genpark-structural-causal-model-dag-interventional-engine-skill
GenPark AI Agent Skill - Structural Causal Model (SCM) DAG engine evaluating observational distributions and simulating Pearl's do-calculus interventions.
Details
- External ID
- 1362859894
- Source
- GITHUB
- Company
- —
- Product
- genpark-structural-causal-model-dag-interventional-engine-skill
- Website domain
- github.com
- Launched
- Sept. 9, 2026
- Cohort
- —
- Upvotes
- 8
- Upvotes percentile
- 0.14514476044068664
- Tags
- agentic-ai, causal-inference, counterfactuals, do-calculus, genpark-skill, instrumental-variables, mcp, propensity-score, python-stdlib, structural-causal-models
- Fetched at
- Sept. 13, 2026, 5:48 a.m.
- Updated at
- Sept. 13, 2026, 5:48 a.m.
Enrichment
- Theme
- specialized AI models and agent reasoning tools
- Vertical
- Horizontal
- Function
- Dev tools
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Hobby / open-source project
- Normalized one-liner
- structural causal model engine for autonomous agents
- Manually corrected
- False
Could you build this?
Yes Evaluating DAG causal models and simulating graph interventions can be implemented using standard Python DAG libraries (like NetworkX) and basic probability calculations.
Competitors
Other products that read as similar to this one — 368 launches clear the similarity bar, closest 8 shown.
Attention rank: #40 of 369 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 307 days after the earliest competitor.
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Other launches for this product
Same idea, different domain
Nobody's really built a dev tools tool for Sales yet.