Best for
- Heavy to execute (multi-sprint, multi-team, or high coordination cost), or
- Irreversible or costly to reverse (schema migration, public API change,
- The failure is already evidenced — root cause is known → use
event4u-app/agent-config/src/skills/premortem/SKILL.md
Use before committing to a heavy or irreversible plan — imagine it's 6 months later and this failed; enumerate why, score each mode, derive early-warning signals and preventive guardrails.
Decision brief
Forward-looking imagined-failure analysis. Sibling of blameless-post-mortem (which analyses what actually went wrong after the fact) and risk-officer (which scores pre-commit risks per likelihood × impact). This skill adds the prospective frame: "Assume total failure at horizon…
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/premortem"Inspect the Agent Skill "premortem" from https://github.com/event4u-app/agent-config/blob/6a5670b7881a676c0da90d2afb950298087c4ccb/src/skills/premortem/SKILL.md at commit 6a5670b7881a676c0da90d2afb950298087c4ccb. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Summarise the plan in one sentence: "We are doing X for outcome Y, touching Z." Set the prospective-failure frame explicitly: "Assume total failure at horizon H (e.g. 6 months post-launch). What went wrong?"
Before committing to a plan that is:
Summarise the plan in one sentence: "We are doing X for outcome Y, touching Z." Set the prospective-failure frame explicitly: "Assume total failure at horizon H (e.g. 6 months post-launch). What went wrong?"
Generate failure scenarios across multiple angles (people, process, technical, external, timing). Each scenario is a short narrative in past tense: "We shipped, but adoption collapsed because …"
For each top failure mode (sorted by L × I from risk-officer):
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 92/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 9 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Forward-looking imagined-failure analysis. Sibling of
blameless-post-mortem(which analyses what actually went wrong after the fact) andrisk-officer(which scores pre-commit risks per likelihood × impact). This skill adds the prospective frame: "Assume total failure at horizon H — reconstruct why."
Before committing to a plan that is:
Trigger phrasing: "premortem this", "what if this fails?", "imagine it's 6 months later and this shipped badly", "help me stress-test this plan".
Do NOT use when:
systematic-debugging.blameless-post-mortem.Summarise the plan in one sentence: "We are doing X for outcome Y, touching Z." Set the prospective-failure frame explicitly: "Assume total failure at horizon H (e.g. 6 months post-launch). What went wrong?"
If the plan cannot be summarised in one sentence, it is not reviewable — stop and ask for scope clarification.
Generate failure scenarios across multiple angles (people, process, technical, external, timing). Each scenario is a short narrative in past tense: "We shipped, but adoption collapsed because …"
For each scenario:
adversarial-review to attack the
plan's assumptions and surface hidden coupling or over-engineering.risk-officer to assign L × I (likelihood
× impact) scores to each failure mode.Do NOT re-implement L × I scoring inline — delegate to risk-officer.
For each top failure mode (sorted by L × I from risk-officer):
accept if no practical guardrail exists.When the pre-mortem accompanies a plan artefact (a roadmap, an ADR, a design
doc), compress the analysis into the four-part failure register — the
fixed, comparable shape the roadmap template's optional ## Pre-mortem
section consumes:
The register was validated blind against this repo's own closed nulls
(3 of 4 registers named the actual failure cause at rank 1 —
agents/evidence/analysis/premortem-blind-retro-validation.md). The hits were
all failures of measurability; the miss was a mechanism that worked but
added nothing — weight the register toward "can this experiment answer its
question" and state redundancy risks explicitly.
If the analysis surfaces a pattern worth preserving for future decisions:
retrieve() over the same key-space (plan type,
affected paths, decision area). If a match is found, propose a
frequency/supersedes update to the existing entry rather than a new one.historical-patterns candidate and send it to /memory propose per
docs/contracts/analysis-memory-loop.md./memory promote.risk-officer)accept with rationale)## Pre-mortem section)/memory propose if the pattern
clears the admission gate (≥ 2 distinct file paths OR ≥ 3 future decisions)risk-officer; don't duplicate
its five-lens framework inline./memory propose is the intake;
/memory promote requires explicit human action and passes
check_memory_proposal.ts.blameless-post-mortem is backward-looking — it analyses
a past failure. Do not conflate them.risk-officer — L × I scoring; invoked in
Step 2. Not duplicated here.adversarial-review — assumption attack;
invoked in Step 2. Not duplicated here.blameless-post-mortem — post-hoc
analysis of an actual failure; backward-looking counterpart to this skill./analyze premortem, feature:plan, roadmap-create
(surface the premortem step as optional before committing to a plan).Frequently asked questions
Forward-looking imagined-failure analysis. Sibling of blameless-post-mortem (which analyses what actually went wrong after the fact) and risk-officer (which scores pre-commit risks per likelihood × impact). This skill adds the prospective frame: "Assume total failure at horizon…
The source record exposes this install command: npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/premortem". Inspect the command and pinned source before running it.
Alternatives
coreyhaines31/marketingskills
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
alirezarezvani/claude-skills
App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklist
equinor/neqsim
Engineering deliverable quality — the nine analytical-depth moves (contributor ranking, adjudicating the source document, quantitative rule-outs, robustness crossover, conservatism direction, discriminating test), results.json schema, figure→discussion→linked_results traceability, evidence matrices, assumptions/gaps registers, citation conventions, KaTeX math formatting, units consistency, executive-summary structure, AACE class declaration. USE WHEN: producing a task report, a PEPR/M1/root-caus
JasonColapietro/suede-creator-skills
Suede-owned experimentation discipline for hypotheses, sample sizing, test duration, significance, and repeatable experiment programs. Use when comparing variants, deciding whether a result is reliable, or building an experiment backlog and cadence. NOT FOR: analytics instrumentation (use suede-analytics), post-click conversion diagnosis (use suede-site-alchemy), or writing the variant copy itself (use suede-copy).