Probabilistic Analysis Toolkit
SkillDev toolsAnalyze randomized algorithms with probability theory tools and concentration inequalities
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Probabilistic Analysis Toolkit skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/computer-science/skills/probabilistic-analysis-toolkit/SKILL.md and read by ahel’s review.
Purpose
Provides expert guidance on analyzing randomized algorithms using probability theory and concentration inequalities.
Capabilities
- Expected value calculations
- Chernoff and Hoeffding bound applications
- Markov and Chebyshev inequality analysis
- Moment generating function analysis
- Concentration inequality selection
- Las Vegas and Monte Carlo analysis
Usage Guidelines
- Random Variable Identification: Define relevant random variables
- Expectation Computation: Calculate expected values
- Concentration Selection: Choose appropriate bounds
- Bound Application: Apply concentration inequalities
- Result Interpretation: Interpret probabilistic guarantees
Tools/Libraries
- Symbolic probability
- Statistical libraries
- SymPy
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
probabilistic-analysis-toolkit- Source
- github.com/a5c-ai/babysitter