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Agent skill

QA Acceptance

by paperclipai in paperclipai/paperclip

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.

MITAuto-check passedProduct & Project Management

Install QA Acceptance

skills CLI
$ npx skills add paperclipai/paperclip --skill qa-acceptance -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install paperclipai/paperclip qa-acceptance --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/paperclipai/paperclip.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills-catalog/catalog/bundled/quality/qa-acceptance .claude/skills/qa-acceptance && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
qa-acceptance
GitHub stars
99k
Token cost
~964 tokens
SKILL.md length
460 words
Files
1
Skills in repo
60
Repo updated
First seen
Licence
MIT

At a glance

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.

  • Works in 8 steps: Golden path. The most common successful… → Empty and minimum states. Zero items,… → Boundary inputs. Max length strings, max… → …
  • Tasks that involve User stories
  • SKILL.md covers When to use, When not to use, Acceptance criteria format and What every plan must cover, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

QA Acceptance is an agent skill from paperclipai/paperclip. 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.

Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Product & Project Management, covering User stories and Platform engineering. The repository describes itself as: The open-source app everyone uses to manage agents at work. The licence is MIT.

When your agent uses it

  • Tasks that involve User stories
  • Tasks that involve Platform engineering

Example prompts

  • “/qa-acceptance”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit b9750b1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

QA Acceptance loads about 964 tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 460 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~964

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from paperclipai/paperclip at commit b9750b1, republished under its MIT licence (© paperclipai). 460 words, ~964 tokens.

Download SKILL.mdSave it as .claude/skills/qa-acceptance/SKILL.md (or your agent's skills folder).
name
qa-acceptance
description
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.
key
paperclipai/bundled/quality/qa-acceptance
recommendedForRoles
qa, engineer, product
tags
qa, acceptance, validation, testing

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: <why>" — do not silently omit.

Show full SKILL.md (196 more words)Show less

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.

© paperclipai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/skills-catalog/catalog/bundled/quality/qa-acceptance of paperclipai/paperclip.

Open the folder on GitHubat commit b9750b1

Compare with similar skills

QA Acceptance next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

QA Acceptance compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
QA Acceptance this skillpaperclipai/paperclip99k—~964Automated safety check: PassMIT
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Agile Product Owneralirezarezvani/claude-skills28k3 repos~3.2kAutomated safety check: PassMIT
Ralph Tui Create Beads Rustsubsy/ralph-tui2.5k1 repos~2.8kAutomated safety check: PassMIT
To Specbestofjs/bestofjs3.1k21 repos~757Automated safety check: PassMIT

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Categories

Questions about QA Acceptance

What does QA Acceptance 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. QA Acceptance is an agent skill from paperclipai/paperclip. 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.

When should I use QA Acceptance?

QA Acceptance fits situations like: tasks that involve User stories; tasks that involve Platform engineering.

How do I install QA Acceptance in Claude Code?

Run `npx skills add paperclipai/paperclip --skill qa-acceptance -a claude-code`. Or copy the skill folder (packages/skills-catalog/catalog/bundled/quality/qa-acceptance in paperclipai/paperclip) into .claude/skills/qa-acceptance in your project. Claude Code loads it when a task matches its description.

How do I install QA Acceptance in Codex?

Run `npx skills add paperclipai/paperclip --skill qa-acceptance -a codex`. Or copy the skill folder (packages/skills-catalog/catalog/bundled/quality/qa-acceptance in paperclipai/paperclip) into .agents/skills/qa-acceptance in your project. Codex loads it when a task matches its description.

Can I use QA Acceptance in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add paperclipai/paperclip --skill qa-acceptance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qa-acceptance, .gemini/skills/qa-acceptance, .github/skills/qa-acceptance and .opencode/skills/qa-acceptance in your project.

What does QA Acceptance need to run?

SKILL.md names no scripts, command-line tools or credentials: QA Acceptance is instructions for the agent only.

Does QA Acceptance access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is QA Acceptance safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does QA Acceptance use?

QA Acceptance is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does QA Acceptance use?

About 964 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to QA Acceptance?

Skills that share tags, products or a category with QA Acceptance: User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars), Ralph Tui Create Beads (subsy/ralph-tui, 2.5k stars), Agile Product Owner (alirezarezvani/claude-skills, 28k stars) and Ralph Tui Create Beads Rust (subsy/ralph-tui, 2.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains QA Acceptance?

paperclipai (a GitHub organization) maintains it in paperclipai/paperclip, which has 98,967 GitHub stars. The repository holds 60 skills in this directory. The repository was last updated on October 9, 2026.

Source: paperclipai/paperclip on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.