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post-mortem-author

Build-an-X workflow that produces a blameless post-mortem from an incident - captures the timeline (chronological event sequence with sources), root cause analysis (what + why, not who), impact (users / revenue / SLO debt), action items (with owners + due dates + measurable success criteria), and "what went well" (intentional). Per Google SRE: "Blameless postmortems are a tenet of SRE culture." Use after every user-visible incident, not just severe ones.

Install with skills.sh (any agent)

npx skills add testland/qa --skill post-mortem-author
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post-mortem-author

Overview

Per google-sre-postmortem (opens in new window):

"A postmortem is 'a written record of an incident, its impact, the actions taken to mitigate or resolve it, the root cause(s), and the follow-up actions to prevent the incident from recurring.'"

"Blameless postmortems are a tenet of SRE culture." (google-sre-postmortem (opens in new window))

"Writing a postmortem is not punishment - it is a learning opportunity for the entire company." (google-sre-postmortem (opens in new window))

The blameless framing is load-bearing. Per google-sre-postmortem (opens in new window), the document must "focus on identifying the contributing causes of the incident without indicting any individual or team for bad or inappropriate behavior" - assuming "everyone involved in an incident had good intentions and did the right thing with the information they had."

When to use

Per google-sre-postmortem (opens in new window), common triggers include:

"user-visible downtime, data loss, on-call interventions, extended resolution times, and monitoring failures."

Author a post-mortem after every such incident - not just sev-1. Lower-severity incidents accumulate context that prevents the sev-1.

Step 1 - Author the document

Copy the full section skeleton from references/post-mortem-document-template.md and fill every section. The required sections, in order:

  1. Header - status, severity, authors, dates, reviewers.
  2. Summary - 2-3 sentences: what, who, how long, what was done.
  3. Impact - users affected, revenue (deferred vs lost), SLO debt, reputational.
  4. Timeline - chronological events with UTC timestamps and a source per row.
  5. Root cause - what happened in detail, with the system as the subject, never a person.
  6. Contributing factors - every condition that allowed the incident; list all, since incidents rarely have one cause.
  7. What went well - the positives; per google-sre-postmortem (opens in new window), post-mortems should call these out too.
  8. Action items - the load-bearing section (Step 3).
  9. Lessons learned and Postmortem trigger - what is known now, and which trigger criteria the incident met.

The worked example below fills this skeleton for a real SEV-2.

Step 2 - Blameless review

Per google-sre-postmortem (opens in new window): "Postmortems are not punishment."

Reviewers should:

  • Reject blame language. "Bob deployed without testing" → "The pre-deploy testing didn't cover the null-metadata case."
  • Focus on systems, not individuals. "Why did Bob fix this fast?" → "What enabled fast diagnosis? (Sentry stack trace + the team's incident-response training.)"
  • Surface contributing factors openly. Multiple factors usually contribute; document all.

Step 3 - Action item discipline

Action items must have:

  • Owner (one named person; not "the team").
  • Due date (concrete; not "next sprint when we have time").
  • Priority (P0/P1/P2/P3; ties to the action's importance).
  • Success criterion (measurable; "X done" not "we'll think about X").

The action items are the post-mortem's value. Without them, the document is paperwork.

Step 4 - Approval + closure

The post-mortem isn't "done" until:

  1. Reviewers (eng manager, SRE lead, Product) sign off.
  2. Action items are added to the team's tracker (Jira / Linear / GitHub issues).
  3. P1/P2 action items have a target completion before the next release.

The post-mortem is "closed" when all action items ship - typically 2-4 weeks. A 6-month-old open post-mortem is a process failure.

Step 5 - Storage

docs/postmortems/
├── INC-1234-stripe-webhook-2026-05-04.md
├── INC-1235-cache-invalidation-2026-05-12.md
├── INC-summary-2026-Q2.md       ← rollup
└── README.md

Markdown + git. Quarterly rollup identifies patterns:

## Q2 2026 incident summary

**Total incidents:** 12
**SEV-1:** 1
**SEV-2:** 6
**SEV-3:** 5

**Patterns:**
- 4 of 12 (33%) were "test gap" - the failing condition wasn't
  in the test suite. Action: invest in
  test-coverage-targeter
  + property-based testing.
- 3 of 12 (25%) involved canary metrics; 2 of those proceeded
  through canary gate. Action: review thresholds (per AI-2 from
  INC-1234).
- ...

