lstm-price-prediction-guide SKILL.md skillA
lstm-price-prediction-guide from nirholas/three.ws is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add nirholas/three.ws/lstm-price-prediction-guide@git:20261023.22a5a1fPins git:20261023.22a5a1f in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- nirholas/three.ws
- Path
data/skills/analysis/lstm-price-prediction-guide/SKILL.md- Versions recorded
- 2
- Latest version
- git:20261023.22a5a1f, committed Oct 23, 2026
- First version recorded
- May 1, 2026
- Size
- 6,273 bytes
- Repository stars
- 269
- License
- Apache-2.0
Guide to LSTM-based cryptocurrency price prediction. Covers data preprocessing, feature engineering, LSTM architecture, training, evaluation, and deployment. Includes TensorFlow/Keras implementation with technical indicators and sentiment features.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# LSTM Price Prediction Guide A guide to building LSTM (Long Short-Term Memory) neural networks for cryptocurrency price prediction. Covers the full pipeline from data collection to model deployment. ## Reference notebook The companion repo is [nirholas/lstm-bitcoin-prediction.ipynb](https://github.com/nirholas/lstm-bitcoin-prediction.ipynb), a single self-contained Jupyter notebook that predicts the daily BTC/USD close. It fetches 2000 daily candles from the public CryptoCompare `histoday` endpoint (no key), holds out the last 10% by time with no shuffling, builds overlapping 7-day windows normalised to each window's first entry, and trains a Keras `Sequential` of `LSTM(20)`, `Dropout(0.25)`, `Dense(1)` with MAE loss and Adam for 50 epochs at batch size 4 (`np.random.seed(42)`). It then plots actual against predicted prices and daily returns. The repo is proprietary (all rights reserved): read it, do not copy it. The deeper multi-feature pipeline below is a larger design than the notebook. ## Pipeline Overview ``` Data Collection → Feature Engineering → Preprocessing → Model Training → Evaluation → Deployment …
Read the whole file at its exact version.
How to install
mdr add nirholas/three.ws/lstm-price-prediction-guide@sha256:a8b9e1862000dcadThe line at the top of this page pins the label git:20261023.22a5a1f, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_dxnpmgh23ifmtwp6)
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Versions
The registry has recorded 2 versions of this file, between May 1, 2026 and Oct 23, 2026, about one every 175 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261023.22a5a1f latest | 2026-10-23 | 22a5a1f | 6,273 B | A | view · diff |
| git:20260501.87cefc9 | 2026-05-01 | 87cefc9 | 5,489 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6273 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
nirholas/three.ws · 269 stars · license Apache-2.0 · pushed 2026-11-06 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_dxnpmgh23ifmtwp6 GET https://markdownregistry.com/api/v1/resolve?ref=nirholas/three.ws/lstm-price-prediction-guide GET https://markdownregistry.com/api/v1/blob/a8b9e1862000dcad29a80bc01bc2ae275b79e5b61f36f9210e55215cc5367072
Your AI assistant 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.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.