regression-testing

name	regression-testing
description	Execute regression test suites via CI/CD, analyze results, classify failures, and produce GO/NO-GO release decisions. Use when running regression, smoke, or sanity suites through GitHub Actions, monitoring workflow runs, downloading Allure or Playwright artifacts, classifying failures (REGRESSION vs FLAKY vs KNOWN vs ENVIRONMENT vs NEW TEST), computing pass-rate and trend metrics, deciding release readiness, generating executive quality reports, or creating regression issues. Triggers on: run regression, trigger test workflow, analyze test results, quality report, GO/NO-GO decision, release readiness, flaky tests, Allure report, smoke suite, pass rate, nightly test failure, stage 6. Do NOT use for writing new regression tests (that belongs to test-automation) or for manual fix verification (that belongs to sprint-testing).
license	MIT
compatibility	["claude-code","copilot","cursor","codex","opencode"]
complementary_categories	["testing-e2e","ci-cd"]

Forbidden invocations

NEVER invoke /sdd-* skills from this workflow. SDD is an optional user-installed ceremony; this skill ships self-contained and does not chain SDD under any condition. If you need to refactor KATA, fixtures, cli/, scripts/, or api/schemas/ pipeline, exit this skill first and invoke /framework-development — which itself runs Plan → Code → Verify → Archive natively (no SDD required).

This boundary is mechanical, not advisory: scripts/lint-skills.ts rejects any /sdd- mention outside this section. See: .claude/skills/agentic-qa-core/references/skill-composition-strategy.md §4 (governs users who manually install SDD).

Regression Testing — Execute, Analyze, Decide

Orchestrates the full release-readiness pipeline: trigger a CI suite, monitor it to completion, classify failures, score against release criteria, and emit a GO / CAUTION / NO-GO verdict plus a stakeholder report.

Three phases, always in this order: Execute → Analyze → Report. Do not skip analysis and jump to a report. Do not guess classification without reading failure logs.

---

Inputs

• .github/workflows/*.yml — workflow files for regression / smoke / sanity suites; defines triggers, inputs, and artifact uploads.
• .context/master-test-plan.md — regression Epic key + expected pass-rate SLOs per suite.
• playwright.config.ts — reporter config, retry policy, project matrix; needed to interpret retry counts and shard splits.
• Previous run's Allure report (artifact URL or local download under ./analysis/previous/) — baseline for trend computation.
• kata-manifest.json — registry of tests and ATCs available; used to cross-reference failed test IDs.
• .agents/jira-required.yaml — Jira refs (project key, work types, transitions) for filing regression issues.
• agentic-qa-core/references/defect-management-doctrine.md — canonical authority for classifying (Bug/Defect/Improvement), the mandatory field matrix, QA-Assignee ownership, and the QA process epic when a confirmed regression is filed in Jira (Phase 3). Read BEFORE filing any defect.

---

Subagent Dispatch Strategy

Orchestration & Session contracts: this skill follows ./orchestration-doctrine.md (mandatory subagent dispatch — main thread is command center) AND ./session-management.md (Phase 0 resume check, plan-first persistence at .session/<skill-slug>/<scope>/, archive on completion). Phase 0 (resume check) and Phase 1 (plan write) are NOT optional. The orchestrator also applies the per-stage Definition-of-Done gates in ./stage-gates.md: verify a stage's DoD BEFORE recording its progress checkpoint and advancing.

This skill is per-run scope: <scope> = <env>-<YYYY-MM-DD> (e.g. staging-2026-05-20). Session state lives at .session/regression-testing/<scope>/{plan.md, progress.md} per agentic-qa-core/references/session-management.md §3 + §9. The single highest-value resume case: if the Monitor subagent dies while watching a long CI run but RUN_ID was captured in plan.md, Phase 0 re-attaches via gh run view <RUN_ID> instead of re-triggering CI (saves 20–60 min of wall-clock).

This skill is compliant with the doctrine in CLAUDE.md §"Orchestration Mode (Subagent Strategy)" and the session contract in .claude/skills/agentic-qa-core/references/session-management.md. Every dispatch follows the 6-component briefing format defined in .claude/skills/agentic-qa-core/references/briefing-template.md, and the pattern selected per stage matches the decision guide in .claude/skills/agentic-qa-core/references/dispatch-patterns.md. The two CI-bound stages (long-running watch, multi-artifact download) and the high-volume failure classification step are the hotspots — everything else stays inline because the dispatch overhead is not justified.

