premortem▌
parcadei/continuous-claude-v3 · updated Jun 4, 2026
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Identify failure modes before they occur by systematically questioning plans, designs, and implementations. Based on Gary Klein's technique, popularized by Shreyas Doshi (Stripe).
Pre-Mortem
Identify failure modes before they occur by systematically questioning plans, designs, and implementations. Based on Gary Klein's technique, popularized by Shreyas Doshi (Stripe).
Usage
/premortem # Auto-detect context, choose depth
/premortem quick # Force quick analysis (plans, PRs)
/premortem deep # Force deep analysis (before implementation)
/premortem <file> # Analyze specific plan or code
Core Concept
"Imagine it's 3 months from now and this project has failed spectacularly. Why did it fail?"
Risk Categories (Shreyas Framework)
| Category | Symbol | Meaning |
|---|---|---|
| Tiger | [TIGER] |
Clear threat that will hurt us if not addressed |
| Paper Tiger | [PAPER] |
Looks threatening but probably fine |
| Elephant | [ELEPHANT] |
Thing nobody wants to talk about |
CRITICAL: Verify Before Flagging
Do NOT flag risks based on pattern-matching alone. Every potential tiger MUST go through verification.
The False Positive Problem
Common mistakes that create false tigers:
- Seeing a hardcoded path without checking for
if exists():fallback - Finding missing feature X without asking "is X in scope?"
- Flagging code at line N without reading lines N±20 for context
- Assuming error case isn't handled without tracing the code
Verification Checklist (REQUIRED)
Before flagging ANY tiger, verify:
potential_finding:
what: "Hardcoded path at line 42"
verification:
context_read: true # Did I read ±20 lines around the finding?
fallback_check: true # Is there try/except, if exists(), or else branch?
scope_check: true # Is this even in scope for this code?
dev_only_check: true # Is this in __main__, tests/, or dev-only code?
result: tiger | paper_tiger | false_alarm
If ANY verification check is "no" or "unknown", DO NOT flag as tiger.
Required Evidence Format
Every tiger MUST include:
tiger:
risk: "<description>"
location: "file.py:42"
severity: high|medium
# REQUIRED - what mitigation was checked and NOT found:
mitigation_checked: "No exists() check, no try/except, no fallback branch"
If you cannot fill in mitigation_checked with specific evidence, it's not a verified tiger.
Workflow
Step 1: Detect Context & Depth
# Auto-detect based on context
if in_plan_creation:
depth = "quick" # Localized scope
elif before_implementation:
depth = "deep" # Global scope
elif pr_review:
depth = "quick" # Localized scope
else:
# Ask user
AskUserQuestion(
question="What depth of pre-mortem analysis?",
header="Depth",
options=[
{"label": "Quick (2-3 min)", "description": "Plans, PRs, localized changes"},
{"label": "Deep (5-10 min)", "description": "Before implementation, global scope"}
]
)
Step 2: Run Appropriate Checklist
Quick Checklist (Plans, PRs)
Run through these mentally, note any that apply:
Core Questions:
- What's the single biggest thing that could go wrong?
- Any external dependencies that could fail?
- Is rollback possible if this breaks?
- Edge cases not covered in tests?
- Unclear requirements that could cause rework?
Output Format:
premortem:
mode: quick
context: "<plan/PR being analyzed>"
# Two-pass process: first gather potential risks, then verify each one
potential_risks: # Pass 1: Pattern-matching findings
- "hardcoded path at line 42"
- "missing error handling for X"
# Pass 2: After verification
tigers:
- risk: "<description>"
location: "file.py:42"
severity: high|medium
category: dependency|integration|requirements|testing
mitigation_checked: "<what was NOT found>" # REQUIRED
elephants:
- risk: "<unspoken concern>"
severity: medium
paper_tigers:
- risk: "<looks scary but ok>"
reason: "<why it's fine - what mitigation EXISTS>"
location: "file.py:42-48" # Show the mitigation location
false_alarms: # Findings that turned out to be nothing
- finding: "<what was initially flagged>"
reason: "<why it's not a risk>"
Deep Checklist (Before Implementation)
Work through each category systematically:
Technical Risks:
- Scalability: Works at 10x/100x current load?
- Dependencies: External services + fallbacks defined?
- Data: Availability, consistency, migrations clear?
- Latency: SLA requirements will be met?
- Security: Auth, injection, OWASP considered?
- Error handling: All failure modes covered?
Integration Risks:
- Breaking changes identified?
- Migration path defined?
- Rollback strategy exists?
- Feature flags needed?
Process Risks:
- Requirements clear and complete?
- All stakeholder input gathered?
- Tech debt being tracked?
- Maintenance burden understood?
Testing Risks:
- Coverage gaps identified?
- Integration test plan exists?
- Load testing needed?
- Manual testing plan defined?
Output Format:
premortem:
mode: deep
context: "<implementation being analyzed>"
# Two-pass process
potential_risks: # Pass 1: Initial scan findings
- "no circuit breaker for external API"
- "hardcoded timeout value"
# Pass 2: After verification (read context, check for mitigations)
tigers:
- risk: "<description>"
location: "file.py:42"
severity: high|medium
category: scalability|dependency|data|security|integration|testing
mitigation_checked: "<what mitigations were looked for and NOT found>"
suggested_fix: "<how to address>"
elephants:
- risk: "<unspoken concern>"
severity: medium|high
suggested_fix: "<suggested approach>"
paper_tigers:
- risk: "<looks scary>"
reason: "<why it's actually ok - cite the mitigation code>"
location: "file.py:45-52"
false_alarms:
- finding: "<initial concern>"
reason: "<why verification showed it's not a risk>"
checklist_gaps:
- category: "<which checklist section>"
items_failed: ["<item1>", "<item2>"]
Step 3: Present Risks via AskUserQuestion
BLOCKING: Present findings and require user decision.
# Build risk summary
risk_summary = format_risks(tigers, elephants)
AskUserQuestion(
question=f"""Pre-Mortem identified {len(tigers)} tigers, {len(elephants)} elephants:
{risk_summary}
How would you like to proceed?""",
header="Risks",
options=[
{
"label": "Accept risks and proceed",
"description": "Acknowledged but not blocking"
},
{<How to use premortem on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add premortem
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches premortem from GitHub repository parcadei/continuous-claude-v3 and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate premortem. Access the skill through slash commands (e.g., /premortem) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★37 reviews- ★★★★★Fatima Diallo· Dec 4, 2024
premortem reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Michael Li· Nov 23, 2024
I recommend premortem for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Tariq Sanchez· Nov 23, 2024
Keeps context tight: premortem is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Hassan Patel· Oct 14, 2024
Useful defaults in premortem — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Tariq Nasser· Oct 14, 2024
premortem is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Tariq Abebe· Sep 17, 2024
premortem reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Michael Thomas· Sep 5, 2024
premortem is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Arya Martin· Sep 5, 2024
Useful defaults in premortem — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Rahul Santra· Sep 1, 2024
Registry listing for premortem matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Hassan Khanna· Aug 24, 2024
Keeps context tight: premortem is the kind of skill you can hand to a new teammate without a long onboarding doc.
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