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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.

72

Quality

88%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-structured skill body with an explicit fail-closed workflow, executable CLI guidance, and exemplary reference navigation. The statistical rationale is partly duplicated between the body and the reference file, and Phase 2's events curation would benefit from one concrete inline example.

Suggestions

Trim the 'Why this isn't a naive failure-ratio' paragraph to two or three lines (the false-positive rates and Monte-Carlo detail) and defer the rest to references/news-failure-patterns.md, which already covers it.

Add a minimal inline events-JSON example (one event with event, event_time, source_url, source_tier, expected_impact) to Phase 2 so curation can proceed without loading the reference first.

DimensionReasoningScore

Conciseness

Nearly all content is skill-specific and non-obvious (fail-closed semantics, drift-significance rationale, proxy caveats), but the 'Why this isn't a naive failure-ratio' section spends nine lines on statistics (69% noise-fail rate, 48-83% false-confirms) before deferring to the reference 'for the full statistical rationale' — mild duplication that could be trimmed.

4 / 5

Actionability

Provides a copy-paste-ready CLI invocation with full flags, an explicit output JSON field list, and a concrete handoff JSON block; however, Phase 2 (events curation via WebSearch) names the JSON fields but gives no inline example search query or events-JSON snippet, deferring entirely to the reference template.

4 / 5

Workflow Clarity

Four phases are clearly sequenced with explicit fail-closed validation checkpoints (NEUTRAL classification, stale/missing detector, symbol not in report) and error-recovery feedback loops (WebSearch unavailable → state the limitation, exit 0 with a documented reason, never fabricate events or force a verdict).

5 / 5

Progressive Disclosure

Two one-level-deep references (both verified to exist), each summarized in a Resources section, plus a 'When to Load References' section that states exactly when each is needed and when references are unnecessary — clean overview with scripts kept in a separate bundle.

5 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A highly specific, third-person description that clearly states what the skill does, what it consumes and produces, and exactly when to use it with concrete natural-language triggers. The only weakness is slightly incomplete synonym coverage for how users might phrase a news-failure request.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Consumes a cot-contrarian-detector report', 'fetches the underlying price series with a documented fallback chain', 'produces a fail-closed CONFIRMED / NOT_CONFIRMED / INSUFFICIENT_EVIDENCE verdict' — with comprehensive coverage of inputs, processing, and outputs in third-person voice.

5 / 5

Completeness

Explicitly answers both what (judge news-reaction failure, consume detector report + events JSON, fetch prices, emit verdict) and when ('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').

5 / 5

Trigger Term Quality

Includes natural phrases users would say — 'shrugged off' good/bad news, 'news-failure confirmation', 'Shapiro step 2', CROWDED_LONG/CROWDED_SHORT — but misses common synonyms such as 'ignored news' or 'priced in', so coverage is good rather than exhaustive.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (Shapiro COT contrarian step 2, news-failure confirmation) with distinct trigger terms; the 'reusable for PEAD and macro-crowding' broadening stays within the same well-defined niche, so conflict risk is minimal.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
tradermonty/claude-trading-skills
Reviewed

Table of Contents

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