stockbee-episodic-pivot-analyzer

stockbee-episodic-pivot-analyzer is a skill for Claude Code, Codex from tradermonty/claude-trading-skills. It costs 122 tokens per session (1,216 once invoked), scanned A, original, MIT.

A stock-market analysis tool for Day 1 Episodic Pivots: large moves caused by events such as earnings, acquisitions, regulatory decisions, contracts, or product launches. It combines the event quality with price and trading-volume evidence to classify candidates.

In plain words
What is it for?
Use it to evaluate supplied catalyst data, combine event analysis with price-and-volume results, and pass stronger earnings or guidance candidates to another screening step.
Why use it?
It helps separate candidates with strong news and market confirmation from those that should only be watched. It is for analysis, not for placing trades.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 2.8krepo +32 today A scan Socket: passSnyk: passSkillSpector: pass 122 tokens original MIT

Good fit Use it to evaluate supplied catalyst data, combine event analysis with price-and-volume results, and pass stronger earnings or guidance candidates to another screening step.

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Install with agentmods
npx agentmods add skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer
About the project

Claude Trading Skills is a collection of Claude Code workflows for individual investors who want structured market analysis, charting, economic-calendar review, screening, trade planning, journaling, and risk management. It is designed for people using long-term investing, ETFs, dividend stocks, and disciplined swing trading, and the catalogue entries package these workflows as skills, agents, commands, settings, and instructions.

tradermonty/claude-trading-skills · 2,813 stars · on GitHub · tradermonty.github.io

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tradermonty/claude-trading-skills --skill stockbee-episodic-pivot-analyzer
Clone the repo
git clone --depth 1 https://github.com/tradermonty/claude-trading-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for stockbee-episodic-pivot-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer/github.svg)](https://agentmods.dev/skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer)
Your own site
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for stockbee-episodic-pivot-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/stockbee-episodic-pivot-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,216 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 5 Sept 2026
  • Snyk pass 5 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00122 $0.01216
Opus 5 $0.00061 $0.00608
Sonnet 5 $0.00024 $0.00243
Haiku 4.5 $0.00012 $0.00122

Measured 9d ago against content hash b5eac42930c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

stockbee-episodic-pivot-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/analyze_ep.py, scripts/tests/test_analyze_ep.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/stockbee-episodic-pivot-analyzer/SKILL.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Stockbee Episodic Pivot Analyzer

Classify Day 1 Episodic Pivot (EP) candidates using both catalyst quality and price/volume confirmation. The skill is a candidate-quality analyzer, not an execution engine.

When to Use

  • The user asks for Pradeep Bonde / Stockbee style EP candidates
  • The user provides earnings, guidance, M&A, FDA, analyst, contract, product, short-squeeze, or theme/news events
  • The user wants to separate ACTIONABLE_DAY1 candidates from DELAYED_EP_WATCH names
  • The user wants to hand strong earnings/guidance EPs into pead-screener
  • The user wants to combine catalyst analysis with stockbee-momentum-burst-screener price/volume output

Prerequisites

  • Python 3.10+
  • Optional: FMP API key for OHLCV/profile enrichment
  • One of:
    • Catalyst/events JSON
    • earnings-trade-analyzer JSON output
    • Catalyst JSON plus stockbee-momentum-burst-screener JSON enrichment
  • This skill does not fetch or discover news by itself. If the catalyst is not supplied, first gather the event/news context using the user's preferred news or research process.

Workflow

Step 1: Prepare Candidate Inputs

Use one or more of these input modes.

Mode A — Catalyst/event JSON:

{
  "events": [
    {
      "symbol": "ABC",
      "event_date": "2026-04-25",
      "catalyst_type": "guidance_raise",
      "headline": "ABC raises FY guidance after record demand",
      "summary": "Management raised revenue and EPS guidance."
    }
  ]
}

Mode B — Earnings pipeline:

Use the JSON produced by earnings-trade-analyzer.

Mode C — Price/volume enrichment:

Pass a stockbee-momentum-burst-screener JSON report to reuse day-gain, volume, close-location, and risk-distance fields.

Step 2: Run the Analyzer

# Catalyst JSON + offline OHLCV
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
  --events-json data/catalysts.json \
  --prices-json data/daily_ohlcv.json \
  --output-dir reports/

# Earnings pipeline input
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
  --earnings-json reports/earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.json \
  --output-dir reports/

# Catalyst JSON + Stockbee momentum enrichment
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
  --events-json data/catalysts.json \
  --momentum-json reports/stockbee_momentum_burst_YYYY-MM-DD_HHMMSS.json \
  --output-dir reports/

Read the full file on GitHub · 119 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 119 lines · 122 tokens per session scan A b5eac42930c8

Subscribe to this mod's changes

stockbee-episodic-pivot-analyzer is a skill published in the GitHub repository tradermonty/claude-trading-skills (2,813 stars, last pushed today), licensed MIT. It adds 122 tokens to every session and 1,216 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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