think-premortem

think-premortem is a skill for Claude Code from product-on-purpose/thinking-framework-skills. It costs 77 tokens per session (1,178 once invoked), scanned A, original, Apache-2.0.

A planning exercise that assumes a decision has already failed and works backward to identify why. It turns those possible causes into a risk list with preventive actions, warning signals, and conditions for stopping.

In plain words
What is it for?
Use it before launches, hires, investments, migrations, or other risky commitments to rank failure risks and define mitigations, tripwires, and kill criteria.
Why use it?
It makes unspoken concerns easier to raise before a commitment is made. It replaces general caution with specific risks and pre-agreed responses.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the thinking-framework-skills plugin — 68 skills, 10 commands, 1 agent shipped together

Good fit Use it before launches, hires, investments, migrations, or other risky commitments to rank failure risks and define mitigations, tripwires, and kill criteria.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/product-on-purpose/thinking-framework-skills/think-premortem
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.

Any agent
npx skills add product-on-purpose/thinking-framework-skills --skill think-premortem
Clone the repo
git clone --depth 1 https://github.com/product-on-purpose/thinking-framework-skills

Made for: Claude Code.

Or install thinking-framework-skills, the plugin that ships this one along with the rest of its 68 skills, 10 commands, 1 agent.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for think-premortem

README.md
[![agentmods](https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-premortem/github.svg)](https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-premortem)
Your own site
<a href="https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-premortem"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-premortem/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for think-premortem

Your own site · 80×15
<a href="https://agentmods.dev/skills/product-on-purpose/thinking-framework-skills/think-premortem"><img src="https://agentmods.dev/badge/skills/product-on-purpose/thinking-framework-skills/think-premortem.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,178 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00077 $0.01178
Opus 5 $0.00039 $0.00589
Sonnet 5 $0.00015 $0.00236
Haiku 4.5 $0.00008 $0.00118

Measured 12d ago against content hash 02955a0da84d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

think-premortem 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 12d 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.

skills/think-premortem/SKILL.md · 64 lines

How it starts

The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Premortem

A premortem stress-tests a plan by assuming it has already failed and reasoning backward to explain why, then converting each cause into a mitigation, a tripwire, and a kill criterion. The shift from "what might go wrong?" to "it went wrong, why?" is what does the work: it licenses dissent, surfaces more and more specific causes than ordinary risk review, and turns vague worry into pre-committed action while you can still change course. The output is a risk register, not a discussion.

When to Use

  • Before a launch, hire, investment, migration, vendor selection, or any consequential, hard-to-reverse commitment.
  • When a plan has optimistic momentum and you suspect concerns are going unspoken.
  • When you want risks expressed as observable signals and pre-decided responses, not a feeling of caution.
  • Often after options have been compared and one has been chosen, as the last gate before committing.

When NOT to Use

  • After the outcome is known. That is a postmortem, a different tool.
  • For trivial or fully reversible (two-way-door) decisions. The ceremony is not worth it.
  • To generate options or to choose among them. Use an ideation skill or a decision-option review; premortem is a risk tool.
  • As a ritual to bless a decision already made. If the mitigations will not be acted on, skip it; a premortem nobody acts on is theater.

Instructions

When asked to run a premortem, follow these steps:

  1. Frame the decision and the horizon. State the plan and intended outcome in one or two sentences, and pick a concrete time horizon (for example, "six months after launch"). If the decision is trivial or already irreversible, say so and stop.
  2. Declare the failure vividly. Assert it in the definite past: "It is [horizon]. This plan has failed badly." Make the failure concrete and specific, not "it underperformed." Write it into the template's "The failure, declared" section as a past-tense scene of observed fact - it is part of the artifact, and every cause in the register must explain it in the past tense.
  3. Generate causes broadly, before judging. List the plausible reasons the failure happened. Aim for breadth and specificity; include uncomfortable, political, and second-order causes, not just technical ones. Do not filter yet.
  4. Cluster and rank. Group related causes and rank them by likelihood and impact (High/Medium/Low each). Keep the vital few; do not pad.
  5. Convert each top cause into action. For each high-priority cause, define a leading signal / tripwire (the early sign it is happening), a mitigation (what reduces the risk now), an owner, and a kill criterion (the pre-decided condition under which you stop or change course). This conversion step is mandatory; a list of risks without it is not a premortem.
  6. Emit the risk register and a short summary. Produce the artifact in references/TEMPLATE.md: the declared failure in the definite past, then a one-paragraph "top risks and what we will do" summary above a ranked register table.

Read the full file on GitHub · 64 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 64 lines · 77 tokens per session scan A 02955a0da84d

Subscribe to this mod's changes

think-premortem is a skill published in the GitHub repository product-on-purpose/thinking-framework-skills (15 stars, last pushed today), licensed Apache-2.0. It adds 77 tokens to every session and 1,178 once invoked, about $0.0004 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 2026-08-30.

Related

Other skills, from other repositories

ops-demo

CocoOps demo mode activator — populates .cocoplus/ops/demo/ with realistic mock data and sets cocoplus.toml [demo] enabled = true. Invoked via $ops demo.

Snowflake-Labs/cocoplus · 46 tokens

acl-rule-analysis

Vendor-agnostic ACL and firewall rule analysis with shadowed rule detection, overly permissive rule identification, unused rule discovery, redundant rule flagging, and rule ordering optimization. Covers ACLs (Cisco/JunOS/EOS) and firewall policies (PAN-OS/FortiGate/CheckPoint).

LeoYeAI/openclaw-master-skills · 64 tokens

add-analytics

Add Google Analytics 4 tracking to any project. Detects framework, adds tracking code, sets up events, and configures privacy settings.

LeoYeAI/openclaw-master-skills · 32 tokens

agent-teams-simplify-and-harden

Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…

LeoYeAI/openclaw-master-skills · 115 tokens

agent-team-orchestration

Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4)…

LeoYeAI/openclaw-master-skills · 102 tokens

agent-bom-enforce

Enforce security policies on MCP tool calls and block dangerous operations at runtime. Use when: "block risky calls", "apply policy", "proxy", "runtime protection", "policy enforcement", "intercept MCP calls".

LeoYeAI/openclaw-master-skills · 50 tokens