Review an executed business decision against its original success and stopping criteria. Compare actual results, revisit assumptions and dissenting views, and create a retrospective record with lessons and follow-up actions.
/cs:post-mortem <decision> — Honest retrospective on an executed decision, scored against original assumptions and dissent. Closes the strategic sprint loop. Use when a decision hits its 90-day review checkpoint or its kill criteria trigger — e.g. scoring last quarter's pricing change against its pre-committed success metrics.
Review the instructions the agent will receive before you install.
Command: /cs:post-mortem <decision-path>
Closes the strategic sprint loop. Scores a decision against the success and kill criteria written before the decision (not retro-fitted) and revisits the preserved dissent. This is the rigor that compounds over time.
/cs:office-hours → /cs:brief → /cs:boardroom → /cs:decide → /cs:execute → /cs:post-mortem
↑ you are here
/cs:decide)/cs:decide)/cs:execute)Saved to ~/.claude/postmortems/YYYY-MM-DD-<slug>.md:
# Post-Mortem: <decision title>
**Decision date:** YYYY-MM-DD
**Post-mortem date:** YYYY-MM-DD
**Status:** WIN / PARTIAL / LOSS / MIXED
## Outcome Scoring (against pre-committed criteria)
| Success Criterion | Threshold | Actual | Met? |
|---|---|---|---|
| <metric 1> | <threshold> | <actual> | ✅ / ❌ |
| <metric 2> | <threshold> | <actual> | ✅ / ❌ |
| Kill Criterion | Threshold | Actual | Triggered? |
|---|---|---|---|
| <metric> | <threshold> | <actual> | ✅ / ❌ |
**Overall:** WIN / PARTIAL / LOSS / MIXED
## What We Got Right
- <factor 1>
- <factor 2>
## What We Got Wrong
- <factor 1>
- <factor 2>
## Preserved Dissent — Revisited
[Original dissent from the boardroom memo, scored:]
- **<dissenter>:** <original concern>
- **Did it materialize?** YES / NO / PARTIAL
- **Cost if YES:** <quantified impact>
- **Lesson:** <one sentence>
## Assumption Audit
[Original brief's assumptions, scored:]
- **Assumption 1:** <text>
- **Held?** YES / NO / PARTIAL
- **Why:** <explanation>
## Process Lessons
- **Phase 2 isolation worked?** YES / NO
- **Devil's advocate concerns played out?** YES / NO / PARTIAL
- **Cadence was right?** YES / TOO LOOSE / TOO TIGHT
## Forward Actions
- [ ] <change to operating system or routing logic>
- [ ] <new decision to make based on this learning>
- [ ] <update company-context.md>
## Status
- WIN → archive, log lesson
- LOSS → schedule follow-up boardroom: `/cs:brief` for the next call
The biggest temptation in post-mortems is retroactive justification: "we always knew X, that's why we did Y." Pre-committed criteria, signed at /cs:decide time, eliminate that move. The numbers either matched or they didn't.
The dissent column from /cs:boardroom is the single most useful piece of organizational memory. Most of the time, the dissenter was directionally right. Revisiting and scoring it builds calibration over years.
/cs:brief — if the post-mortem surfaces a new decision/cs:freeze — if the post-mortem reveals a process gap that needs cooldown enforcementcs-onboarddecision-loggercs-chief-of-staff/em:postmortem — adversarial single-decision post-mortemVersion: 1.0.0
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Audit web applications for accessibility issues against WCAG 2.2 Level A and AA, the web accessibility standards. Get framework-specific code fixes, contrast checks, verification steps, and reports, with options for automated checks in development pipelines.
Plan A/B tests that compare page variations, from headlines to pricing layouts. Define a hypothesis, choose success metrics, calculate sample size and duration, and prepare launch checks and results reports to support decisions.
Create paid ad headlines and body copy tailored to each platform's character limits. Use existing performance data to develop variations, explore new messaging angles, and check copy for length, quality, and potential rejection risks.
Review code changes from three critical perspectives: production failures, maintainability, and security. Get a consolidated report that ranks findings by severity and provides merge guidance, helping examine assumptions that an ordinary self-review may overlook.
Audit and improve content intended for citation in AI answers. Review evidence, author information, and structure, generate revised content and structured metadata, and keep a local record of observed citations across AI services.
Create signed records for consequential agent actions such as deployments, deletions, and payments. Decide which actions need evidence, record the agent, action, target, and policy, then verify the resulting certificate offline to detect later changes.