Stage	Pattern	Subagent role
Trigger workflow (gh workflow run)	Single	inline — no dispatch needed (one shell call)
Wait/monitor gh run watch	Background	one Monitor subagent runs the watch; main thread continues with prep work; subagent notifies on exit
Download 3 artifacts (allure / evidence / playwright)	Parallel	3 simultaneous subagents, one per artifact; cap = 3 (no rate-limit risk)
Classify failures (chunks of ~10 tests each)	Parallel	N subagents based on failure volume; cap = 10 to avoid context dilution
Compute metrics (pass-rate, trends)	Single	inline — needs aggregated state, low cost
Generate executive report	Single	inline — final synthesis, decisions live here
GO / CAUTION / NO-GO verdict	Single	inline — main thread owns release decisions

• Error protocol: On any subagent failure: STOP, report full context to user, present retry / skip / abort options. Do NOT auto-fix. See .claude/skills/agentic-qa-core/references/orchestration-doctrine.md.

---

Readiness Preflight Gate (MANDATORY — runs before Phase 0)

Full doctrine: agentic-qa-core/references/preflight-gate.md. Runs FIRST, before the resume check and any gh workflow run. Two laws: (1) args-as-answers — the suite (regression/smoke/sanity), env, and any grep/test_file are provided args; ask only the gaps. (2) probe, don't assume. Surface gaps + REDs as ONE AskUserQuestion checklist; self-fix with approval + explanation; STOP on any blocking RED. This generalizes the Phase 1 §Preflight (gh auth) to a full readiness check pulled to t=0. Generic baseline (env resolution, secret/restart handling, the two laws, output contract) is inherited from the reference §3.1 — not repeated here. Below is only this skill's specific capability delta (note: test-user creds, MCPs and browsers live inside the CI runner, not the orchestrator).

Capability	Need	Why here
GitHub CLI authenticated	REQUIRED	Every stage drives CI via gh (gh auth status, gh workflow run, gh run watch, gh run download). Not authed → user runs gh auth login (suggest the ! prefix); do not proceed.
Workflow files present	REQUIRED	.github/workflows/ must hold the regression/smoke/sanity workflow for the chosen suite, with the inputs this skill passes.
GitHub Actions Secrets/Variables	REQUIRED	The runner authenticates with env-prefixed creds (secrets.<ENV>_USER_EMAIL / _PASSWORD) + XRAY_* / ATLASSIAN_* as Repository/Environment Secrets — the suite 401s mid-run without them. gh secret list (add --env <env> for environment scope) shows them; missing → gh secret set <NAME> from .env. /adapt-framework only emits a manual list today, so this is the most common silent gap.
Allure 3 local	REQUIRED	bunx allure resolves (devDep, no global install); allurerc.mjs present for bun allure:agent markdown triage.
Active env	REQUIRED	The suite runs against <<ACTIVE_ENV>> (default {{DEFAULT_ENV}}). Confirm it is the intended target before a 20–60 min run.
[TMS_TOOL] (result sync)	OPTIONAL	Only when .agents/project.yaml testing.tms_cli is set — Stage 3 pushes run status. jira-xray → /xray-cli + XRAY_*.
[ISSUE_TRACKER_TOOL] (file regression issues)	OPTIONAL	Only on NO-GO / CAUTION-with-regressions, to file issues. Load /acli then.

Test-user creds, OpenAPI/API_TOKEN, DBHub and Playwright browsers live inside the CI runner, not the orchestrator — this skill does not exercise them locally, so they are out of scope for this gate. After the gate clears (all REQUIRED GREEN), continue to Phase 0 below.

---

Phase 0 — Session resume check (MANDATORY, inline)

Before suite selection or any gh workflow run, run the resume contract from agentic-qa-core/references/session-management.md §4:

1. Compute prospective <scope> = <env>-<YYYY-MM-DD> from invocation context (env defaults to {{DEFAULT_ENV}}).
2. Check .session/regression-testing/<scope>/progress.md.
3. If it does NOT exist → proceed to suite selection + Phase 1 preflight + plan.md write.
4. If it DOES exist:
   • Read plan.md (captured suite, env, workflow_file, RUN_ID if Phase 1 already triggered).
   • Read tail of progress.md.
   • If RUN_ID is present AND progress.md last entry is Phase 1 — Trigger — status: completed but Monitor entry is missing/failed: surface the option to re-attach to the existing RUN_ID via gh run view <RUN_ID> --json status,conclusion instead of re-triggering. This is the high-value resume case.
   • Otherwise surface the standard offer resume / restart / abort. On restart, archive to .session/.archive/<YYYY-MM-DD>-regression-testing-<scope>-aborted/ first.

