# Convergence Assumption Extraction

> Systematically surface hidden assumptions underlying a decision with confidence levels.

- Skill: `yogsoth-ai/convergence-assumption-extraction` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/convergence-assumption-extraction`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/convergence-assumption-extraction/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/convergence-assumption-extraction

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# Assumption Extraction

Surfaces all hidden assumptions underlying a decision — the unstated beliefs that must be true for the decision to be correct. Each assumption is tagged with a confidence level indicating how certain we are that it holds.

## Execution

Spawns a subagent that systematically examines the decision and its evidence base to extract implicit assumptions across multiple categories.

## Why Subagent

- Assumption extraction requires focused, systematic attention
- The extractor must examine the decision from outside, without the decision-maker's blind spots
- Isolation prevents rationalization of assumptions as "obvious"

## HARD-GATE

Output must include:
- >= 5 distinct assumptions
- Confidence level for each (HIGH/MEDIUM/LOW)
- Category for each (causal, scope, temporal, resource, stakeholder, technical)
- Brief justification for each confidence rating

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## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |

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