Verify Release logo

Verify Release

Organization
Parcha-ai
verify-release

Verify a specific release in its target environment, follow an in-progress rollout, and resume agreed checks when it is ready. Use for “I deployed it, verify”, “monitor the deployment and continue QA”, or “is this release working in staging/production?”. Discovers the stack and uses live evidence. Not a deployment tool or a full QA campaign by default.

Overview

PublisherParcha-ai
Repositoryparcha-skills
Skill nameverify-release
Stars
65
Forks
5
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by Parcha-ai on GitHub. Read the source before you install it.

Installation

Install the Verify Release 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/Parcha-ai/parcha-skills/tree/main/verify-release/skills/verify-release
  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/Parcha-ai/parcha-skills.git /tmp/parcha-skills
mkdir -p .claude/skills
cp -r /tmp/parcha-skills/verify-release/skills/verify-release .claude/skills/verify-release
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Verify Release 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 Verify Release 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 Verify Release 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.

Verify release

Establish that the intended change is serving in the intended environment and that its agreed behavior works there. Keep the verification proportional to the change. Use the repository's existing deployment tools, tests, and observability; no particular provider, framework, browser, or telemetry service is required.

Carry forward the request

Recover the target environment, candidate release, expected behavior, selected checks, and existing authorization from the request and any tracker or handoff. Inspect deployment configuration and the relevant diff only as needed to fill gaps. Ask only for a consequential choice you cannot establish; do not repeat settled scope or permission questions.

Identify the components and dependencies that actually serve the selected path. Do not make unrelated or intentionally disabled services gates. Keep environments and test identities separate. A preview result proves only what that preview exercised.

Establish the live candidate

Map the intended change to an immutable deployed identity: commit, image digest, build ID, package version, or equivalent. Use the release manifest when components have different versions; do not require every component to share one SHA. A merge commit may differ from the PR head: establish the mapping instead of assuming a mismatch or equivalence.

Check the deployment's state and its running artifact, not merely a green CI job or a completed deploy label. Where available, corroborate with a live version endpoint or fresh runtime evidence. A missing version endpoint is not itself a defect if another trustworthy source proves the running artifact. If identity cannot be established, report that gap instead of claiming the candidate passed.

If rollout is still progressing, use bounded waits appropriate to its normal duration and continue independent checks. Resume dependent checks as soon as their prerequisites pass. Stop unchanged retries when evidence shows failure, unavailable access, or an exhausted execution limit. State the next diagnostic or resumption condition. Claim ongoing monitoring only when a real monitor is running, with an owner and a way to retrieve its result; otherwise save a resumable checkpoint.

Verify the changed path

  • Readiness: inspect applicable health/readiness checks and effective configuration. When relevant, include traffic destinations, build-time versus runtime settings, TLS, migrations, and queue routing. A removed probe or a process saying “ready” does not prove the configured readiness contract.
  • Prerequisites: before a stateful probe, check the chosen identity, permissions, effective flags, fixture state, and capacity needed for that case. Mark blocked cases individually and continue runnable ones. Do not repeatedly swap accounts without checking what prerequisite would change.
  • Behavior: run the smallest live probe that exercises the changed boundary through its actual entry point. Use AutoQA when available for an agreed test matrix or substantial browser/stateful coverage; pass the existing scope and candidate identity. For a narrow check, use the project's existing smoke command or a focused API, CLI, or browser probe.
  • Outcome: correlate the request with its actual result. HTTP acceptance is insufficient for an asynchronous workflow. Verify the relevant terminal state or side effect. A browser error can occur after the server accepted a request: establish whether it executed before retrying a mutation.
  • Observability: inspect fresh, relevant signals in the target environment and rollout window. Check environment/release attribution when applicable. Old events, another environment's traffic, or no traffic at all do not establish success. Separate observed failures from unproven causes and explain whether baseline issues affect acceptance.

Use existing authorization for tests and fixes. Verification alone does not authorize deployment, rollback, flag changes, credential changes, or new spending. If a fix is authorized, follow it through the applicable release and recheck the affected cases. Otherwise report the concrete repair and continue independent verification. Restore temporary test state that this run owns, respecting concurrent changes, and verify cleanup.

Close or resume

For longer work, update the existing tracker or one compact receipt in private session scratch space; do not build a second task system. Record:

  • Target, intended-to-observed release mapping, and observation time/window.
  • Required checks with PASS, FAIL, BLOCKED, or NOT RUN, plus evidence pointers.
  • Cleanup, remaining gaps, and the exact next action or resumption condition.

On resume and before the final verdict, recheck the deployed identity and relevant configuration. Label evidence from a superseded candidate and repeat only checks whose applicability changed. Never silently combine results from different environments or releases.

Lead the answer with VERIFIED, FAILED, or INCOMPLETE, qualified by environment, candidate, and tested scope. Name both intended and observed identities when they differ. A required failed check means FAILED; missing required evidence means INCOMPLETE. Use VERIFIED only when all required checks pass and required cleanup is confirmed. Distinguish rollout failure, application failure, and test-tool failure. State material coverage limits without implying full release or production approval. Link concise evidence; keep secrets and private payloads out of the receipt and reply.

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 Verify Release AI skill do?

Verify a specific release in its target environment, follow an in-progress rollout, and resume agreed checks when it is ready. Use for “I deployed it, verify”, “monitor the deployment and continue QA”, or “is this release working in staging/production?”. Discovers the stack and uses live evidence. Not a deployment tool or a full QA campaign by default.

Why use Verify Release on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Parcha-ai/parcha-skills/tree/main/verify-release/skills/verify-release. 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 Verify Release?

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 Verify Release?

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

Is the Verify Release AI skill free?

Yes. It is published on GitHub by Parcha-ai 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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