---

When to run each suite

Suite	Workflow file	Duration	Use when
regression	regression.yml	20-60 min	Pre-release validation, nightly full run
smoke	smoke.yml	2-5 min	Post-deploy health check, @critical only
sanity	sanity.yml	1-10 min	Validate one feature / one file / one grep pattern

If the user says "run regression" with no qualifier, default to regression on {{DEFAULT_ENV}}. If they say "smoke" or "critical only", use smoke. If they specify a file, grep, or single feature, use sanity.

---

Local reporting (Allure 3, no global install)

Allure 3 is a devDep — bunx allure resolves to the local node_modules/.bin/allure, no brew install allure / scoop install allure required. Configuration lives at allurerc.mjs, single-plugin BY DESIGN: with only the Awesome plugin the generated index.html IS the report (no card-chooser landing), and its top-left mode dropdown covers everything — Report (drill-down, tag filters), Graphs (complete executive chart set: status, dynamics, severities, stability, testing pyramid, durations…), Timeline. Never add plugin-dashboard instances — they duplicate Graphs with fewer charts and bring back the landing screen (rationale in allurerc.mjs comments). Trend charts are fed by historyPath: ./.allure/history.jsonl and populate from the 2nd run onward.

Use case	Script	Underlying command
Run tests + auto-generate report (human review)	bun allure:run	bunx allure run -- bun test
Run tests + emit markdown for AI review	bun allure:agent	bunx allure agent -- bun test
Generate report from existing ./allure-results	bun allure:generate	bunx allure generate ./allure-results
Serve last generated report locally	bun allure:open	bunx allure open
Live-refresh report during iterative dev	bun allure:watch	bunx allure watch ./allure-results

bun allure:agent is the AI-friendly entry point: it produces a markdown summary the orchestrator (or a Verifier subagent) can read directly without parsing HTML. Use it whenever you need a structured pass/fail breakdown after a local re-run while triaging a CI failure (Phase 2 step 1, before downloading the merged-allure-results artifact from CI).

CI artifacts (merged-allure-results-{env}) are still produced by the workflow and downloaded via gh run download as documented in Phase 2. The published GitHub Pages reports are generated by scripts/ci/publish-allure-pages.ts with the SAME allurerc.mjs and allure devDep as local runs — the /{env}/{suite}/ URL redirects straight into the latest run's Awesome report (Report | Graphs | Timeline), with per-suite trend history and last-10-runs retention.

Allure version-currency check (MANDATORY during any Allure/Pages setup)

The boilerplate pins allure / allure-playwright / allure-js-commons at scaffold time, so by the time someone installs the repo and runs this setup they are usually behind upstream. Whenever this skill performs Allure setup (first local report, preflight RED on the "Allure 3 local" row) or GitHub Pages setup (references/github-pages-setup.md), run this check FIRST:

1. npm view allure version && npm view allure-playwright version → compare against package.json.
2. Same major behind → summarize the news for the user (release notes: gh api repos/allure-framework/allure3/releases), then offer bun update allure allure-playwright allure-js-commons (or bump the ^ ranges + bun install). Keep allure-js-commons in lockstep with allure-playwright (it is imported directly by tests/components/TestFixture.ts for the layer auto-label).
3. New major available → NEVER upgrade silently. Present breaking changes and wait for explicit user approval.
4. Config-currency (older scaffolds) — bun run update syncs skills and appends new devDeps, but it NEVER overwrites allurerc.mjs or tests/components/TestFixture.ts (project-adapted files). If the local allurerc.mjs predates the current template (no historyPath, no categories, or stale plugin-dashboard instances), OFFER to migrate it: fetch the boilerplate's current allurerc.mjs as reference (https://raw.githubusercontent.com/upex-galaxy/agentic-qa-boilerplate/main/allurerc.mjs), preserve the project's name, and port the config. Same for the _allureLayer auto-fixture in TestFixture.ts (feeds the testingPyramid + durations-by-layer charts in Awesome's Graphs tab) — without it those charts render empty. Never overwrite silently; show the diff and wait for approval.
5. After any bump: bun allure:generate from existing results (or a sandbox run) and confirm the report renders — the root index.html must open the Awesome report directly, with the Report | Graphs | Timeline mode dropdown working.

Known gotchas to preserve on upgrade (context in allurerc.mjs comments):

• Dashboard chart type values must match ChartType in @allurereport/charts-api — the plugin README's trend/pie examples are stale and yield an empty dashboard (404 on widgets/charts.json).
• historyPath must stay OUTSIDE allure-report/ (./.allure/history.jsonl) or test:clean erases trend history.
• Multiple instances of one plugin need an explicit import: field — a custom key alone does not resolve (relevant only if a project deliberately adds extra report views).

