post-trade-compliance
post-trade-compliance is a Privacy & regulatory compliance skill for AI agents, published by JoelLewis in the finance_skills repository on GitHub. Skillspace rates post-trade-compliance C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Guide post-trade compliance monitoring and trade surveillance system design. Use when building alert logic to detect churning, front-running, cherry-picking, layering, spoofing, wash trading, or marking the close, implementing post-trade best execution review, evaluating allocation fairness with pro-rata verification or dispersion analysis, designing exception-based monitoring workflows with escalation paths, correlating trading with MNPI events for insider trading detection, building personal trading surveillance for preclearance and blackout enforcement, determining SAR or blue sheet or CAT reporting triggers, or tuning surveillance thresholds to reduce false positives. Also covers turnover ratios, cost-to-equity ratios, and investigation case management.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 151
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
- 99 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked 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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