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event4u-app/agent-config/src/skills/premortem/SKILL.md

premortem

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.

Source repository stars
7
Declared platforms
0
Static risk flags
0
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

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…

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

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/premortem"
Safe inspection promptEditorial

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

What the source asks the agent to do

  1. 01

    Procedure

    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?"

    Invoke adversarial-review to attack theInvoke risk-officer to assign L × I (likelihoodEarly-warning signal — what would you observe first if this failure
  2. 02

    When to use

    Before committing to a plan that is:

    Heavy to execute (multi-sprint, multi-team, or high coordination cost), orIrreversible or costly to reverse (schema migration, public API change,The failure is already evidenced — root cause is known → use
  3. 03

    1. State the plan and set the horizon

    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?"

    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.
  4. 04

    2. Enumerate failure stories

    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 …"

    Invoke adversarial-review to attack theInvoke risk-officer to assign L × I (likelihoodGenerate 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 …"
  5. 05

    3. Derive early-warning signals and preventive guardrails

    For each top failure mode (sorted by L × I from risk-officer):

    Early-warning signal — what would you observe first if this failurePreventive guardrail — one specific change to the plan, process, orFor each top failure mode (sorted by L × I from risk-officer):

Permission review

Static risk signals and limitations

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

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score92/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars7SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
event4u-app/agent-config
Skill path
src/skills/premortem/SKILL.md
Commit
0adf49a8ae84b0ff6e2de8759eea43257e020eff
License
MIT
Collected
2026-07-28
Default branch
main
View the original SKILL.md

premortem

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 H — reconstruct why."

When to use

Before committing to a plan that is:

  • Heavy to execute (multi-sprint, multi-team, or high coordination cost), or
  • Irreversible or costly to reverse (schema migration, public API change, infrastructure restructure, major dependency swap, architecture decision).

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:

  • The failure is already evidenced — root cause is known → use systematic-debugging.
  • Analysing something that already failed in the past → use blameless-post-mortem.
  • The plan is trivial or fully reversible — overhead exceeds value.

Procedure

1. State the plan and set the horizon

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.

2. Enumerate failure stories

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:

  • Invoke adversarial-review to attack the plan's assumptions and surface hidden coupling or over-engineering.
  • Invoke 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.

3. Derive early-warning signals and preventive guardrails

For each top failure mode (sorted by L × I from risk-officer):

  1. Early-warning signal — what would you observe first if this failure mode were activating? Name a concrete, observable indicator (metric, alert, user behaviour, team signal). This is the load-bearing output.
  2. Preventive guardrail — one specific change to the plan, process, or rollout strategy that reduces the likelihood of this failure mode. Keep it executable; flag as accept if no practical guardrail exists.

4. Optional memory write-back

If the analysis surfaces a pattern worth preserving for future decisions:

  1. Run a dedup pre-check: call 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.
  2. Draft a historical-patterns candidate and send it to /memory propose per docs/contracts/analysis-memory-loop.md.
  3. Never auto-promote. Human action drives /memory promote.

Output format

  1. Ranked prospective failure modes — L × I ordered list (from risk-officer)
  2. Early-warning signal per failure mode — concrete, observable indicator
  3. Preventive guardrails — one per failure mode (or accept with rationale)
  4. Optional memory candidate — drafted to /memory propose if the pattern clears the admission gate (≥ 2 distinct file paths OR ≥ 3 future decisions)

Do NOT

  • Do NOT invent strawman failure modes — each must be grounded in the actual plan's structure, assumptions, or dependencies.
  • Do NOT re-implement L × I scoring — invoke risk-officer; don't duplicate its five-lens framework inline.
  • Do NOT present speculation as evidence — premortem is imaginative framing, not a prediction; label scenarios as prospective.
  • Do NOT auto-promote memory candidates — /memory propose is the intake; /memory promote requires explicit human action and passes check_memory_proposal.ts.

Gotchas

  • Premortem is forward-looking — it imagines a future failure to improve the present plan. blameless-post-mortem is backward-looking — it analyses a past failure. Do not conflate them.
  • The early-warning signal is the load-bearing output, not the doom list. A failure mode without a detectable signal cannot be caught in time — flag it explicitly.
  • Failure stories in past tense ("we shipped, and then X happened") are more generative than abstract risk statements. Force the past-tense narrative.

See also

  • 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.
  • Invocation surfaces: /analyze premortem, feature:plan, roadmap-create (surface the premortem step as optional before committing to a plan).

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