# Causal Claim Extraction

> Extract all causal claims (X causes Y, X leads to Y, X enables Y) from an artifact, producing a structured list of cause-effect pairs.

- Skill: `yogsoth-ai/causal-claim-extraction` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/causal-claim-extraction`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/causal-claim-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/causal-claim-extraction

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# Causal Claim Extraction

Extracts all explicit and implicit causal claims from an artifact.

## Execution

Subagent — spawned via subagent-spawning/spawn-agent.

## Why Subagent

Causal claim extraction requires careful linguistic analysis of the entire artifact. Isolated context prevents premature evaluation of claims.

## Input

- **artifact**: The artifact to analyze
- **artifact_type**: Type of artifact (gap, hypothesis, claim, etc.)

## Output

- **causal_claims**: List of {cause, effect, strength, evidence, location}
- **causal_graph**: Directed graph of cause-effect relationships
- **claim_count**: Total number of causal claims found

## Budget

One unit = one extraction pass per artifact.

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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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