Worked example - INC-1234 Stripe webhook failure (SEV-2)

The skeleton from Step 1, filled for a real incident.

Summary. A v1.4.5 deploy introduced a null-metadata crash in the Stripe webhook handler; ~12,400 customers (4.3% of MAU) hit failed checkout completions for 23 minutes until rollback.

Impact. ~$140,000 in delayed (not lost) orders; 32% of the monthly availability budget burned; 47 support tickets.

Timeline (excerpt).

Time (UTC)EventSource
14:00Deploy of v1.4.5 to canary (5% traffic)CD pipeline log
14:23First Sentry alert: NullPointerException at WebhookHandler:42Sentry
14:30Canary window ends within thresholds; promoted to 100%CD pipeline
14:42PagerDuty SLO burn-rate alert; incident declared SEV-2PagerDuty
14:58Rollback complete; error rate returning to baselineDatadog

Root cause (what, not who). The v1.4.5 handler added a path for Stripe's payment_intent.partially_funded event that called payment.metadata.get("internal_id"); for ~3% of events metadata was null, the exception was uncaught, the handler returned 500, and Stripe stopped retrying, so fulfillment never triggered. The canary stage saw the error rate rise (0.4% vs 0.3% baseline) but stayed under the 1.5x rollback threshold, so prod-canary-validator returned PROCEED with WARNING and the gate was acked.

Contributing factors. (1) test gap - no unit test for the null-metadata case; (2) canary threshold too lenient for a low baseline; (3) staging carries almost no Stripe webhook traffic, so the new event type was never exercised pre-deploy.

Action items.

IDActionOwnerPriorityDueSuccess criterion
AI-1Unit test for partially_funded with null metadataBobP12 daysTest in WebhookHandlerTest.kt fails against the bug, passes after
AI-2Tighten canary error-rate threshold 1.5x -> 1.3xSREP21 sprintcanary-thresholds.yml updated; one normal canary passes
AI-3Staging fixture covering all Stripe event typesBobP21 sprintStaging "events by type" metric shows all types > 0

What went well. Sentry caught the regression at 14:23, well before the PagerDuty page; rollback finished in 7 minutes, inside RTO. Diagnosis came from the Sentry stack trace alone, with no production debugging.

Anti-patterns

Anti-patternWhy it failsFix
Blame languageDefeats the blameless principle; team stops authoring post-mortems honestly.Per Google SRE: focus on contributing causes, not individuals (Step 2).
Action items without owner / due dateNobody acts; same incident recurs.All four fields required (Step 3).
Skipping post-mortems for "small" incidentsLower-severity context that prevents big incidents is missed.Author per google-sre-postmortem (opens in new window) trigger criteria (Step 1).
Post-mortem stored in private docsOrg learning capped at the team.Public to org (per Google SRE pattern).
One-shot post-mortem with no follow-up"Closed" but action items stale; recurrence likely.Track action items in tracker (Step 4); post-mortem closed only when all done.
Post-mortem authored 2+ weeks after incidentMemory faded; details lost.Author within 5 business days.

Limitations

  • Honesty depends on culture. A team that fears blame will produce sanitized post-mortems. Leadership must reinforce blamelessness in word and action.
  • Post-mortems don't prevent the next incident. They prevent the same class of incident. Pair with proactive practices (chaos testing, threat modeling).
  • Time investment. A SEV-2 post-mortem typically takes 4-8 hours to author + 2-4 hours of review. Budget accordingly.

References

  • gsp (opens in new window) - Google SRE blameless post-mortem definition, triggers, blamelessness principle, learning-opportunity framing.
  • prod-canary-validator - sibling: canary verdict; post-mortems often surface threshold tuning needs.

