assumption-mapper
Skill0 starsChanged 4 months agoMITView on GitHub
Extract and rank assumptions from any plan, idea, or strategy. Identifies what to test first. Anti-sycophancy tool — surfaces beliefs the user treats as facts. Activates on "what am I assuming", "assumptions", "what could go wrong", "blind spots", "stress test my thinking", or "what haven't I considered?"
3 other projects use a version of this.
Adopted by
Most recently taken up by
- imohammadfaraz/claude-skills-for-product-managertheir own version, first seen Nov 1, 2026
- varunk130/ai-customer-discovery-skillstheir own version, first seen May 2, 2026
- pratikshadake/claude-product-management-skillstheir own version, first seen Feb 19, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- pratikshadake/claude-product-management-skills★ 33same name
- imohammadfaraz/claude-skills-for-product-manager★ 19same name
- varunk130/ai-customer-discovery-skills★ 2same 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 repository15 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- ai-graduationSkill
- arbitrage-auditSkill
- b2b-idea-vettingSkill
- codifySkill
- decision-briefSkill
- design-thinking-liteSkill
- grill-meSkill
- grill-with-docsSkill
- innovation-diagnosticSkill
- kill-goSkill
- preflightSkill
- problem-framingSkill
- pull-frameworkSkill
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
Ask: "Walk me through your plan, idea, or strategy.
- Distinctive: line 41
Impact if wrong (1-5): If this assumption is false, how badly does it break the plan?
- Distinctive: line 56
Behavior test (1 day): Create a landing page, fake door, or signup form.
- Distinctive: line 58
Data test (1 hour): Search for existing data that confirms or contradicts.
≈ “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
How It Works
Listen to the user describe their plan, idea, or strategy. Then extract every assumption hiding in what they said.
Step 1: Gather the Plan
Ask: "Walk me through your plan, idea, or strategy. Don't filter — include the parts you're less sure about."
Let the user talk. Don't interrupt to challenge yet. Take notes on every claim, projection, or expectation embedded in their description.
Step 2: Extract Assumptions
Review everything the user said. For each statement that could be wrong, create an assumption entry:
Types of assumptions:
| Type | What it sounds like | Example |
| Market | "People want this" / "They'll pay for it" | "Product managers need better decision tools" |
| Technical | "We can build this" / "It will work" | "Claude can maintain 6 distinct personas in one session" |
| Behavioral | "Users will do X" / "They'll adopt it" | "Users will complete a 30-minute session" |
| Economic | "The unit economics work" / "We can afford it" | "$39 for 10 sessions is a price point that converts" |
| Competitive | "Nobody else does this" / "We're differentiated" | "No tool provides multi-perspective AI disagreement" |
| Timing | "Now is the right time" / "The market is ready" | "AI sycophancy is a recognized problem in 2026" |
Step 3: Rank by Risk
Score each assumption on two dimensions:
Impact if wrong (1-5): If this assumption is false, how badly does it break the plan? Confidence level (1-5): How much evidence supports this assumption?
| Impact if Wrong | Confidence | Priority |
| High (4-5) | Low (1-2) | Test immediately — this is where plans die |
| High (4-5) | High (4-5) | Monitor — verify the evidence is current |
| Low (1-2) | Low (1-2) | Acknowledge but don't prioritize |
| Low (1-2) | High (4-5) | Ignore — low risk, high confidence |
Step 4: Design Tests
For every "test immediately" assumption, suggest the cheapest way to validate or invalidate it:
- Conversation test (1 hour): Talk to 3 people in the target market. Ask about the problem, not the solution.
- Behavior test (1 day): Create a landing page, fake door, or signup form. Measure clicks, not opinions.
- Build test (1 week): Build the smallest version that tests the assumption. Ship it to 5 people. Measure usage.
- Data test (1 hour): Search for existing data that confirms or contradicts. Google Trends, competitor revenue, industry reports.
Step 5: Present the Map
Output
# Assumption Map: [Plan Name]
Date: [date]
## Test Immediately (High Impact, Low Confidence)
| # | Assumption | Type | Impact | Confidence | Cheapest Test |
|---|-----------|------|--------|------------|---------------|
| 1 | [assumption] | [type] | X/5 | X/5 | [test] |
## Monitor (High Impact, High Confidence)
| # | Assumption | Type | Evidence |
|---|-----------|------|----------|
| 1 | [assumption] | [type] | [what supports it] |
## Acknowledged (Low Impact)
- [assumption 1]
- [assumption 2]
## Summary
- Total assumptions found: [N]
- Test immediately: [N]
- Biggest risk: [the #1 assumption to test first and why]Anti-Sycophancy Note
The user may push back on assumptions you surface. "No, I know that's true." Ask: "How do you know? What's the evidence?" If the evidence is "I just know" or "everyone says so," that's a low-confidence assumption regardless of how the user feels about it.
Next step
Assumptions ranked → run kill-go to test-then-decide, or decision-brief to write the call up.
Part of the ThinkHaven Method Kit by Kevin Holland. Full Board of Directors experience: ThinkHaven
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
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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.

