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/stockbee-20pct-study

@85c6305
by tradermontytradermonty/claude-trading-skills2.9k stars
663

Build and maintain a Stockbee-style daily 20% mover study for US equities by scanning +20%/-20% movers, classifying catalysts and setup context, updating forward outcomes, and summarizing cohort patterns. Use when the user asks to run a daily 20% study, backfill historical 20% movers, find recurring edge patterns, or build a model book of explosive market moves.

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Use this Skill: https://skilld.dev/gh/tradermonty/claude-trading-skills/stockbee-20pct-study

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referencescatalyst_taxonomy.md

≈567 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Catalyst Taxonomy

Upside and Downside Catalyst Labels

Label Use when
EARNINGS_REVALUATION Earnings, revenue, EPS, margin, or business results triggered a major repricing
GUIDANCE_RAISE Management raised outlook, forecast, or long-term targets
M&A Acquisition, merger, takeover, buyout, strategic alternative, or asset sale
FDA_CLINICAL FDA, clinical trial, PDUFA, approval, rejection, or biotech study data
CONTRACT_ORDER Large contract, government award, partnership, supply agreement, or major customer win
ANALYST_UPGRADE Analyst upgrade, initiation, or material target-price change
SHORT_SQUEEZE Short-interest, low float, borrow stress, squeeze narrative, or forced covering appears central
THEME_SYMPATHY Move is primarily linked to a broader sector or theme cluster
CAPITAL_STRUCTURE Offering, warrant, reverse split, convertible, ATM, recapitalization, or dilution issue
LOW_FLOAT_SPECULATION Low-float / low-liquidity speculative burst without durable fundamental evidence
NO_CLEAR_NEWS No structured catalyst is available or the move is price-only at the time of classification

Classification Rules

  • Prefer structured catalyst data over price-only inference.
  • Use NO_CLEAR_NEWS rather than hallucinating a catalyst.
  • Keep confidence low when the text source is weak, vague, or stale.
  • Classify the first-order catalyst, not every related news item.
  • Allow human override in human_review.label_override when manual research finds a better label.

Theme Context

Theme fields are separate from catalyst labels. A stock can be EARNINGS_REVALUATION and still belong to an AI infrastructure cluster. Use THEME_SYMPATHY only when the theme itself appears to be the primary driver.

Risk Flags Often Associated With Catalysts

Catalyst Common risk
FDA_CLINICAL Binary-event reversal after data details are digested
SHORT_SQUEEZE Violent reversal and borrow/locate constraints
CAPITAL_STRUCTURE Dilution, warrant overhang, reverse-split distortions
LOW_FLOAT_SPECULATION Low liquidity, wide spreads, gap risk
NO_CLEAR_NEWS Unexplained move, rumor risk, poor repeatability

Source: SKILL.md on GitHub

Third-party checks

No alerts3d3 checks · Risk SAFE
  • Gen Agent Trust Hub3d

    The skill is a comprehensive market research tool designed to analyze and study significant price movements in US equities. It retrieves market data and news from the Financial Modeling Prep (FMP) API, a legitimate financial data service, or processes local JSON data. The skill adheres to security best practices by managing API credentials through environment variables and command-line arguments, and it contains no evidence of malicious behavior, obfuscation, or unauthorized system access.

  • Socket3d

    No alerts

  • Snyk3d

    Risk: LOW · No issues

Provenance

Signed by skilld at 85c6305. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 18 hours ago.

Activeupdated 3 months ago

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