Post-mortem document template

View source (opens in new window)

Post-mortem document template

Deep reference for the post-mortem-author SKILL.md. The full per-incident section skeleton to copy when authoring a blameless post-mortem. Fill every section; the Action items table is load-bearing - a post-mortem without owned, dated, measurable action items is paperwork.

Store one markdown file per incident under a stable directory (for example docs/postmortems/) with an incident-ID-and-date filename.

# Post-mortem - `INC-XXXX` - <one-line title>

**Status:** Draft | Review | Approved | Action items closed
**Severity:** SEV-n
**Authors:** <incident commander>, <lead investigator>
**Date authored:** YYYY-MM-DD   **Incident date:** YYYY-MM-DD
**Reviewers:** <eng manager>, <SRE lead>, <product>

## Summary
2-3 sentences: what happened, who was affected, how long, what was done.

## Impact
- **Users affected:** count and % of MAU.
- **Revenue impact:** amount (state deferred vs lost).
- **SLO debt:** % of the monthly availability budget burned.
- **Reputational:** support tickets, social reach.

## Timeline
Chronological events, one row each, with a UTC timestamp and a source link.

| Time (UTC) | Event | Source |
|------------|-------|--------|
| ... | ... | ... |

## Root cause
What happened, in detail. Not who. The system is the grammatical subject.

## Contributing factors
Every condition that allowed the incident (test gap, threshold too lenient,
missing staging traffic, ...). List all; incidents rarely have a single cause.

## What went well
The positives - what mitigated faster than expected. Per
[Google SRE, Postmortem Culture](https://sre.google/sre-book/postmortem-culture/),
post-mortems should call these out too.

## Action items
| ID | Action | Owner | Priority | Due | Success criterion |
|----|--------|-------|----------|-----|-------------------|
| AI-1 | ... | one named person | P0-P3 | concrete date | measurable "done" condition |

## Lessons learned
What the team knows now that it did not before.

## Postmortem trigger
Which trigger criteria this incident met (user-visible, duration, revenue, SLO).

Two fields carry the most weight. Root cause must read as a property of the system, never of a person. Action items must each have one named owner, a concrete due date, a priority, and a measurable success criterion; without all four the item does not get acted on and the same incident recurs.

Related skills

attack-surface-test-checklist

Maps a code change to the security tests worth running against it. Classifies changed paths and file contents into nine attack surfaces (authentication, session management, input handling, file upload, deserialization, access control, API and web service, cryptography, data protection), attaches the matching OWASP ASVS 4.0.3 verification requirements, OWASP Top 10 2021 category IDs, and OWASP WSTG section numbers to each active surface, then emits a per-surface manual and automated test checklist bounded by what actually changed. Surfaces with no changed lines are excluded rather than carried as filler. Use when a pull request, release branch, or feature is about to be security tested and the team needs a targeted test list instead of a generic application-wide checklist.

code-change-shape-classifier

Classifies a code change set into four shapes (pure-logic, service-layer, ui-heavy, data-heavy) from file-path and file-content signals, computes the shape distribution over a window of git history, and attaches a relative per-layer test cost model (unit 1x, service 3x, UI 10x) so downstream planning works from one shared input. Produces the classification only: it does not prescribe a target unit:service:UI ratio, does not estimate hours, and does not select which tests to run. Use when a pull request, release branch, or epic needs its change shape labelled before test effort, pyramid balance, or coverage depth is decided.

definition-of-done

Pure-reference + checklist-generator for the team's Definition of Done (DoD) - explains the Scrum Guide's DoD definition ("a formal description of the state of the Increment when it meets the quality measures required for the product"), proposes a starter DoD with the 7-10 lines most teams need (code reviewed, unit tests, docs, AC met, deployed to staging, smoke passed, no a11y regressions, telemetry wired, observability in place), and emits a per-PR checklist a reviewer enforces. Use when the team doesn't have a DoD or wants to revise theirs.

