Causal Claim Extraction
SkillDev toolsExtract all causal claims (X causes Y, X leads to Y, X enables Y) from
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Causal Claim Extraction skill
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/causal-claim-extraction/SKILL.md and read by ahel’s review.
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.
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. |
Signals
- GitHub stars
- 469
- Forks
- 37
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
causal-claim-extraction- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine