news-reaction-failure-analyzer
Judge whether a market FAILED to react to news favorable to a crowded speculative position — step 2 of Jason Shapiro's COT contrarian process. Consumes a cot-contrarian-detector report (or an explicit direction) plus a Claude-curated events JSON, fetches the underlying price series with a documented fallback chain, and produces a fail-closed CONFIRMED / NOT_CONFIRMED / INSUFFICIENT_EVIDENCE verdict using a statistically validated drift-significance test (not a naive failure-ratio, which false-confirms on pure noise). Generic beyond COT — reusable for PEAD and macro-crowding news-failure checks. Use when the user asks to check news-failure confirmation, whether a crowded market "shrugged off" good/bad news, or wants to run Shapiro step 2 on a CROWDED_LONG/CROWDED_SHORT market.
How do I install this agent skill?
npx skills add https://github.com/tradermonty/claude-trading-skills --skill news-reaction-failure-analyzerIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The news-reaction-failure-analyzer skill is a specialized financial tool that evaluates market sentiment using statistical drift-significance tests. It demonstrates robust security practices, including explicit redaction of API credentials, strict validation of external JSON data inputs, and comprehensive automated testing. All network activity is directed toward well-known financial data providers for its documented analytical purpose.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · 1 issue
What does this agent skill do?
News Reaction Failure Analyzer
Overview
Implements step 2 of Jason Shapiro's COT contrarian process: once a market
is flagged as crowded (cot-contrarian-detector, step 1), check whether it
FAILED to react to news that should have rewarded the crowd. A crowded-long
market that doesn't rally on genuinely bullish news, or a crowded-short
market that doesn't sell off on genuinely bearish news, is the core
behavioral tell that the crowd has run out of buying/selling power — this
is the confirmation step that turns "crowded" into a contrarian setup
candidate (steps 3-5, still manual: price-action confirmation, entry, exit).
Why this isn't a naive failure-ratio check: an earlier design flagged
"news failure" whenever fewer than half the relevant events "responded" —
but under pure noise, roughly 69% of individual events fail to respond by
chance, so that rule would CONFIRM on random noise 48-83% of the time
depending on sample size. This skill instead requires the market to have
moved significantly against the crowd's favorable news (a drift-
significance test with a Monte-Carlo-verified null false-positive bound),
never merely "didn't respond enough." See
references/news-failure-patterns.md for the full statistical rationale.
When to Use This Skill
English:
- "Did the market shrug off [event] even though [asset] is crowded long/short?"
- "Run a news-failure check on [symbol]"
- "Is [symbol] confirmed for a Shapiro-style contrarian setup?"
- After
cot-contrarian-detectorflags a market CROWDED_LONG / CROWDED_SHORT and the user wants to move to step 2
Japanese:
- 「この市場は好材料に反応しなかった?」
- 「COTで偏っているこの銘柄のニュース失敗を確認して」
Do NOT use when:
- The market isn't crowded (NEUTRAL classification) — this skill refuses
fail-closed without an explicit
--directionoverride - No curated events JSON exists yet — WebSearch must run first (Phase 2 below); never fabricate events or URLs to get a verdict
Prerequisites
- FMP API Key: Required. Set
FMP_API_KEYor pass--api-key. Used for price data only (stable/historical-price-eod/light) — coverage varies by symbol; seereferences/price-source-map.md. - Python 3.9+ with
requestsinstalled. - WebSearch access to curate the events JSON (Phase 2). Skill degrades gracefully without it (states the limitation; never fabricates events).
- Optional: a
cot-contrarian-detectorJSON report (--detector-json) to auto-resolve symbol + direction, or supply--directionexplicitly.
Workflow
Phase 1: Obtain symbol + direction
From a cot-contrarian-detector report (--detector-json, symbol looked
up in markets[]) or directly from the user (--symbol + --direction).
A NEUTRAL classification, a symbol missing from the report, or a report
older than --max-detector-age-days (default 10) all refuse fail-closed
with a specific reason — only an explicit --direction overrides.
Phase 2: Curate the events JSON via WebSearch
Search news in the evaluation window (--window-days, default 10) using
the 4-tier source hierarchy (issuer/primary → SEC/official stats → wire →
portal — see references/news-failure-patterns.md). Write findings into
an events JSON from references/news-failure-patterns.md's template —
event, event_time (ISO8601 with explicit UTC offset), source_url,
source_tier, expected_impact (BULLISH/BEARISH) per event.
Never fabricate events or URLs. WebSearch unavailable → state it
explicitly; proceed without an events JSON only if the user accepts an
INSUFFICIENT_EVIDENCE result (reason no_events_provided) — the CLI
never raises an exception for a missing events file, it always exits 0
with a documented reason.
Phase 3: Run the CLI
python3 skills/news-reaction-failure-analyzer/scripts/analyze_news_reaction.py \
--symbol B6 --detector-json reports/cot_crowding_2026-07-12.json \
--events-json reports/nrf_events_B6_2026-07-12.json \
--output-dir reports/
The script fetches the price series (documented fallback chain — futures
symbol first, ETF proxy if 402/restricted or rows == 0; see
references/price-source-map.md), computes effective dates / returns /
z-scores per event, clusters events whose 3-trading-day windows overlap
(independence guard), and synthesizes the verdict.
Phase 4: Present verdict + handoff
Present the verdict, aggregate stats (drift_stat, responded_ratio), and
the evidence table (per-event returns/z-scores/reaction labels, with any
dropped_events reasons shown — never silently hidden). If a proxy
(run_context.proxy_used) was used, note the tracking-error caveat.
Emit a handoff block for contrarian-setup-gate (#241, not yet built):
{"news_failure": {"verdict": "CONFIRMED", "confidence": "HIGH", "report_path": "reports/nrf_B6_2026-07-12.json"}}
Output
- JSON:
reports/nrf_<symbol>_<as-of-date>.json—schema_version,symbol,direction,expected_direction,actual_reaction(FAILED_TO_RALLY/FAILED_TO_SELL_OFF/RALLIED/SOLD_OFF/MIXED_REACTION/NO_DATA),verdict,confidence,relevant_events_used,aggregate(mean_z3/drift_stat/responded_ratio),evidence[],dropped_events[],run_context. - Markdown:
reports/nrf_<symbol>_<as-of-date>.md— human-readable verdict, aggregate stats, evidence table, dropped-events table, proxy caveat (if used), and methodology footnote.
Guardrails
- CONFIRMED is not a trade signal. It confirms step 2 of 5 — price- action confirmation (step 3), entry (step 4), and exit (step 5) are still manual and still required before any position.
- INSUFFICIENT_EVIDENCE never advances the pipeline. Fewer than
--min-events(default 3) usable relevant event clusters, a missing detector report, or a detector vintage (data_date) that's missing, unparsable, dated after--as-of, or older than--max-detector-age-days(stale), aNEUTRALclassification without an explicit override, or no working price source all produce this verdict — never a crash, never a forced call on inadequate data. - COT publication lag. COT data is 3-9 days old by the time it's read
(see
cot-contrarian-detector); news-failure evidence should be read in that context, not as same-day confirmation. - Counter-direction events are context only — shown in the evidence
table but excluded from the verdict (only events whose
expected_impactmatches the crowd'sexpected_directioncount). - Proxy-based prices are noted, not hidden. When an ETF proxy was used
(
run_context.proxy_used), the report says so — tracking error, expense drag, and roll-timing differences make the reaction-direction read approximate, not exact. - Residual statistical risk under extreme correlation. The verdict's
null false-CONFIRMED rate is hard-verified under i.i.d. noise (<8%) and
under a realistic residual-correlation stress (AR(1) ρ=0.1, <10%). Under
an intentionally extreme correlation stress (lag-1 ρ=0.3 across
non-clustered event windows — roughly 10x liquid-futures empirical
autocorrelation), the measured null rate rises to ~11-13%. This is a
documented v1 limitation, not a silent gap — see
references/news-failure-patterns.mdfor the full numbers. Users who want the stricter <10% margin even under that stress can pass--drift-z 1.75(at the cost of missing some genuine news-failure signals, not just noise). - Not investment advice. Research/educational purposes only.
Resources
references/news-failure-patterns.md
Full methodology: what qualifies as a relevant event, the 4-tier source hierarchy, worked examples, the events-JSON curation guide + template, and the verdict-threshold rationale (why drift-significance, not a naive ratio; the Monte-Carlo-verified null bounds).
references/price-source-map.md
Per-market price-source fallback chain, verified/402/0-rows status (live-
probed at implementation time), ETF-proxy caveats, and markets with no
viable source (documented no_price_source cases: VX, ZQ, HO, all agri on
this key).
When to Load References
- First use / explaining the methodology: Load
references/news-failure-patterns.md - Explaining why a market has no verdict (no_price_source): Load
references/price-source-map.md - Regular execution: References not needed for the CLI itself — needed for Phase 2 (events curation) and for explaining results to the user
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/tradermonty/claude-trading-skills/news-reaction-failure-analyzer">View news-reaction-failure-analyzer on skillZs</a>