---

Phase 1 — Execute

Preflight (always)

gh auth status
gh repo view --json name,owner
gh workflow list

If gh is not authenticated, stop and ask the user to run gh auth login. Do not proceed.

Write .session/regression-testing/<scope>/plan.md per agentic-qa-core/references/session-management.md §6 BEFORE the Trigger step below. Capture: Goal (suite + env + reason for run), Inputs (workflow file path, env vars, optional grep/test_file for sanity), Approach (subagent pattern per stage from the dispatch table above), Phase breakdown (Trigger → Monitor → Download → Classify → Compute → Report → Verdict), Risks, Verification checklist (all 3 artifacts download + verdict emitted), Cross-references (.context/reports/regression-<env>-<date>.md will hold the final verdict). RUN_ID lands in plan.md §Inputs AFTER the Trigger step captures it — append, do not rewrite the body.

Trigger

# Full regression
gh workflow run regression.yml \
  -f environment=staging \
  -f video_record=false \
  -f generate_allure=true

# Smoke
gh workflow run smoke.yml -f environment=staging -f generate_allure=true

# Sanity (grep OR test_file, never both)
gh workflow run sanity.yml -f environment=staging -f test_type=e2e -f grep="@auth"
gh workflow run sanity.yml -f environment=staging -f test_file="tests/e2e/auth/login.test.ts"

Capture run ID

# Wait 3-5 seconds for the run to register, then:
gh run list --workflow=regression.yml --limit=1 --json databaseId,status,createdAt -q '.[0].databaseId'

Store as RUN_ID. Every subsequent step uses it.

Progress checkpoint after Trigger: append RUN_ID to .session/regression-testing/<scope>/plan.md §Inputs (so resume can re-attach) AND append a phase entry ## Phase 1.Trigger — <ts> with status: completed, next: Phase 1.Monitor, notes: RUN_ID=<value> to progress.md. This is the critical persistence point — Trigger landing without RUN_ID persisted means resume cannot re-attach.

Monitor to completion

Use the dispatch defined in §Subagent Dispatch Strategy: Background. Delegate gh run watch <RUN_ID> to a Monitor subagent so the main thread is freed to prepare the report scaffold and load the classification rubric. See references/ci-cd-integration.md §"Monitoring the workflow run (Background dispatch)" for the full briefing.

Reference command (executed inside the subagent, not inline on the main thread):

gh run watch <RUN_ID> --exit-status
# Fallback polling (only if gh run watch is unavailable):
gh run view <RUN_ID> --json status,conclusion
# status: queued | in_progress | completed
# conclusion (only when completed): success | failure | cancelled | timed_out

Do not start Phase 2 until the Monitor returns status: completed.

Output of Phase 1

A short execution summary with: workflow name, run ID, environment, duration, conclusion, per-job status, artifact list, and the Allure URL pattern https://{owner}.github.io/{repo}/{environment}/{suite}/.

Read references/ci-cd-integration.md when configuring new workflows, debugging CI-only failures, tuning sharding / retries / timeouts, or wiring up secrets and variables.

---

Phase 2 — Analyze

Step 1: Collect data

Use the dispatch defined in §Subagent Dispatch Strategy: Parallel for the three artifact downloads (allure / evidence / playwright). Fan out three subagents in a single tool-call block — each owns one artifact, writes to its own directory, and reports back when its download is verified. The metadata reads (gh run view) stay inline because they are short.

Reference commands (the metadata reads run inline; the three gh run download calls live inside the parallel subagents):

# Inline (main thread): full run context
gh run view <RUN_ID> --json status,conclusion,jobs,createdAt,updatedAt,url,headBranch,event,actor

# Inline (main thread): failed logs only (much smaller than --log)
gh run view <RUN_ID> --log-failed

# Inline (main thread): list artifacts so the parallel dispatchers know what to fetch
gh run view <RUN_ID> --json artifacts --jq '.artifacts[].name'

# Parallel subagent A — allure results
gh run download <RUN_ID> -n merged-allure-results-staging -D ./analysis/

# Parallel subagent B — failure evidence (screenshots, traces, videos)
gh run download <RUN_ID> -n e2e-failure-evidence       -D ./analysis/evidence/

# Parallel subagent C — playwright HTML report
gh run download <RUN_ID> -n e2e-playwright-report      -D ./analysis/playwright/

Each subagent uses the briefing shape in agentic-qa-core/references/briefing-template.md §"Parallel — Download 3 CI artifacts in regression-testing". Cap the fan-out at 3 — there are only ever three artifact streams and GitHub's per-run rate limits are not a concern at that size.

Step 2: Parse results

Source of truth priority: Allure results JSON > Playwright report.json > raw logs. Each Allure result has status, statusDetails.message, statusDetails.trace, and labels[] (look for testId = ATC ID, suite, and severity).

