Identify failure modes before they occur by systematically questioning plans, designs, and implementations. Based on Gary Klein's technique, popularized by Shreyas Doshi (Stripe).
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpremortemExecute the skills CLI command in your project's root directory to begin installation:
Fetches premortem from parcadei/continuous-claude-v3 and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate premortem. Access via /premortem in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
210
total installs
210
this week
3.7K
GitHub stars
0
upvotes
Run in your terminal
210
installs
210
this week
3.7K
stars
Identify failure modes before they occur by systematically questioning plans, designs, and implementations. Based on Gary Klein's technique, popularized by Shreyas Doshi (Stripe).
/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
"Imagine it's 3 months from now and this project has failed spectacularly. Why did it fail?"
| 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 |
Do NOT flag risks based on pattern-matching alone. Every potential tiger MUST go through verification.
Common mistakes that create false tigers:
if exists(): fallbackBefore 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.
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.
# 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"}
]
)
Run through these mentally, note any that apply:
Core Questions:
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>"
Work through each category systematically:
Technical Risks:
Integration Risks:
Process Risks:
Testing Risks:
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>"]
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"
},
{<Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
jezweb/claude-skills
premortem reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend premortem for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: premortem is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in premortem — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
premortem is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
premortem reduced setup friction for our internal harness; good balance of opinion and flexibility.
premortem is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in premortem — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for premortem matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: premortem is the kind of skill you can hand to a new teammate without a long onboarding doc.
showing 1-10 of 37