Home / tradermonty / claude-trading-skills · skills/stockbee-setup-fluency-trainer/SKILL.md · GitHub

stockbee-setup-fluency-trainer skillA

stockbee-setup-fluency-trainer is agent-read markdown (skill) from tradermonty/claude-trading-skills: Build a Stockbee-style setup model book from momentum-burst screener candidates, then update 3-day and 5-day forward outcomes with MFE/MAE, stop-hit status, outcome tags, and cohort statistics. Use when the user wants to study Stockbee Momentum Burst examples, track failed candidates, build setup fluency, review A/B setup quality, or convert screener outputs into a learning loop rather than immediate trade signals..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Stockbee Setup Fluency Trainer

Build and maintain a model book for Stockbee-style Momentum Burst setups. This skill turns daily screener candidates into structured study records, updates them after the 3-day and 5-day windows mature, and summarizes which setup features are working or failing.

## When to Use

- User wants to study Stockbee Momentum Burst setups systematically
- User asks to build a model book from `stockbee-momentum-burst-screener` output
- User wants to review failed candidates, missed trades, or A/B setup quality
- User wants 3-day / 5-day forward returns, MFE, MAE, and stop-hit outcomes
- User wants to improve setup recognition before increasing position size
- User asks which Stockbee tags should be promoted, downgraded, or filtered

## Prerequisites

- Python 3.10+
- A `stockbee-momentum-burst-screener` JSON report, or compatible candidate JSON
- Optional: FMP API key for outcome updates when offline OHLCV JSON is not supplied
- Recommended local state path: `state/stockbee/model_book.jsonl`

## Workflow

### Step 1: Ingest Momentum Burst Candidates

Run after the Stockbee Momentum Burst screener has produced a JSON report.

```bash
…

Read the whole file at its exact version.

How to install

Latest version
mdr add tradermonty/claude-trading-skills/stockbee-setup-fluency-trainer@git:20260628.fc9c3f9
Exact content
mdr add tradermonty/claude-trading-skills/stockbee-setup-fluency-trainer@sha256:ae45d220f94c0ad0

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

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Versions

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git:20260628.fc9c3f9 latest2026-06-28 fc9c3f9 4,866 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (4866 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

tradermonty/claude-trading-skills · 2,885 stars · license MIT · pushed 2026-09-24 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_pcjk2npy5yhnwvbr
GET https://markdownregistry.com/api/v1/resolve?ref=tradermonty/claude-trading-skills/stockbee-setup-fluency-trainer
GET https://markdownregistry.com/api/v1/blob/ae45d220f94c0ad096b08080ed4d756f2886a8cc3738003e79b7b5083fd70003

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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