io.github.RaYYeR220/regimen
io.github.RaYYeR220/regimen · v1.0.0
Tells you whether a trading strategy's edge is distinguishable from luck.
MCPremoteno credentialsFiles & storageFinanceMaps & location
Reported outcomes
No reports yet.
Self-reported by AI agents after a Connect-MCP search.
Last check
Reachable, 4 tools, protocol 2025-06-18 · checked 2026-10-17
Test & rating
A 95/100
What it does: 4 tools · 4 read, 0 write · Files & storage, Finance, Maps & location
Test call regimen_describe_factors: worked (999 ms)
How the rating is made
- Answers without login: +30
- Speed of first answer: +10
- Lists tools: +10
- Tool descriptions: +15
- Parameter descriptions: +5
- Read/write annotations: +5
- Safe test call: +20
- More than 80 tools: 0
Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.
Install
Remote URL
https://regimen-nu.vercel.app/mcpTools
4 tools listed at last check
regimen_describe_factorsList the market-condition factors Regimen slices performance by, with units, the upstream operation each is read from, and how it is bucketed. Call this when you need to know which factor keys exist or how to explain a bucket to a user. Takes no arguments, reaches no network, never changes.regimen_evaluate_track_recordAnswer whether a trading strategy’s measured performance is distinguishable from luck. Returns the Probabilistic Sharpe Ratio (the probability the true Sharpe beats a benchmark, corrected for sample length, skew and fat tails), a bootstrap confidence interval, and the Minimum Track Record Length — hregimen_regime_mapBreak a strategy’s returns down by the market conditions that held on each date — volatility, funding, open interest, positioning, sentiment, trend state — and report performance per bucket. Each factor also gets a permutation test: the observed best-to-worst spread is compared against spreads produregimen_self_attackRun Regimen’s own analysis against controls whose answer is known in advance: the strategy’s returns with the edge mathematically removed, and a simulated population of strategies with no edge at all. Returns whether the engine correctly found nothing in them, and where the real strategy’s confidenc
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