Agentic QA Onboard

Agentic QA Onboard — First-time tour of this repo

Activate when a user lands on this repo for the first time and asks "where do I start?", "how does QA work here?", or invokes /agentic-qa-onboard. The skill is a guided tour, not an executor: it explains the stack, the QA pipeline (pre-sprint Stage 0 + in-sprint Stages 1-6), the MCPs, and the env vars that everything depends on, then hands off to the right downstream skill.

This skill is specific to this Playwright + KATA QA boilerplate and points at the concrete entry points (/shift-left-testing, /sprint-testing, /test-automation, /test-documentation, /regression-testing, /framework-development).

Teaching mode — when someone is lost or wants to understand a skill

This skill is also the front desk for anyone who is confused: "I don't know how to use this", "how does /sprint-testing actually work?", "what does this repo even do?", "explain test-automation to me", "no entiendo cómo funciona esto". When that happens, step into the scene as a friendly guide and follow these rules:

1. Speak like a human, not a terminal. For the whole explanation, suspend any compressed / caveman register — full sentences, warm tone, simple words, zero unexplained jargon. Define each technical term the first time you use it ("an ATC — basically one complete test case, start to finish"). This is an explicit in-skill override of the default register; resume your normal style once the person is oriented.
2. Mirror the user's language. Spanish in → explain in Spanish. English in → explain in English — but note that the visual decks ship in Spanish only (technical terms stay in English inside them).
3. Start from where they are. If the goal is unclear, ask ONE quick question ("are you trying to test a ticket, or understand the whole flow?"). Don't dump all six stages on someone who asked about one.
4. Concept first, in plain words — what the activity is and why it matters — before any command, flag, or file path.
5. Then offer the visual presentation. Each workflow skill has a how-it-works deck that walks the skill's workflow step by step: a cover slide, a full workflow map (main path + adjacent paths), then one phase per slide with the craft concepts embedded where they apply. Offer to open it in their browser — follow the opening protocol below.
6. Hand off when oriented. Once they know which skill to call, point them at it and step back.

How-it-works presentations (visual, in the browser)

Six of the workflow skills ship a self-contained HTML presentation (Spanish; technical terms in English) that teaches the skill as a step-by-step workflow — and agentic-qa-core adds two cross-cutting reference decks (naming conventions + skills inputs/outputs; see the section below). Each how-it-works deck follows the same shape: slide 1 is the cover (/skill-name), slide 2 is the full workflow map (main path + adjacent paths: gates, fallbacks, handoffs), then one phase per slide with the craft concepts embedded where they apply, closing with handoffs and how to invoke the skill.

Cross-cutting reference decks (agentic-qa-core)

Beyond the per-skill workflow decks, agentic-qa-core ships two transversal reference decks. Offer them by intent, not by skill:

The skills-io deck is the best single answer to "what does skill X need / produce" or "show me the whole pipeline" — it renders as a Mac-style terminal with one tab per phase (arrow keys or 1-9 to switch tabs). The full deck catalog (including the academy/craft decks per skill) lives on the published homepage below.

Single files (CSS + JS inlined) — they open by double-click, no server. Navigate with ← →, S for speaker notes, O for the slide overview, F for fullscreen.

Published site (PREFERRED source — works in every project)

All decks — plus the interactive KATA Academy and the boilerplate homepage — are published on the boilerplate's GitHub Pages hub:

https://upex-galaxy.github.io/agentic-qa-boilerplate/           ← homepage (deck catalog)
https://upex-galaxy.github.io/agentic-qa-boilerplate/kata/      ← KATA Academy (interactive)
https://upex-galaxy.github.io/agentic-qa-boilerplate/decks/<skill>/<deck>.html

Example: .../decks/sprint-testing/how-it-works.es.html. The <skill>/<file> segment matches the local paths in the table above. Prefer the published URL — it always works, even in consumer projects scaffolded from this boilerplate (which may not carry the local HTML files). Use the local file only when offline or when the user explicitly wants the repo copy.

Opening protocol (ALWAYS ask first)

Opening a deck launches the user's default browser — an outward, local action — so never open one without asking, and open only ONE at a time.

1. Announce + ask. "I can open a short visual deck that walks through how /sprint-testing works — the full workflow map first, then each phase step by step. Want me to open it in your browser?"
2. Decks are Spanish-only (.es.html). If the user speaks English, mention the deck is in Spanish (technical terms stay in English) before opening it.
3. On a yes, open exactly one deck — published URL first; local file as offline fallback (pick the OS command for the user's platform):

   open "https://upex-galaxy.github.io/agentic-qa-boilerplate/decks/sprint-testing/how-it-works.es.html"  # macOS → default browser
   xdg-open "https://upex-galaxy.github.io/agentic-qa-boilerplate/decks/sprint-testing/how-it-works.es.html" # Linux
   start "" "https://upex-galaxy.github.io/agentic-qa-boilerplate/decks/sprint-testing/how-it-works.es.html" # Windows
   # offline / repo-copy fallback (only if the file exists locally):
   open "packages/decks/sprint-testing/how-it-works.es.html"
   

4. One at a time. Let the person watch and come back with questions before offering the next skill's deck. Do not batch-open several.
5. After it opens, tell them the keys (← → to move, S for speaker notes) and offer to walk the slides together or answer questions as they go.
6. For "how does KATA work" / architecture questions, also offer the interactive KATA Academy (.../kata/) — 8 interactive chapters, Spanish, presentation mode with the P key.

