agentleFS
ysskrishnaysskrishna/ai-agent-skills/skills/pre-mortem/SKILL.md

pre-mortem

Skill20 starsChanged 27 days agoMITView on GitHub

Use for a pre-mortem, or before committing to a plan, launch or migration: "what could go wrong?", "stress test this plan", "how might this fail?", "risks before we ship". Assumes failure, lists causes, ranks them and sets mitigations. Skip for explaining a failure that already happened.

30 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use brainstorm-experiments-existing, prioritize-assumptions and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • skytiger6724Skill

    brainstorm-experiments-existing

    Design experiments to test assumptions for an existing product — prototypes, A/B tests, spikes, and other low-effort validation methods. Use when validating assumptions, testing feature ideas cheaply, or planning product experiments.

    Also in 7 projects that use this

  • skytiger6724Skill

    prioritize-assumptions

    Prioritize assumptions using an Impact × Risk matrix and suggest experiments for each. Use when triaging a list of assumptions, deciding what to test first, or applying the assumption prioritization canvas.

    Also in 7 projects that use this

  • 45ckSkill

    pestle-analysis

    Also in 7 projects that use this

  • About-IntelligenceSkill

    positioning-ideas

    Brainstorm product positioning ideas differentiated from competitors.

    Also in 7 projects that use this

  • About-IntelligenceSkill

    product-name

    Brainstorm 5 unique, memorable product names with rationale aligned to brand values and target audience.

    Also in 6 projects that use this

  • +5 more from skytiger6724
  • +1 more from About-Intelligence

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 23 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Before a launch, migration, reorg, contract, hire, architecture change or any hard-to-reverse commitment.

    line 17
  2. Distinctive:

    Gather first: Read the plan, timeline, dependencies, past incidents and similar launches before generating causes.

    line 26
  3. Distinctive:

    Write one sentence in the past tense: "It is [date].

    line 32
  4. Distinctive:

    Add an owner (or "to be assigned").

    line 49

“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Pre-mortem

Gary Klein's technique: imagine the plan has already failed, then work backward to explain why. Assuming failure makes it safe to name risks that optimism hides.

When to use

  • Before a launch, migration, reorg, contract, hire, architecture change or any hard-to-reverse commitment.
  • "What could go wrong?", "stress test this", "play out the failure".
  • A plan everyone likes and nobody has attacked.

Skip: explaining a failure that already happened, or reviewing the logic of an argument rather than a plan.

Before you start

  1. State in one block: Plan (what, who, by when), Failure definition (what "failed badly" means, observable), Horizon, and Pass (Imagine, Causes, Rank, Mitigate, Decide).
  2. Gather first. Read the plan, timeline, dependencies, past incidents and similar launches before generating causes. Ask up to 3 questions only for what tools cannot answer.
  3. Light path. Small ask: 6 causes, top 3 ranked, one mitigation each.

Steps

1. Imagine

Write one sentence in the past tense: "It is [date]. The [plan] failed badly: [failure definition]."

2. Causes

List reasons it failed. Cover different angles so they do not cluster: people and skills, process and timeline, technology and dependencies, customers and market, money, external events. Add one inversion prompt: "What would guarantee failure?" and list what you would then have to avoid. Each cause is a specific story ("the vendor API changes its rate limit during launch week"), not a category ("vendor risk").

3. Rank

For each cause give a plain-language likelihood, impact if it happens, and an early warning sign. Keep the top 5-8.

CauseLikelihoodImpactEarly warning

4. Mitigate

For each top cause choose one:

  • Prevent: change the plan so it cannot happen.
  • Detect: a metric or check that shows it early.
  • Respond: a rehearsed fallback.

Add an owner (or "to be assigned").

5. Decide

  • Plan changes to make now.
  • Tripwires: conditions under which the plan is paused, changed or stopped.
  • Go / no-go statement: go as is, go with changes, or hold until named risks are reduced.

Pitfalls

  • Generic risks ("scope creep") with no story. Write what it looks like when it happens.
  • Everything high likelihood and high impact. Force a ranking; a list where all items matter does not guide action.
  • Mitigations nobody owns. Name an owner or mark it unassigned.
  • Using it on something already failed. That is a postmortem; use a root-cause method.
  • Treating the output as a promise that nothing else will go wrong. Revisit at each tripwire.

Worked example: references/example.md.

Checklist

  • Plan, failure definition and horizon stated
  • Failure written in the past tense
  • Causes are specific stories across several angles, plus an inversion prompt
  • Ranked with likelihood, impact and an early warning sign
  • Mitigations are prevent, detect or respond, with owners
  • Tripwires and a go / no-go statement

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.