dod-adherence-review

Audits an existing Definition of Done checklist line by line against repository evidence (review records, diffs, CI runs, coverage reports, scan output) and tags every line met, not met, or unverifiable, refusing to pass a line on self-attestation or on a claim with no matching diff. Covers the line-pattern-to-evidence mapping for the common checklist shapes (code reviewed, coverage threshold, docs updated, acceptance criteria covered, staging deploy plus smoke, no new accessibility regressions, telemetry wired), the entry-stage versus exit-stage split many teams run, the roll-up verdict rules, and the audit table that gets emitted. Does not author, revise, or soften the checklist. Use when a story or pull request is about to be marked done and a committed Definition of Done exists that nobody has actually checked the work against.

e2e-suite-budget

Caps E2E suite size by computing per-test ROI - (regressions caught × value) ÷ (runtime × flake rate × maintenance) - then ranks every end-to-end test and recommends which bottom-decile ones to retire, move to a lower layer, or fix. Use when CI is slow or E2E-dominated, flaky failures are rising, or quarterly to keep suite size within maintenance capacity. For strategic unit:service:UI layer ratios use test-pyramid-balancer, for the minimal per-deploy critical-path gate use smoke-suite-gate, and for quarantining flaky tests use flaky-test-quarantine; this prunes low-signal tests by ROI.

framework-choice-advisor

Pure reference catalog for picking a test automation framework - covers Playwright / Cypress / Selenium / WebdriverIO / Appium / Espresso / XCUITest / RestAssured / Karate / k6 / Locust with side-by-side tradeoffs on speed, cross-browser, mobile, parallelisation, language support, ecosystem maturity, CI integration; a decision tree for matching project NFRs to framework choice; and reference directory / fixture / CI layouts for the chosen stack. This is the **upstream selection step**: it decides which tool to adopt, not how to configure a tool already chosen, and not how to rebalance the unit / integration / E2E mix of an existing suite. Use when starting a new test-automation suite from scratch, before installing any tool.

heuristic-test-design-reference

Reference catalog of the four canonical heuristic test-design models - Bach's Heuristic Test Strategy Model (HTSM) with SFDPOT product elements, Whittaker's 'How to Break Software' attack patterns, Bolton's FEW HICCUPPS consistency oracles, and the ISO/IEC 25010 quality characteristics - for use when the tester has no user story, no acceptance criteria, and no documentation. This is the zero-documentation case: it does not read from a written story, and it yields test-case ideas rather than session charters. Use as the reference layer when generating coverage for a feature with no documented input.

product-risk-register-builder

Build-an-X workflow that produces a product-level risk register catalogue - per-feature / per-component product risks (functionality, performance, security, usability, compatibility, reliability) that persist across releases, distinct from per-release risk matrices. Walks the author through risk identification by ISO 25010 quality characteristic, scoring per impact × likelihood, and linking each register entry to mitigations + owners + review cadence. Output is a Markdown register the team reviews quarterly and that seeds release-level risk matrices. Use for long-lived product-quality risks; complements risk-matrix for per-release risks.

project-risk-register-builder

Build-an-X workflow producing a project-level risk register - risks to project execution (schedule slippage, environment instability, people / staffing, vendor / dependency, scope creep) rather than the product itself. Walks the author through ISO 31000-aligned identification, impact × likelihood scoring, mitigation strategy (avoid / mitigate / transfer / accept), and ownership; the project manager reviews it weekly. Use for release-execution risk. For product-quality risks use product-risk-register-builder, for the per-release product risk table use risk-matrix, and to sign off accepting one specific risk use risk-acceptance-decision-author.

qa-okr-author

Build-an-X workflow that drafts a QA team's quarterly OKR set - one to three Objectives, each with 3 - 5 measurable Key Results - from the team's current state (risk matrix, defect-trend narrative, test-run history, test-pyramid balance, compliance coverage). Every numeric target cites its source artifact (e.g., a defect-trend baseline's 2026-Q1 escape rate). QA-specific by design - generic OKR generators (Tability, Asana, ClickUp) don't know test metrics; the differentiation is the domain. Produces the OKR set itself - not the test-strategy document it sits inside, and not the risk-score calibration behind the baselines. Use at the start of each quarter to draft the OKR set the manager edits and the team commits to.

