crash-out
Skill11 starsChanged 3 months agoMITView on GitHub
Anti-hallucination mode where Claude drafts an answer and then becomes obsessed with proving itself wrong, attacking every claim with tools and counter-evidence and shipping only what survives; invoke via /crash-out on factual questions, debugging, research, or any answer where confident-and-wrong is expensive.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- taljeon/plzdotheir own version, first seen Nov 1, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- taljeon/plzdo★ 9same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
- 67Skill
- aura-farmingSkill
- china-maxingSkill
- larpSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
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
- Distinctive: line 18
Run the code, command, or query when one exists.
- Distinctive: line 19
Read the actual source, docs, or file.
- Distinctive: line 20
Search for disconfirming evidence, not confirming.
- Distinctive: line 27
If a busted claim was central, say the original answer was wrong and what changed.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Crash Out
Hallucinations survive because the model defends its first draft. This flips the incentive: after drafting, the only goal is to destroy the draft. Every claim gets attacked. Whatever is still standing is the answer.
When to use
- Factual questions, research, technical claims, debugging conclusions.
- Anywhere a confident wrong answer costs more than a slow right one.
Behavior
- Draft the answer privately. Do not show it yet.
- Extract every load-bearing claim from the draft into a list: facts, numbers, names, API behaviors, causal statements. If the answer depends on it, it goes on the list.
- Attack each claim in turn. Attacking means evidence, not re-reading your own reasoning:
- Run the code, command, or query when one exists.
- Read the actual source, docs, or file.
- Search for disconfirming evidence, not confirming.
- Attack load-bearing claims from at least two angles.
- Verdict per claim:
- SURVIVED: attacked and held, evidence cited.
- SHAKY: could not verify either way. Must be labeled as unverified in the final answer, never asserted as fact.
- BUSTED: disproven. Correct it or delete it.
- Rewrite the answer from survivors only. Shaky items appear with an explicit flag and what would confirm them.
- If a busted claim was central, say the original answer was wrong and what changed. Never smooth it over.
Output
The verified answer with unverified statements flagged inline, followed by a short kill list: claims that got busted during the crash-out and what replaced them.
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
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.

