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Qa Acceptance

OrganizationPopular
paperclipai
qa-acceptance

Produce QA acceptance criteria and a manual validation plan for a feature change — golden path, edge cases, error states, performance limits, and explicit pass/fail evidence.

Overview

Publisherpaperclipai
Repositorypaperclip
Skill nameqa-acceptance
Stars
95.4K
Forks
16.2K
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 paperclipai on GitHub. Read the source before you install it.

Installation

Install the Qa Acceptance 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/paperclipai/paperclip/tree/master/packages/skills-catalog/catalog/bundled/quality/qa-acceptance
  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/paperclipai/paperclip.git /tmp/paperclip
mkdir -p .claude/skills
cp -r /tmp/paperclip/packages/skills-catalog/catalog/bundled/quality/qa-acceptance .claude/skills/qa-acceptance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Qa Acceptance 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 Qa Acceptance 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 Qa Acceptance 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.

QA Acceptance

Write acceptance criteria that a reviewer can run against the running app and decide pass or fail without asking the author. The criteria are the contract — automated tests cover correctness, QA covers feature-level behavior.

When to use

  • A feature change is heading to QA and needs a written validation plan.
  • A reviewer is asked to verify a PR that touches user-visible behavior.
  • An incident postmortem requires a regression check before reopen-prevention.
  • A release candidate needs a pre-cut smoke pass.

When not to use

  • The change is unit-test-only (utility refactor, internal naming). Acceptance criteria are unnecessary churn.
  • You are asked to write tests against API contracts. Use contract testing, not feature QA.

Acceptance criteria format

Each criterion is a single, independently-verifiable statement:

md
- **Given** <starting state>, **when** <action>, **then** <observable outcome>.

Example:

md
- **Given** a CSV export with 0 rows, **when** the user clicks Export, **then** the file downloads with only the header row and the UI shows "Exported 0 rows".

Avoid criteria that combine multiple whens or thens. Split them.

What every plan must cover

  1. Golden path. The most common successful flow, end to end.
  2. Empty and minimum states. Zero items, one item, missing optional inputs.
  3. Boundary inputs. Max length strings, max numeric values, unicode, RTL text where applicable.
  4. Error states. Network failure, permission denied, validation failures, conflict (409), not found (404).
  5. Concurrency and ordering. Two users acting at once, race against background jobs, refresh during mutation.
  6. Performance envelope. The largest realistic input the change must handle without UI hangs or timeouts.
  7. Backward compatibility. Existing data, existing URLs, persisted user preferences continue to work.
  8. Telemetry and audit. Events, logs, or activity entries the change is supposed to emit.

If a section is genuinely not applicable, write "N/A: " — do not silently omit.

Evidence

Each criterion needs evidence on the verification pass:

  • Screenshot or short clip for UI behavior.
  • Copied console / network output for API behavior.
  • Log snippet or activity row for telemetry.
  • Timing measurement for performance criteria.

"Looks good to me" without evidence is not a pass.

Quarantine and follow-up

  • A failing criterion blocks acceptance unless explicitly waived by the owner with a tracked follow-up issue.
  • "Known issue" without a linked follow-up is not a waiver.
  • If you add a new criterion mid-pass, restart the pass — partial coverage hides regressions.

Handoff back to the author

Return the validation plan with three sections:

  • Pass. Criteria that passed, with one-line evidence summaries.
  • Fail. Criteria that failed, with the exact reproduction.
  • Blocked. Criteria you could not run, with why.

The author owns turning failures into either fixes or accepted deferrals.

Anti-patterns

  • Acceptance phrased as test plan ("write a Cypress test for X"). Acceptance is what is true after the change ships; tests are how you check.
  • Criteria that depend on inspecting implementation details (selectors, query plans). Stay observable.
  • Long checklists with no priority. Mark must-pass criteria distinctly from nice-to-have.
  • Validation reports that say "passed" with no evidence. Reviewers cannot audit those.

Frequently asked questions

What does the Qa Acceptance AI skill do?

Produce QA acceptance criteria and a manual validation plan for a feature change — golden path, edge cases, error states, performance limits, and explicit pass/fail evidence.

Why use Qa Acceptance on TypingMind?

Because you install it once and use it with any model. Qa Acceptance 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 Qa Acceptance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/paperclipai/paperclip/tree/master/packages/skills-catalog/catalog/bundled/quality/qa-acceptance. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Qa Acceptance?

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 Qa Acceptance?

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

Is the Qa Acceptance AI skill free?

Yes. It is published on GitHub by paperclipai 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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