Artifact Yylo logo

Artifact Yylo

Organization
agent-skills-hub
artifact-yylo

Capture and retrieve durable YYLO Ledger artifact Records with intentional profiles, payload modes, provenance, retention, and secret-safe immutable evidence.

Overview

Publisheragent-skills-hub
Repositoryagent-skills-hub
Skill nameartifact-yylo
Stars
101
Forks
35
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 agent-skills-hub on GitHub. Read the source before you install it.

Installation

Install the Artifact Yylo 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/agent-skills-hub/agent-skills-hub.git /tmp/agent-skills-hub
mkdir -p .claude/skills
cp -r /tmp/agent-skills-hub/skills/artifact-yylo .claude/skills/artifact-yylo
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Artifact Yylo 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 Artifact Yylo 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 Artifact Yylo 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.

Use YYLO artifact Records

Overview

Durable evidence — reports, receipts, model output, bounded process output — is captured as immutable YYLO Ledger artifact Records with explicit profile, payload mode, provenance, and retention.

When to Use This Skill

  • Use when a user asks to capture, store, or retrieve run evidence or generated reports in a YYLO project.
  • Use when later verification depends on exact bytes (choose an immutable payload mode).
  • Do not treat an artifact Record as a release artifact or as authority to publish or deploy.

Treat Ledger as the source of truth for artifact identity and metadata. Use yy ledger in a YYLO controller or yylo-ledger standalone. Inspect COMMAND artifact --help; if unavailable, do not create store files manually.

Classify before capture

Choose the profile matching the evidence:

  • stdout: bounded process output;
  • model-output: an agent/model response;
  • report: a generated human- or machine-readable result;
  • receipt: evidence binding an operation and its inputs/outcome.

Choose payload mode deliberately:

  • inline: small immutable bytes embedded in the Record;
  • local: immutable content-addressed bytes in Ledger storage;
  • external: immutable external bytes with URI, digest, and size;
  • link: URI reference without an immutable-byte guarantee.

Prefer immutable evidence when later verification depends on exact bytes. A link must never be presented as content-addressed proof.

Create explicitly

Use file/stdin transport and provide the media type:

bash
yy ledger artifact create --title "Focused test report" --profile report \
  --mode local --media-type application/json --file report.json

For external immutable content, provide the supported URI, SHA-256 digest, and size shown by installed help. Never embed URI credentials. Ledger rejects unsafe schemes, traversal, size/digest mismatches, oversized capture, and known secret patterns.

Attach only supported, non-secret provenance such as actor, agent, model, session, run, invocation, task, or workflow identity. Task/workflow provenance uses immutable Record IDs. Select temporary, standard, or permanent retention deliberately; retention metadata does not itself authorize deletion.

Find and verify

bash
yy ledger artifact search --profile report --projection summary --limit 20 -f json
yy ledger artifact get RECORD_ID -f json
yy ledger artifact history RECORD_ID -f ndjson

Use bounded metadata/summary projections before requesting payload details. Verify profile, mode, media type, digest, size, provenance, retention, revision, and immutable ID before relying on evidence.

Artifact payloads are immutable evidence. Represent replacement with explicit predecessor/successor relationships and the installed revision-safe update contract; do not overwrite bytes or edit content objects. Archive is a lifecycle transition, not deletion. Release, publication, external upload, retention execution, and production mutation always require separate authority.

Frequently asked questions

What does the Artifact Yylo AI skill do?

Capture and retrieve durable YYLO Ledger artifact Records with intentional profiles, payload modes, provenance, retention, and secret-safe immutable evidence.

Why use Artifact Yylo on TypingMind?

Because you install it once and use it with any model. Artifact Yylo 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 Artifact Yylo in TypingMind?

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

Which AI models can use Artifact Yylo?

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 Artifact Yylo?

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

Is the Artifact Yylo AI skill free?

Yes. It is published on GitHub by agent-skills-hub 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