The suite label is tag-derived — single source of truth. Allure suite/grouping labels are NOT a separate taxonomy: they derive from the Playwright tag (@smoke / @regression / @e2e / @integration / @critical) that also drives CI scope selection. A test tagged @integration reports suite: integration automatically. So the suite you read here is exactly the scope CI ran — never reconcile it against a parallel Allure label set. Convention owner: test-automation/references/ci-integration.md §3.2.1.

Step 3: Compute metrics

Metric	Formula
Total	count of results
Passed / Failed / Skipped / Broken	count by status
Pass Rate	Passed / Total * 100
Duration	max(stop) - min(start)
Trend	current pass rate − previous run pass rate

Exclude KNOWN-BLOCKED from the gating pass-rate. Tests classified KNOWN-BLOCKED (tagged @blocked:{BUG-KEY}, see Step 4) are parked behind an already-filed bug — they are NOT regression failures and must not depress the pass-rate that drives the GO/NO-GO score. Compute the gating Pass Rate over Total − KNOWN-BLOCKED, and report the blocked count separately (with each {BUG-KEY}) so the release decision is not gamed in either direction.

Previous-run comparison requires downloading artifacts of the previous run:

PREV=$(gh run list --workflow=regression.yml --limit=2 --json databaseId -q '.[1].databaseId')
gh run download $PREV -n merged-allure-results-staging -D ./analysis/previous/

Step 4: Classify every failure

Use the dispatch defined in §Subagent Dispatch Strategy: Parallel when the failure list has more than 10 entries. Shard the failures into chunks of ~10 (cap at 10 subagents) and fan out one classification subagent per chunk; merge their JSON reports in the main thread. For ≤10 failures, classify inline (the dispatch overhead is not justified). See references/failure-classification.md §"Parallel classification (default for >10 failures)" for the full briefing and merge protocol.

Apply this decision tree to each failed test (whether classified inline or inside a parallel subagent). Never mark a test REGRESSION without checking history first — that is the single most common misclassification.

Failed test
  │
  ├── Tagged @blocked:{BUG-KEY}? ────────────► KNOWN-BLOCKED
  │   (test asserts test.fail('Blocked by {BUG-KEY}') — a deliberately
  │    parked test, not a fresh regression; excluded from gating pass-rate)
  │
  ├── Linked to a known-issue ticket? ───────► KNOWN ISSUE
  │
  ├── Error matches environment pattern? ────► ENVIRONMENT ISSUE
  │   (ECONNREFUSED, ETIMEDOUT, net::ERR_, Navigation timeout,
  │    browserType.launch, 502/503, context deadline exceeded)
  │
  ├── No history (first-ever run)? ──────────► NEW TEST FAILURE
  │
  ├── Failure rate > 20% over last 10 runs? ─► FLAKY
  │
  └── Passed in last ≤ 5 runs, now fails? ───► REGRESSION   (release blocker)

Category	Impact	Action
KNOWN-BLOCKED	LOW	Already tracked by {BUG-KEY} — exclude from gating pass-rate, list in report with the blocking bug key. No new Jira bug (the marker already names the open bug)
REGRESSION	HIGH	Block release, file Jira Bug/Defect (Phase 3 §File defects in Jira, doctrine Part 1), assign
FLAKY	MEDIUM	Schedule stabilization, do not block — no Jira bug
KNOWN ISSUE	LOW	Document against existing ticket, do not block — no new Jira bug
ENVIRONMENT	MEDIUM	Re-run after infra check — no Jira bug
NEW TEST	LOW	Manual verification → if a genuine product defect, file Jira Bug/Defect; else accept or fix

KNOWN-BLOCKED — consuming the blocked-test marker. The @blocked:{BUG-KEY} tag + test.fail('Blocked by {BUG-KEY}') marker is defined in test-automation (references/automation-standards.md §7 Stability; the PROGRESS.md blocked-tests note lives in references/planning-playbook.md) — this skill only consumes it. The GO/NO-GO gate MUST recognize @blocked:{BUG-KEY} tests and classify them as KNOWN-BLOCKED, never REGRESSION: they are deliberately parked behind an already-filed bug, not a fresh failure. Exclude them from the pass-rate that gates the release (see §Compute metrics), and list each in the report under its own heading with the blocking {BUG-KEY}. Do NOT file a new Jira bug — the marker already names the open one.

sdet CI-fallback clause (integration-trunk suites only): an ENVIRONMENT-class red on a Sanity-CI run for a ticket branch may authorize merging into the integration trunk — never the final trunk → main PR — when proven by BOTH (a) the change passing locally on local AND staging, and (b) the same red being present independent of the change (nightly already red, or the failing line is shared pre-existing code). File a separate infra/flake ticket and reference it in the PR. This is NOT a relaxation of the GO bar: a REGRESSION-class failure is never eligible, and the final PR to main still requires a genuinely green test step. See .claude/skills/git-flow-master/references/sdet-integration-trunk.md §CI-fallback clause.

