monte-carlo
monte-carlo is a Physics, mathematics & simulation skill for AI agents, published by shreyas-lyzr in the quant-sim repository on GitHub. Skillspace rates monte-carlo D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Foundation Monte Carlo simulation for binary contracts and prediction markets. GBM-based path simulation, binary payoff estimation, confidence intervals, and Brier score calibration. The base layer everything else builds on.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 23
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
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 1 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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