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Skill Release Gate

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rohitg00
skill-release-gate

Evaluate an Agent Skill bundle for structural integrity, trigger quality, artifact improvement, script correctness, safety, installed-tree integrity, and target-host portability before release.

Overview

Publisherrohitg00
Repositoryai-engineering-from-scratch
Skill nameskill-release-gate
Stars
54.9K
Forks
9.6K
Bundled files
7
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.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by rohitg00 on GitHub. Read the source before you install it.

Installation

Install the Skill Release Gate 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/rohitg00/ai-engineering-from-scratch.git /tmp/ai-engineering-from-scratch
mkdir -p .claude/skills
cp -r /tmp/ai-engineering-from-scratch/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate .claude/skills/skill-release-gate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Release Gate 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 Skill Release Gate 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 Skill Release Gate 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 release gate

Use this skill before publishing or distributing an Agent Skill directory bundle.

Workflow

  1. Resolve SKILL_ROOT to the absolute directory containing this installed SKILL.md. Do not assume the process cwd is the installed bundle.
  2. Resolve TARGET_ROOT from the original workspace working directory and resolve the user-supplied candidate as an absolute TARGET_BUNDLE.
  3. Read references/eval-contract.md from SKILL_ROOT.
  4. Inspect the positive and near-miss trigger cases in evals/cases.json under TARGET_BUNDLE.
  5. Inspect the shared baseline and with-skill assertions in evals/artifacts.json under TARGET_BUNDLE.
  6. Inspect the explicit script and safety results in evals/evidence.json under TARGET_BUNDLE.
  7. Inspect the declared runtime capabilities in assets/hosts.json under TARGET_BUNDLE and verify the target file hashes against its assets/manifest.json.
  8. For production, replace deterministic predictions, artifacts, evidence, and host capabilities with captured results; set all four captured modes; and bind every raw trigger observation, both artifacts, the complete evidence set, and the non-empty host matrix to non-empty sources and matching SHA-256 provenance digests. These local checks can set localEvidenceReady, but locally recomputable hashes do not prove capture.
  9. Obtain an external JSON attestation whose evidenceRoot matches the report, plus the SHA-256 of its exact bytes from a separate trusted policy or release channel. The attestation must be a regular file outside the target bundle.
  10. Before execution, show the exact resolved argv. The installed evaluator is scripts/evaluate_skill.py under SKILL_ROOT. For the shipped lesson fixture, build argv from python3, that absolute evaluator path, --fixture-demo, and the absolute TARGET_BUNDLE. For production, use the same installed script with --attestation, --trusted-attestation-sha256, and the absolute TARGET_BUNDLE, without --fixture-demo.
  11. Return checksPassed, fixturePassed, localEvidenceReady, trustAnchorValid, productionReady, and passed with the evidence root, evaluation modes, failed checks, precision, recall, every raw trigger observation, per-case repeated-run rates, artifact comparison, script and safety evidence, installed-tree verification, and portability matrix. Include the resolved script path, resolved target path, cwd, exact argv, and exit code. Mark unavailable observations unverified.

Output contract

Return the complete JSON evaluation report. Preserve every layer-specific check and its evidence so a passing aggregate cannot hide a routing, artifact, script, safety, installed-tree, or portability failure. fixturePassed reports a successful teaching fixture. localEvidenceReady reports only local digest integrity. passed is true only when productionReady also has a valid out-of-bundle trust anchor.

Failure behavior

If configuration is invalid, provenance is absent or mismatched, the trusted attestation is missing or invalid, a file hash differs, a required capability is absent, or any production gate fails, stop with a nonzero result and report the failed layer. The explicit --fixture-demo path may exit successfully only when fixturePassed is true, and it never makes a release claim. Never publish, install elsewhere, repair evidence, create the trust decision, or weaken a threshold automatically.

Do not publish a bundle merely because SKILL.md parses or one positive prompt activates. Do not label a package portable when a target drops required companion files or ignores required runtime extensions.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Skill Release Gate AI skill do?

Evaluate an Agent Skill bundle for structural integrity, trigger quality, artifact improvement, script correctness, safety, installed-tree integrity, and target-host portability before release.

Why use Skill Release Gate on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohitg00/ai-engineering-from-scratch/tree/main/phases/13-tools-and-protocols/27-skill-evals-packaging-and-portability/outputs/skill-release-gate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Skill Release Gate?

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 Skill Release Gate?

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

Is the Skill Release Gate AI skill free?

Yes. It is published on GitHub by rohitg00 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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