pre-mortem

A planning method that imagines a project has already failed and then works backward to identify why. It also prepares alternative responses for different future conditions.

In plain words
What is it for?
Use it before approving a strategy or major initiative, to list failure causes, define prevention steps, and set triggers for a backup plan.
Why use it?
It exposes overlooked risks before a major decision and gives the team clear warning signs and backup actions.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/voxtechnologies/anty-framework/pre-mortem
Any agent
npx skills add VoxTechnologies/anty-framework --skill pre-mortem
Clone the repo
git clone --depth 1 https://github.com/VoxTechnologies/anty-framework

Made for: Claude Code, Codex.

Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,256 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00042 $0.01256
Opus 5 $0.00021 $0.00628
Sonnet 5 $0.00008 $0.00251
Haiku 4.5 $0.00004 $0.00126

Measured 2d ago against content hash 56c48d2fbff5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pre-mortem scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/pre-mortem/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Pre-Mortem & Scenario Planning

When to Apply

  • Before finalizing any Strategy Kernel
  • When planning a major initiative or Goal
  • When buffer enters YELLOW zone (validate contingencies)
  • When the founder is overly optimistic about a single plan
  • Quarterly strategy reviews

Core Framework

Pre-Mortem (5-Step Process)

  1. Assume total failure: "It is 6 months from now. This strategy has completely failed. Why?"
  2. Enumerate causes: List 3-5 specific, concrete failure scenarios (not vague risks)
  3. For each cause, define:
    • Prevention measure (what to do now)
    • Plan B (what to do if it happens)
    • Early warning KPI (what to watch)
    • Trigger threshold (when to act)
  4. Rank by likelihood x impact
  5. Embed triggers into the monitoring system so Plan B activates automatically
Failure cause: "LinkedIn organic saturated — ICP exhausted in target segment"
  Prevention: Track unique ICP accounts remaining; alert at <500
  Plan B: Pivot to content-first -> community -> warm intro strategy
  Early warning KPI: new connection acceptance rate declining
  Trigger: acceptance rate < 15% for 2 consecutive weeks

Scenario Planning (4 Scenarios with Auto-Triggers)

Define quantitative trigger points for each scenario. When thresholds are hit, Plan B activates AUTOMATICALLY — removing human judgment to prevent bias (loss aversion, sunk cost).

Scenario Condition Response
OPTIMISTIC Exceeds target by 20%+ Continue scaling. Increase targets.
BASE 80-120% of target Maintain strategy. Increase effort on constraint Driver.
PESSIMISTIC 40-80% of target + buffer RED + growth <3%/week for 3 weeks Auto-activate Plan B: pivot channel, reposition ICP, adjust pricing
CATASTROPHIC <40% of target + buffer >90% + negative growth for 2 weeks Full strategy reset: rebuild Strategy Kernel from scratch

Future State Narrative (PR/FAQ)

Before executing any major initiative, write success AS IF it already happened:

Read the full file on GitHub · 121 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 121 lines · 42 tokens per session scan A 56c48d2fbff5

Subscribe to this mod's changes

pre-mortem is a skill published in the GitHub repository VoxTechnologies/anty-framework (6 stars, last pushed 4mo ago), licensed MIT. It adds 42 tokens to every session and 1,256 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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