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/0adf49a8ae84b0ff6e2de8759eea43257e020eff/src/skills/premortem/SKILL.md at commit 0adf49a8ae84b0ff6e2de8759eea43257e020eff. 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 | 7 | 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.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)/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).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
event4u-app/agent-config
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
K-Dense-AI/scientific-agent-skills
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
K-Dense-AI/scientific-agent-skills
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.