qa-vendor-evaluator

Build-an-X workflow that produces a side-by-side **commercial-vendor** evaluation matrix for QA tools - test-management platforms (TestRail / Qase / Xray / Zephyr / TestCollab), no-code platforms (mabl / Testim / Functionize / TestSigma / Reflect), visual regression services (Applitools / Percy / Chromatic), and commercial AI copilots - scoring each on capability fit, cost model, integration depth, vendor lock-in risk, exit cost, contractual posture, and customer-reference data. Scoped to commercial procurement - contract, lock-in, and exit-cost axes - not to choosing an open-source code-first framework on architectural fit. Use for commercial procurement decisions only - refuses to recommend a winner; the team owns the procurement choice.

risk-acceptance-decision-author

Build-an-X workflow that produces a structured risk-acceptance decision document - for risks the team has decided to accept (rather than mitigate / transfer / avoid). Walks the author through the ISO 31000 risk-acceptance criteria (rationale, sign-off, scope, review trigger, exit conditions), captures stakeholder approval, and links to the originating risk register entry. Output is a Markdown decision artefact that lives alongside the risk register and provides audit-defensible justification for the team's acceptance choice. Use when a risk register entry's Strategy column is set to Accept, or an already-accepted risk comes up for its scheduled re-review, an audit, or a post-incident look-back.

risk-coverage-mapper

Build-an-X workflow that produces a risk-to-test-coverage matrix - maps each risk in the product/release register to the tests / cases / monitoring that mitigate it. Walks the author through ingesting risks (from risk-matrix / product-risk-register-builder), inventorying test coverage (test cases via traceability-matrix-builder, automated tests via repo scan, production monitoring via observability dashboards), and computing per-risk coverage depth + identifying orphan risks (no coverage) + orphan tests (not linked to risks). Output is a Markdown matrix + executive summary. Use before a release sign-off or compliance audit, when the team must show which tests, cases, or monitors back each registered risk and which risks have nothing behind them.

risk-matrix

Produces the per-feature / per-release risk-matrix artifact itself: a structured intake (feature, category, impact 1-5 by likelihood 1-5, score), mitigations with owners and due dates, supporting both lightweight (impact by likelihood) and heavyweight (FMEA / Cost of Exposure) methods per RBT canon, output as a Markdown / spreadsheet the team reviews each sprint. Use when building the matrix artifact; to facilitate the live risk-storming meeting use risk-storming-facilitator, to calibrate scores across raters use risk-matrix-calibration, and to map the resulting risks onto test coverage use risk-coverage-mapper.

risk-matrix-calibration

Checks an already-written risk matrix against what actually happened. Maps each row's likelihood rating to observed defect density, test failure rate and code churn, maps its impact rating to the severity mix and escape rate, then classifies each row as over-stated, under-stated, in-agreement, or not calibrated, using stated reporting thresholds so small differences are not treated as findings. Every proposed rating change carries the observation that produced it, and every proposal is handed to the matrix owner rather than applied. Also emits candidate new entries for areas that show up in defect data but have no row. Owns calibration only: choosing a scoring methodology, designing the matrix structure, picking risk categories, mapping risks to test types, FMEA scoring, review cadence and file storage are all out of scope. Use when a matrix has been driving test decisions for at least three releases and nobody has yet checked whether its ratings match the defects, escapes and incidents that followed.

risk-storming-facilitator

Reference guide for planning and facilitating a risk-storming session yourself - meeting structure, participant roster, per-category brainstorm prompts (categories from risk-matrix), affinity grouping, impact by likelihood scoring, and mitigation assignment. Static reference only, not an active runner that writes the matrix file. Use to learn or teach the facilitation pattern, or to run a feature-kickoff session without agent assistance. For the matrix artifact itself use risk-matrix, to calibrate its ratings against real defect data use risk-matrix-calibration, and to map the resulting risks onto test coverage use risk-coverage-mapper.

smoke-suite-gate

Build-an-X workflow for a critical-path smoke suite that runs in <5 minutes - picks the 5-15 highest-business-value journeys (login, hero flow, checkout, payment, primary read), implements as fast E2E or API tests, gates per-deploy, retries on transient failures with quarantine. Use as the canary-precursor or per-deploy verification gate; the team's "if this fails, the build can't proceed" floor.