Read references/failure-classification.md when: the decision tree is ambiguous, you need the full error-pattern catalogue, you are classifying a borderline case, or you are computing flakiness over historical runs.

Step 5: Assess severity per failure

Severity is independent of classification. A FLAKY test on the checkout flow is still CRITICAL severity.

Severity	Criteria
CRITICAL	Core user journey (login, checkout, payment). Any @critical tagged test.
HIGH	Major feature (search, profile, dashboard)
MEDIUM	Secondary feature (filters, preferences)
LOW	Edge case or admin-only path

Output of Phase 2

An analysis block with: metrics table, trend delta, one section per failure category (Regressions first, then Flaky, Known, Environment, New), per-failed-test detail (name, ATC ID, suite, error, last-pass date, screenshot link), job summary, and a preliminary verdict.

---

Phase 3 — Report & Decide

GO / CAUTION / NO-GO scoring

Compute a weighted score from the analysis. Maximum is 9.

Factor	+3	+1	0	-1	-2	-3
Pass Rate	≥ 95%	90–95%			< 90%
Regressions	0	1-2 Low		1+ Medium		Any High/Critical
Critical tests	All pass					Any fail
Flaky tests		≤ 3	4-5	> 5

Verdict thresholds:

• Score ≥ 7 → GO — release approved
• Score 4-6 → CAUTION — manual review required, document accepted risks
• Score < 4 → NO-GO — block release, fix regressions, re-run

Never auto-GO if: any @critical test fails, any REGRESSION with HIGH/CRITICAL severity exists, or pass rate < 90%. These are hard vetoes regardless of score.

File defects in Jira (when decision = NO-GO or CAUTION with regressions)

Quality issues go to Jira, not GitHub. A regression-discovered product failure is a defect-management artifact and follows agentic-qa-core/references/defect-management-doctrine.md — the same authority /sprint-testing uses. This skill files the issue IN JIRA with the full mandatory field matrix; it does NOT open a GitHub issue.

Only CONFIRMED real product failures become Jira issues. Use the Phase 2 Step 4 triage as the gate: file in Jira only for the REGRESSION class and for a NEW TEST failure once it is manually confirmed to be a genuine product defect (not a bad assertion). FLAKY, ENVIRONMENT, and KNOWN ISSUE do NOT get a Jira bug — they route to stabilization / infra / the existing ticket as the classification table already prescribes. The failure-triage classification and the defect issue-type are separate axes: triage decides whether to file; the doctrine decides what type and what fields.

For each issue that clears the gate:

1. Classify Bug vs Defect by the affected feature's lifecycle stage, NOT by where the failure ran (doctrine Part 1): the regressed feature is already live above Staging (production / superior env) → Bug; the feature is still pre-release (Staging or below) → Defect. A genuinely new, desirable behavior surfaced beyond the AC → Improvement (Part 1).
2. File it in Jira with the full mandatory field matrix (doctrine Part 5): severity (impact-based) → priority auto-derived (Part 5.1), native components = affected product module (Part 3, mandatory & pre-existing), root_cause + error_type + test_environment, qa_assignee = the authenticated session user (self; never-overwrite, Part 2), and evidence (Allure link + failure screenshots/traces/logs from ./analysis/evidence/).
3. Parent to the QA Defect Management epic — the QA process epic (qa.qa_epics.defect_epic.name), found-or-created; NEVER a product/dev epic (Part 4).
4. Link to the source Story/feature for traceability via the causal link (Part 4) — the regressed ATC's covering Story.
5. Write via acli/REST (doctrine Part 6): create with acli workitem create --from-json (create-time customfields under additionalAttributes.customfield_*, native components:[{name}]); set customfields/components on an existing issue via REST PUT /rest/api/3/issue/{KEY}; qa_assignee is read-before-write. Because this stage may run from CI, load /acli first (it owns auth, syntax, and the REST-PUT pattern in references/acli-integration.md).

Run the doctrine's filing gate (Part 9) before submitting each issue. Save the returned Jira key to reference in the report.

TMS sync (optional, when [TMS_TOOL] is configured via .agents/project.yaml testing.tms_cli)

Prerequisite: Load /xray-cli skill (Modality jira-xray) before executing the [TMS_TOOL] commands below. In Modality jira-native, load /acli instead and map test-execution operations to native Jira issues (see test-documentation/references/jira-setup.md).

