants marked. If the list is implicit, extract it explicitly before annotating.
Choose the marking strategy based on the medium:
Code: inline comments, // HIGHLIGHT: markers, or extracted function lists with file:line references
Documents: bold/underline, margin notes, or a findings table with clause references
Data/tables: tagged rows, conditional formatting descriptions, or filtered views
Diagrams: callout labels, numbered annotations, or a legend mapping marks to gaps
Apply markers with context: Every mark must include why the item was flagged, not just that it was flagged. A marker without rationale is noise.
Deliver two artifacts: the annotated source and a concise summary listing what was marked and the selection criteria.
Package the result as the deliverables below, with confidence, assumptions, and unresolved risk called out explicitly.

Deliverables

An annotated version of the source material with key findings highlighted and marked.
A summary of what was highlighted and why each item warrants attention.

Pitfalls / Guardrails

Keep the metaphor anchored to a real mechanism instead of drifting into lore.
Be selective. Highlighting everything is highlighting nothing. If the user gives you 200 items, ask them to narrow or apply a ranking.
Never claim to have discovered something you were not asked to mark. Faerie Fire illuminates; it does not hunt.
If the request mixes marking with fixing, translating, or explaining, scope yourself to marking only and note the boundary.
Do not use for: Scanning/searching: "Find all hidden webhooks", "Scan for MCP servers" — the user is asking you to discover, not mark. Use a detection spell instead.
Do not use for: Explaining: "Explain what this manifest does", "What does this code do?" — comprehension, not annotation.
Do not use for: Translating: "Translate from German to English" — language conversion, not highlighting.
Do not use for: Rewriting: "Rewrite for executives", "Simplify this report" — transformation, not marking.
Do not use for: Fixing: "Highlight the risky parts and fix them" — Faerie Fire only marks; it does not remediate. Decline the fix portion or route it to a separate spell.
Do not use for: Vague requests: "Highlight the important stuff" with no criteria — ask the user what "important" means before proceeding.

Verification

Check that the result includes every deliverable promised above.
Check that confirmed facts, assumptions, and inferences are visibly separated.
Check that the metaphor still maps cleanly to a real operational mechanism.

Example Invocation

text
/faerie-fire Use \$faerie-fire to highlight the most important [findings/patterns/elements] in this [document/codebase/dataset] so they cannot be overlooked

Frequently asked questions

What does the Faerie Fire AI skill do?

Why use Faerie Fire on TypingMind?

Because you install it once and use it with any model. Faerie Fire 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 Faerie Fire in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Hmbown/Wizards-of-the-Ghosts/tree/main/generated/hermes/investigation-and-preparation/faerie-fire. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Faerie Fire?

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 Faerie Fire?

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

Is the Faerie Fire AI skill free?

Yes. It is published on GitHub by Hmbown under the CC0-1.0 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Faerie Fire

What This Skill Does

When To Use

Prerequisites

Procedure

Deliverables

Pitfalls / Guardrails

Verification

Example Invocation

Frequently asked questions

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