Welcome

This is the Agentic QA Boilerplate — a QA-only boilerplate for testing web applications with AI agents in the loop. The repo ships skills, scripts, and conventions that turn a Jira QA ticket into documented test cases and automated regression coverage through a structured 6-stage pipeline. It does not ship the application under test — that lives in a separate target repo (configured via .agents/project.yaml).

If you cloned this repo and you don't yet have bun run setup complete, start there. Everything else assumes the foundation is green.

Stack

The stack is intentionally locked. If your QA project needs a different stack (Cypress, Robot Framework, etc.), this boilerplate is not the right starting point — the KATA architecture is Playwright-specific.

First-time setup

Run the interactive installer once after cloning:

bun run setup

This bootstraps .agents/, installs the gentle-ai engram component (minimal preset), configures the 6 canonical MCPs, downloads Playwright browsers, installs 7 user-level community skills + 3 project-level community skills, and verifies the ${VAR} placeholders in the committed .mcp.json against your .env. Full details in INSTALLER.md.

After setup, fill .env with the credentials the rest of the workflow expects (see "Critical env vars" below).

New project path — from a fresh clone to a repo adapted to YOUR app

bun run setup is phase 1 of 4, not the whole story. A brand-new project (new app under test, new Jira project) walks this ordered sequence before the first ticket. Each phase self-defends (later steps gate on earlier ones), but knowing the order saves you from discovering it by error message:

After phase 4: bun run context:hydrate to pull the Jira cache, then /sprint-testing <KEY> for the first ticket. Joining an ALREADY-adapted project instead? Skip phases 2-4 (someone did them) and just run the checklist at the end of this tour.

Primary pipeline: Stage 0 (pre-sprint) + Stages 1-6 (in-sprint)

The QA work in this boilerplate runs in two halves: a pre-sprint Shift-Left grooming phase, then a 6-stage in-sprint pipeline per ticket. Each stage maps to a skill.

Jira QA state machine:

Authoritative source: .agents/jira-workflows.json. Status and transition names below are copied from that file (regenerate with bun run jira:sync-workflows). Never write a Jira status from memory — if it is not in .agents/jira-workflows.json, it does not exist in the instance.

Backlog → Shift-Left QA → Estimation → Ready For Dev → In Progress → In Review → Ready For QA → In Test → QA Approved → Ready For Release → Deployed to Production

/shift-left-testing drives the upstream transitions (Backlog → Shift-Left QA → Estimation). /sprint-testing drives the downstream ones (Ready For QA → In Test → QA Approved). PO/Dev lead drive the middle leg (Estimation → Ready For Dev → In Progress → In Review). A defect found in test sends the story In Test → BLOCKED (transition defect reported); ABORTED is the other terminal.

(For bugs found during QA: Open → In Progress → In Review → Ready For QA → Closed — the ReTest Passed transition closes it after fix verification. Non-fix terminals: Deferred, Duplicated, Enhancement, Cannot Reproduce, REJECTED, ABORTED.)

(Test cases in the TMS have their own lifecycle too: READY → In Review → Candidate → In Automation → Pull Request → AUTOMATED — MANUAL is the terminal for tests that will never be automated.)

Each Story gets three canonical TMS artifacts: the ATP (plan), the ATR (results), and the ATS (Acceptance Test Set — groups ALL the Story's TCs; its link to the Story is what fills the Xray coverage panel). Above the Story sits the planning ladder: FTP per feature/Epic (/sprint-testing feature-test-planning), STP at sprint start + STR recap at sprint close (/sprint-testing, with /regression-testing as fallback/completer), and the MTP Epic from /master-test-plan.

Two conventions apply to every quality issue you file along the way. Components are the target app's functional modules — mandatory on bugs, defects, improvements, and Tests — and are reconciled against the app's real modules via /jira-components. And bugs parent to the QA process epics (e.g. "QA Defect Management"), never a product/dev epic, carrying the source Story via an issue-link: parent = QA bucket, link = source Story, components = product module (the three-axis model).

/sprint-testing orchestrates Stages 1-3. Stage 4 onwards are explicit hand-offs. Wondering what is already covered before Stage 4/5? bun run tests:map renders the synced Epic → Story → Test tree (plus orphans and a component rollup) as one HTML page, and the /xray-cli skill's test enrich command backfills the synced Test cache with the Xray-internal associations (Preconditions, Test Set membership) the Jira REST sync cannot see.