The sprint regression maps to two Jira items (items-first by excellence — the Story custom field is never used at this altitude):

• STP (Sprint Test Plan) — a Test Plan item titled STP: Sprint#{N}: Regression (e.g. STP: Sprint#30: Regression). Parents to the QA Master Test Plan epic (qa.qa_epics.master_test_plan_epic.name); relates to the Sprint.
• STR (Sprint Test Results) — a Test Execution item titled STR: Sprint#{N}: Regression Testing (e.g. STR: Sprint#30: Regression Testing). Parents to the QA Test Artifacts epic (qa.qa_epics.test_artifacts_epic.name); relates to the Sprint; testPlan → STP. The run's term is Regression Testing — "Sprint" already comes from the Sprint#{N} scope-id, so the title carries no redundant "Sprint Regression".

The Update Test Execution below targets the STR item.

[TMS_TOOL] Update Test Execution:
  executionKey: {STR execution-key}
  results: {per-ATC status + failure comments from Phase 2}

Write the report

Save to .context/reports/regression-{env}-{date}.md. Use references/failure-classification.md only if you need the pattern catalogue; the report template itself is inline below.

---

Report template

# Regression Quality Report — {env} — {date}

## Executive Summary
**Verdict: {GO / CAUTION / NO-GO}**
Score: {score}/9. {one-line rationale}

| Metric | Value | Threshold | Status |
|--------|-------|-----------|--------|
| Pass Rate | {x}% | >= 95% | {ok/warn/fail} |
| Regressions | {n} | 0 | {ok/warn/fail} |
| Critical failures | {n} | 0 | {ok/warn/fail} |
| Flaky | {n} | <= 3 | {ok/warn/fail} |
| Duration | {d} | - | - |

## Release Blockers
{if NO-GO, enumerate regressions with severity, owner, ETA. Otherwise: "None."}

## Failure Details
### Regressions ({n})
  - {test} | {atc_id} | last passed {date} | [issue]({url}) | probable cause: {...}

### Flaky ({n}) — schedule stabilization
### Known Issues ({n}) — accepted
### Known-Blocked ({n}) — excluded from gating pass-rate
  - {test} | {atc_id} | blocked by [{BUG-KEY}]({url})
### Environment ({n}) — re-run after infra check

## Trend (last 5 runs)
{ASCII sparkline or pass-rate table}

## Links
- Workflow run: {url}
- Allure: {url}
- Created issues: {list}
- TMS execution: {key / url}

## Recommendations
1. Immediate (pre-release): {...}
2. Short-term (this sprint): {...}
3. Long-term (tech debt): {...}

Post-decision actions

Decision	Actions
GO	Mark release candidate approved; schedule post-deploy smoke
CAUTION	Review with team lead; document accepted risks; proceed deliberately
NO-GO	Block release; assign regression issues; schedule fix verification; plan re-run

Per-phase progress + Archive

After Phase 1 Monitor returns, after each Phase 2 step (Collect / Parse / Compute / Classify / Severity), and after Phase 3 Verdict, the orchestrator appends a phase entry to .session/regression-testing/<scope>/progress.md per agentic-qa-core/references/session-management.md §7. artifacts_touched records the downloaded CI artifacts (allure / evidence / playwright dirs) + the final .context/reports/regression-<env>-<date>.md.

After the Verdict emits, the orchestrator runs Archive per agentic-qa-core/references/session-management.md §8: moves .session/regression-testing/<scope>/ to .session/.archive/<YYYY-MM-DD>-regression-testing-<scope>/ (two-file dir preserved) and calls mem_session_summary with the archive path. The canonical .context/reports/regression-<env>-<date>.md stays in the reports dir as the committed deliverable.

On Verdict = NO-GO with regressions still being filed as issues, archive WAITS until the issue-creation step completes (so the session state still references the open issue list at archive time).

