What problem does it solve?
Crowded speculative positioning alone is not a contrarian signal — you need evidence the market has stopped rewarding the crowd's direction. This Skill automates step 2 of Jason Shapiro's COT contrarian process by statistically testing whether a market failed to react to news that should have favored the crowded side, avoiding naive failure-ratio rules that false-confirm on pure noise.
Core Features & Use Cases
- Statistically validated verdicts: Produces a fail-closed CONFIRMED / NOT_CONFIRMED / INSUFFICIENT_EVIDENCE verdict using a drift-significance test with Monte-Carlo-verified false-positive bounds, plus event clustering to guard independence.
- Robust price sourcing: Fetches price series from the FMP API with a documented per-symbol fallback chain (futures first, ETF proxy on 402 or empty responses) and explicit proxy-use caveats.
- Fail-closed guardrails: Refuses to produce verdicts on stale or NEUTRAL detector reports, missing events, or markets with no viable price source — never crashes or fabricates data.
- Use Case: After cot-contrarian-detector flags GBP futures (B6) as CROWDED_LONG, curate recent bullish news events via web search, then run the analyzer to check whether the market shrugged them off before considering a contrarian short setup.
Quick Start
Run a news-failure check on symbol B6 using my cot-contrarian-detector report and a curated events JSON to see if the crowded-long market failed to rally on bullish news.