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/stockbee-20pct-study

@85c6305

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.

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

This session only. Nothing lands on disk.

referencesscoring_system.md

≈560 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Scoring System

The initial implementation uses deterministic scores. Scores are research triage aids, not trade signals.

Continuation Quality Score

continuation_quality_score ranges from 0 to 100.

Component Intent
Catalyst quality Durable revaluation catalysts score higher than no-news pops
Liquidity Higher dollar volume improves execution realism and institutional relevance
Volume shock Volume expansion indicates unusual attention and participation
Close quality Strong closes receive higher continuation score for upside events
Setup context Base breakout and gap-and-go patterns score higher than weak or failed moves
52-week context Upside events near 52-week highs receive additional score
Data quality Missing history, missing volume, and split-like moves reduce confidence
Extension risk Extreme prior extension reduces quality score

Reversal Risk Score

reversal_risk_score ranges from 0 to 100.

Risk increases when:

  • Catalyst is NO_CLEAR_NEWS, LOW_FLOAT_SPECULATION, or CAPITAL_STRUCTURE
  • The event is extremely extended
  • Upside event closes weakly
  • Dollar volume is below the liquidity floor
  • Data quality flags are present

Study Priority Score

study_priority_score ranks which events deserve manual review. A high-priority event is not necessarily a trade; it may be a high-quality example, a dangerous failure, or a useful negative case.

Suggested Human Ratings

Condition Human-facing label
Quality >= 75 and catalyst is durable A_REVALUATION_OR_HIGH_QUALITY_EVENT
Quality >= 60 B_MOMENTUM_EVENT
Reversal risk >= 65 D_LOW_QUALITY_OR_REVERSAL_RISK
Otherwise C_STUDY_ONLY

Handoff Flags

Flag Meaning
stockbee_episodic_pivot Event resembles a Day 1 EP / gap-and-go / base breakout candidate
pead_screener Earnings or guidance catalyst may warrant PEAD-style research
theme_detector Theme or high-priority event may deserve cluster review
edge_candidate_agent Event is strong enough to export as an edge research prompt
parabolic_short_watch Reversal-risk profile is high enough for study-only exhaustion review

Source: SKILL.md on GitHub

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  • 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

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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