---

Gotchas

• Allure URL is predictable but only live after the "Build & Deploy Allure Report" job succeeds. If that job failed, the URL 404s — analyze from downloaded artifacts instead.
• gh run watch can time out on long suites. Fall back to polling gh run view <RUN_ID> --json status every 60-90 seconds.
• gh run view --log dumps every step's output and is often >50MB on large suites. Always prefer --log-failed during analysis; use --job=<JOB_ID> --log for targeted drilldown.
• Retries mask flakiness. Playwright is configured with retries: 2 in CI. A test that passes on retry is still flaky — inspect retries count in Allure, not just final status.
• ENVIRONMENT is not a scapegoat. ECONNREFUSED to your app's own API probably means the app crashed, not "infra glitch". Check if the same run has many unrelated tests failing on the same host — that is environment. One test failing with a network error on an endpoint that other tests hit successfully is more likely a REGRESSION.
• Never mark NEW TEST as REGRESSION. A first-ever failure with no history is not a regression — it is unverified. Manually confirm once before classifying.
• Flakiness needs 10 runs of history minimum. If you don't have 10 runs, mark it as "insufficient history" and re-evaluate next sprint. Do not guess.
• Sanity + grep and test_file are mutually exclusive. Passing both makes the workflow ignore one silently. Pick one.
• Video recording inflates artifact size by 5-10x. Only enable video_record=true when debugging flakiness or capturing bug evidence. Never enable it for nightly regression.
• CI credentials come from GitHub secrets, not .env. Do not copy values from local .env into workflow YAML — reference ${{ secrets.NAME }} only.
• Session-footer contract (mandatory at close). The final phase is not done until the two chat-facing blocks from ../agentic-qa-core/references/session-footer-contract.md are printed: (1) consolidated screenshot list — repo-relative paths, verified on disk, bug annotations first — plus in-flow surfacing of every capture's path the instant it lands; (2) Session Footer listing skills/MCPs/CLIs actually used + testing levels touched, with explicit "none" entries for expected-but-untouched levels. Framing for this skill: execution. Multi-subagent sessions: each stage report carries the five footer fields (skills_loaded, mcps_used, clis_used, testing_levels_touched, screenshots_captured); the orchestrator compiles the footer ONCE at close. Chat only — never in a Jira comment or ATR body.

---

Specific tasks

• Configuring or debugging GitHub Actions workflows — read references/ci-cd-integration.md
• Enabling GitHub Pages so the published Allure reports are browsable ("set up GitHub Pages", "report URL is 404", "publish the reports site") — read references/github-pages-setup.md (enable via gh api, first-build stuck/errored gotcha + manual rebuild, gh-pages history squash job). Run the §Allure version-currency check first.
• Making CI reports PRIVATE ("reports must be login-protected", "no publiques evidencia pública", "protege los reportes") — read references/private-hosting-setup.md (Test Report Portal: Vercel + Supabase + private R2, work-email login, portal-side retention, history round-trip replacing gh-pages). The publish step in all three suite workflows is already dual-mode — you only wire secrets. GitHub Enterprise orgs have a zero-infra shortcut (Pages visibility → Private); offer it first.
• Setting up Allure locally for the first time, or the user asks "is Allure up to date?" — run the §Allure version-currency check under §Local reporting.
• Classifying a borderline failure (REGRESSION vs FLAKY vs ENVIRONMENT) — read references/failure-classification.md
• TMS / Xray result import — load /xray-cli skill
• Downloading traces or screenshots for a failure — use [AUTOMATION_TOOL] per CLAUDE.md Tool Resolution; for Playwright trace inspection load /playwright-cli
• Session contract (Phase 0 resume, plan.md/progress.md schemas, archive policy, Engram per-phase checkpoint, RUN_ID re-attach mechanism) — read ../agentic-qa-core/references/session-management.md. This skill is a producer of session/regression-testing/<scope>/... topic keys.

---

Anti-patterns — NEVER do these

• R1. NEVER classify a failure as FLAKY without re-running the test in isolation — masks real regressions.
• R2. NEVER emit GO when known REGRESSION class > 0 — quality gate is binary: regressions block.
• R3. NEVER auto-retry failing tests in CI without surfacing the retry count in the report.
• R4. NEVER skip Allure artifact download on red builds — evidence vanishes after the retention window.
• R5. NEVER trigger a regression workflow without --ref <commit-sha> pinned — different commit = different baseline.
• R6. NEVER mix smoke + regression suite results into one pass-rate number — different SLOs.
• R7. NEVER mark a test KNOWN-failure without a Jira ticket linking the suppression to a tracking issue.

---

Quick reference

# Trigger + get run ID in one shot
gh workflow run regression.yml -f environment=staging && sleep 5 && \
  RUN_ID=$(gh run list --workflow=regression.yml --limit=1 --json databaseId -q '.[0].databaseId') && \
  echo "RUN_ID=$RUN_ID"

# Wait for completion
gh run watch $RUN_ID

# Failed logs only
gh run view $RUN_ID --log-failed

# All failure evidence
gh run download $RUN_ID -n e2e-failure-evidence -D ./analysis/evidence/

# Previous run for trend
PREV=$(gh run list --workflow=regression.yml --limit=2 --json databaseId -q '.[1].databaseId')
gh run download $PREV -n merged-allure-results-staging -D ./analysis/previous/