judea-pearl

judea-pearl is a Structured reasoning & decision frameworks skill for AI agents, published by K-Dense-AI in the mimeo repository on GitHub. Skillspace rates judea-pearl C (74/100) and it passed the safety scan; the rating is based on static analysis only.

Applies Judea Pearl's causal reasoning frameworks to distinguish correlation from causation, evaluate AI capabilities, and make counterfactual decisions. Reach for this skill whenever Claude encounters questions about causal inference, structural causal models, the limitations of deep learning, AGI, experimental design, covariate selection, or personalized decision-making. Trigger this skill for topics involving Bayesian networks, the do-calculus, the Ladder of Causation, or when a user tries to answer 'what if' or 'why' questions using purely observational data. Pearl's principles are essential for moving beyond probability calculus into true causal understanding.

Grade
C
Quality
74 / 100
Safety
Passed
GitHub stars
230

Unproven: rated by static analysis only, not yet compared head-to-head.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

Our review

Architecture
100 / 100
Maturity
Structured: ships references or scripts
Security scan
No issues found
License
MIT
Adoption
Adopted by 1 other repositories, in 0 collections
Scope
Portable: works in any project. General causal-reasoning persona applicable anywhere

Not checked yet

  • Not judged on the rubric yet (not a contender in its category)
  • No blind task eval yet
  • Sibling files (scripts, references) not fetched; security scan covers SKILL.md only

Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.