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us-market-bubble-detector

Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.

69

Quality

87%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

81%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.

The body delivers an exceptionally actionable, well-sequenced evaluation workflow with real validation gates and checklists. Its main weakness is verbosity from redundant v2.0/v2.1 revision commentary repeated across four sections, plus incomplete disclosure of the bundle — the executable scripts/bubble_scorer.py is never referenced from SKILL.md.

Suggestions

Collapse the four separate v2.0→v2.1 change-log sections ('Key Revisions in v2.1', 'Key Change in v2.1', 'Summary: Essence of v2.1 Revision', 'Version History'/'Reason for v2.1 Revision') into a single short changelog note; the same points (stricter +3 qualitative cap, new Elevated Risk phase, confirmation-bias checklist) are currently stated at least four times.

Reference scripts/bubble_scorer.py in SKILL.md (e.g. in Phase 2 or the Reference Documents section) and note when to run it versus scoring manually — the script and its contract tests exist in the bundle but are undiscoverable from the skill body.

Move the detailed per-stage Recommended Actions and composite short-selling conditions into references/quick_reference_en.md (they are operational lookup material, not needed on first read), keeping only the phase/risk-budget table inline.

DimensionReasoningScore

Conciseness

The core scoring tables, checklists, and data sources are dense and useful, but the ~540-line body repeats the same v2.0→v2.1 change commentary in at least four places ('Key Revisions in v2.1', 'Key Change in v2.1' under Phase 4, 'Summary: Essence of v2.1 Revision', 'Version History'/'Reason for v2.1 Revision'), and embeds time-stamped version metadata ('v2.0 (Oct 27, 2025)', 'v2.1 (Nov 3, 2025)') outside any deprecated/old-patterns section. This fits 'Mostly efficient but includes some unnecessary explanation or could be tightened' rather than 2, since the padding is confined to revision meta-commentary and the operational content itself is not padded with concepts Claude already knows.

3 / 5

Actionability

For an instruction-only skill the guidance is fully executable: exact numeric thresholds per indicator ('2 points: P/C < 0.70', 'VIX < 12 AND major index within 5% of 52-week high'), concrete collection commands ('web_search "FINRA margin debt latest"', source URLs), valid vs. invalid evidence examples, and a complete copy-paste output report template. It is not a 4 because the common cases are covered end-to-end with no gaps a reader would need to fill in.

5 / 5

Workflow Clarity

The process is a strictly ordered sequence with explicit validation checkpoints: Phase 1 data collection gated by '⚠️ CRITICAL: Do NOT proceed with evaluation without Phase 1 data collection', a confirmation-bias checklist before any qualitative points, self-check questions that force a score to 0, an implementation checklist, and a Common Failures section with ❌/✅ error-recovery examples. This matches the top anchor 'Clear sequence with explicit validation steps; feedback loops for error recovery; checklists for complex processes'.

5 / 5

Progressive Disclosure

All five referenced files exist (references/implementation_guide.md, bubble_framework.md, historical_cases.md, quick_reference.md, quick_reference_en.md) and are clearly signaled with a 'When to Load References' section — good one-level-deep structure. It is not a 5 because the bundle's scripts/bubble_scorer.py and its tests are never mentioned anywhere in SKILL.md, leaving an executable component undiscoverable, and a substantial amount of stage-by-stage action detail (Recommended Actions by Bubble Stage, composite short-selling conditions) is inlined that arguably belongs in the quick-reference files; it is not a 3 because the references that are used are clearly signaled and well-organized.

4 / 5

Total

17

/

20

Passed

Description

88%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 strong description: it states concrete capabilities with named metrics, uses third person, and closes with an explicit 'Use when' trigger clause covering three natural use cases. The only weaknesses are a few missing natural trigger variations (e.g. 'are we in a bubble') and minor overlap risk from the broader 'valuation concerns'/'profit-taking timing' triggers.

DimensionReasoningScore

Specificity

The description lists multiple concrete capabilities with named instruments — 'Evaluates market bubble risk through quantitative data-driven analysis', 'Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data)', 'mandatory data collection and mechanical scoring' — which is comprehensive coverage of what the skill does. It is not a 4 because there are no real gaps: the analysis method, the specific metrics, the adjustment mechanism, and the output (scoring for investment decisions) are all explicitly stated.

5 / 5

Completeness

It explicitly answers both questions: the 'what' is concrete ('Evaluates market bubble risk... Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data)... mechanical scoring') and the 'when' is explicit with concrete trigger phrases ('Use when user asks about bubble risk, valuation concerns, or profit-taking timing'). It is not a 4 because the 'when' clause is already explicit and trigger-phrased, not merely implied or generic.

5 / 5

Trigger Term Quality

The 'Use when' clause covers natural phrases users would say — 'bubble risk', 'valuation concerns', 'profit-taking timing' — which are good trigger keywords. It is not a 5 because common variations users would naturally utter are missing, e.g. 'Are we in a bubble?', 'is the market overvalued/overheated', 'should I take profits', or 'market euphoria'; it is not a 3 because the terms present are genuinely natural rather than technical jargon and cover the skill's three main use cases.

4 / 5

Distinctiveness Conflict Risk

The bubble-detection niche is clear and 'bubble risk' triggers are distinct, matching the anchor 'Mostly distinct; minor overlap risk with closely related skills'. It is not a 5 because the broader triggers 'valuation concerns' and 'profit-taking timing' could also fire for generic valuation-analysis or investment-advice skills; it is not a 3 because the core framing (Minsky/Kindleberger bubble framework, named sentiment/leverage metrics) is unmistakably specific.

4 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (546 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
tradermonty/claude-trading-skills
Reviewed

Table of Contents

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