Stage 1-3 example flow

/sprint-testing UPEX-277:

1. Syncs the ticket from Jira via bun run jira:sync-issues get <KEY> --include-comments (canonical detailed read — acli view returns null for custom fields), then reads the materialized .md files.
2. Loads the synced context from .context/PBI/epics/EPIC-<KEY>-<slug>/stories/STORY-<KEY>-<slug>/ (Module = Epic; Jira-synced files are a read-only cache).
3. Explores the relevant code in the target repo.
4. Authors the ATP (Acceptance Test Plan) → writes it to the Jira field (or fallback comment) → re-syncs; hand-writes only NON-Jira files (context.md, evidence/).
5. Executes smoke + trifuerza exploration (UI / API / DB).
6. Files ATR (Acceptance Test Results) + bug reports if defects found.
7. Transitions the ticket through QA states.
8. Hands off to Stage 4 (/test-documentation) to document the executed test cases in the TMS and score ROI — Stage 4's Candidate verdicts are what feed /test-automation.

You confirm at the gates.

When to use /framework-development instead

/framework-development covers framework evolution (changes to the boilerplate's own infrastructure, not per-ticket test writing). Self-contained Plan → Code → Verify → Archive pipeline; works under the minimal install preset (no SDD-* skills required).

MCPs available

Six canonical MCPs ship with the boilerplate:

The Atlassian MCP is opt-in (setup in docs/mcp/) — the primary Jira tools are /acli and bun run jira:sync-issues.

Decision rule:

• Use Context7 for "how to use X" — official docs, current API
• Use Tavily for "how to solve X" — community fixes, troubleshooting
• Use /acli for ticket WRITES (create, transition, comment, link); for detailed READS (custom fields, ACs, ATP/ATR, comments) use bun run jira:sync-issues get/jql
• Use Playwright MCP for ad-hoc live browser interactions; for scripted runs use /playwright-cli

.mcp.json lives at the repo root and is committed — it is secret-free, referencing secrets as ${VAR} placeholders resolved from .env. Only .mcp.local.json (personal overrides) is gitignored.

Critical env vars

Place these in .env before running anything that talks to a real environment:

.env is gitignored. Never commit it. .agents/project.yaml (committed) holds non-secret context (URLs, project key, environment names); .env holds the matching secrets.

.mcp.json is committed and safe to commit — it never holds a secret value, only ${VAR} placeholders that Claude Code resolves from .env at runtime. Personal overrides go in the gitignored .mcp.local.json.

Verify your config with bun run vars:check (should report 0 errors when fully configured).

Local skills (committed in this repo)

What bun run setup installs via gentle-ai

bun run setup runs gentle-ai install --preset minimal — installs ONLY the engram component (persistent memory binary + MCP adapter + agent config). No SDD-* skills, no foundation skills.

Rationale: this repo already covers Plan → Code → Verify natively in its workflow skills (/shift-left-testing, /sprint-testing, /test-automation, /test-documentation, /regression-testing). SDD ceremony does not apply to test authoring.

Want the explicit SDD ceremony for an architectural change of your own? Run manually:

gentle-ai install --components engram,sdd --agent <claude-code|opencode|cursor>

Full details in INSTALLER.md.

Community skills installed at user level

bun run setup also runs bunx skills add --global for 7 cross-project skills:

Plus 3 project-level community skills installed into .agents/skills/ (not committed): playwright-cli, playwright-best-practices, resend-cli. See cli/install.ts PROJECT_LEVEL_SKILLS and USER_LEVEL_SKILLS arrays.

Next steps after the onboard

On a brand-new project (new app under test / new Jira project): follow the 4-phase "New project path" above — this checklist alone is not enough, it only covers phase 1.

Joining an already-adapted project: run through this checklist before you reach for your first ticket:

• Did you run bun run setup?
• Did you fill .env with your own credentials (LOCAL_*, STAGING_*, ATLASSIAN_*, XRAY_*, TAVILY_API_KEY, POSTMAN_API_KEY)?
• Did you populate .agents/project.yaml (run bun run agents:setup if not yet)?
• Does bun run vars:check exit clean (0 errors)?
• Did you run bun run jira:check to verify Jira credentials?
• Did you run bun run pw:install to get Playwright browsers?
• Did you run bun run context:hydrate to build the .context/PBI/ Jira cache? (gitignored and regenerable — Jira stays the source of truth)
• Does the git_strategy: block in .agents/project.yaml reflect a CHOSEN strategy (meta.strategy_source: chosen)? If it still says inherited, git-flow-master will offer Strategy Setup on your first git action — accepting takes 4 questions.
• Does engram persistent memory respond (try mem_context after restart)?
• Ready for your first QA ticket: /sprint-testing <UPEX-XXX>

If any box is unchecked, fix that first. The downstream skills assume a green foundation.

What this skill does NOT do

• Refine backlog Stories pre-sprint → use /shift-left-testing
• Test a ticket → use /sprint-testing
• Document test cases in TMS → use /test-documentation
• Write automated tests → use /test-automation
• Run a regression suite → use /regression-testing
• Discover a brand-new target project → use /project-discovery
• Adapt the KATA test architecture to a target stack → use /adapt-framework

The onboard tour ends at the moment the user knows which skill to call next. From there, the relevant workflow skill takes over.