mindit-premortem

mindit-premortem is a skill for Claude Code, Codex from Dragoon0x/usemindit. It costs 109 tokens per session (1,408 once invoked), scanned A, original, MIT.

A pre-launch design review that assumes the design has already failed and works backward to identify the likely causes.

In plain words
What is it for?
Use it to examine launch plans, identify failure modes, question high-stakes or irreversible choices, and run a devil’s-advocate review.
Why use it?
It challenges confident assumptions and surfaces risks that a normal approval-focused review may miss.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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/dragoon0x/usemindit/mindit-premortem
Any agent
npx skills add Dragoon0x/usemindit --skill mindit-premortem
Clone the repo
git clone --depth 1 https://github.com/Dragoon0x/usemindit

Made for: Claude Code, Codex.

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 mindit-premortem

README.md
[![agentmods](https://agentmods.dev/badge/skills/dragoon0x/usemindit/mindit-premortem.svg)](https://agentmods.dev/skills/dragoon0x/usemindit/mindit-premortem)
Your own site
<a href="https://agentmods.dev/skills/dragoon0x/usemindit/mindit-premortem"><img src="https://agentmods.dev/badge/skills/dragoon0x/usemindit/mindit-premortem.svg" alt="Measured on agentmods" height="20"></a>
Per session 109 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,408 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 5.1 $0.00109 $0.01408
Opus 5 $0.00055 $0.00704
Sonnet 5 $0.00022 $0.00282
Haiku 4.5 $0.00011 $0.00141

Measured 5d ago against content hash 9c33a56711fd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

mindit-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 5d 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/mindit-premortem/SKILL.md · 113 lines

How it starts

The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.

mindit-premortem

The second of three meta skills. Run this when the question is "what could kill this."

What this skill does

Inverts the design review. Instead of asking "is this good," it assumes the design has already failed and asks "what made it fail." This is the pre-mortem technique applied to design decisions. It surfaces failure modes that confident teams miss because they are reviewing for confirmation rather than refutation.

The skill is adversarial by design. Its goal is not to talk the team out of shipping. Its goal is to make the team's confidence honest by stress-testing it.

When to run this

  • The user is about to ship something they feel good about, and you want to stress-test that confidence.
  • The user asks "what could go wrong," "what are the risks," "what am I missing."
  • The user explicitly asks for a devil's-advocate read or for arguments against a design.
  • A pre-launch checklist would benefit from one final adversarial pass.
  • The user is making a high-stakes irreversible choice (default change, brand refresh, pricing change, schema migration).

How to analyze

  1. State the imagined failure. Write one sentence: "It is three months after launch. The design has failed in a way that is now obvious. The team is doing a post-mortem."

  2. Brainstorm failure scenarios. Generate at least eight distinct ways the design could have failed. Use the eight forces as prompts:

    • It failed because users could not understand it (clarity).
    • It failed because it broke the conventions of the rest of the product (continuity).
    • It failed because it hit a constraint we did not see (constraint).
    • It failed because of a side effect we did not predict (consequence).
    • It failed because we built it for the wrong audience or context (context).
    • It failed because it cost more to maintain than we budgeted (cost).
    • It failed because our evidence was wrong (confidence).
    • It failed because we could not recover when we noticed it was wrong (correctability).

Read the full file on GitHub · 113 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. 5d ago First seen · 113 lines · 109 tokens per session scan A 9c33a56711fd

Subscribe to this mod's changes

mindit-premortem is a skill published in the GitHub repository Dragoon0x/usemindit (2 stars, last pushed 3mo ago), licensed MIT. It adds 109 tokens to every session and 1,408 once invoked, about $0.0005 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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