tdd-stuck-pattern-resolver

Pattern catalog for "I can't write the test first" moments - recognizes common testability blockers (singletons / static dependencies, network in constructors, time / random as hidden inputs, deeply nested construction, untestable boundaries) and proposes the refactor that unblocks TDD (extract interface, dependency injection, seam, ports-and-adapters). Use as TDD coaching when an engineer is stuck on a class of code. For a catalog of what-to-test heuristics with no story use heuristic-test-design-reference, to label a change's shape before planning test effort use code-change-shape-classifier, and for conventions on writing the test well once the code is testable use test-code-conventions.

test-case-from-live-feature

Build-an-X workflow that produces a test-case matrix from a **live, undocumented feature** - running app at a URL, screen recording, screenshot, or verbal brief - by combining structured exploration (Playwright trace / DevTools / accessibility tree) with the heuristic models in `heuristic-test-design-reference` (SFDPOT, Whittaker attacks, FEW HICCUPPS, ISO 25010). Output is a structured case matrix, not an exploratory session charter. Use when there is no story, no AC, and no documentation - only a live feature.

test-case-ideation-from-story

Takes a user story or feature spec and emits a markdown test-case matrix - one row per case (id, title, precondition, steps, expected, tier) covering happy path, alternate paths, boundaries, and negative paths - before any test code is written. Output is the human-reviewable matrix that goes into TestRail / Qase / Xray. Emits the human-reviewable case matrix itself - not Gherkin scenarios written against locked acceptance criteria, and not executable test code. Use as the first artifact a manual tester or three-amigos session produces from a story, ahead of automation.

test-effort-estimation

Turns a list of testable areas plus a change-shape distribution into a PERT three-point test effort estimate, reporting every row as a range around the expected value rather than a single number, requiring a named assumptions ledger across six mandatory categories, and recommending a per-layer ownership split across developer, automation, and exploratory roles. Owns the hours and the ownership recommendation only: it consumes a change-shape distribution rather than producing one, and it does not choose which tests to run or how deep coverage should go. Use when an epic or release has been broken into testable areas and someone is about to commit test capacity for a sprint.

test-pyramid-balancer

Build-an-X workflow that analyzes a repo's test mix (unit / integration / E2E counts + runtimes) and recommends rebalancing toward the test pyramid ratios per the change-set shape - pure-logic-heavy repo wants ~80/15/5; UI-heavy repo wants ~60/25/15. Detects 'ice-cream cone' (E2E-heavy) and 'hourglass' (integration-thin) anti-patterns. Use when the user asks about test distribution, test strategy, test balance, too many E2E tests, slow CI caused by tests, testing best practices, or rebalancing their test suite; also suitable for quarterly calibration of the test mix to codebase reality.

test-strategy-author

Authors a test strategy document (a master test plan) for a project, release, or feature - covers scope, in/out, test types per layer (unit / integration / contract / E2E / perf / security / a11y), risk-based test prioritization that maps top risks to test investment (per `risk-matrix`), tooling stack, environments, exit criteria, and ownership. Use when a team needs the release-readiness artifact stakeholders sign off on before significant test investment, and the reference engineering teams return to when scope or quality questions arise.

tool-selection-decision-record

Defines the output contract for writing down a chosen developer tool as a portable decision record: the observed project signal, exactly one primary recommendation, rationale that names the rejected alternative, what to read next, and a mandatory list of the conditions that would flip the choice. Adapts Architecture Decision Record conventions (context, decision, consequences, status, supersede rather than edit) to tool selection, and refuses any recommendation inferred from a README or a folder name instead of a manifest, lockfile, config file, or existing test directory. Distinct from a catalog or advisor that compares candidate tools on their merits: this owns the shape of the written record, not the comparison. Use when a tool has just been chosen (test framework, build tool, linter, package manager, migration tool) and the choice needs to be recorded so a later reader can see the signal, the rejected alternative, and what would reverse it.