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alphaear-predictor

alphaear-predictor is a skill for Claude Code, Codex from leecyno1/boutique-skills. It costs 29 tokens per session (522 once invoked), scanned A, a copy of alphaear-predictor, MIT.

A finance forecasting tool that predicts future market prices from historical time-series data and can adjust those predictions using recent news sentiment.

In plain words
What is it for?
Forecasting trends for stocks or other financial instruments over a chosen period and refining the forecast when new news changes the outlook.
Why use it?
It combines numerical market patterns with relevant news, so forecasts do not rely on price history alone.

Skill for Claude CodeCodex

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

not rated 5repo today A scan 29 tokens copy · 100% MIT

Good fit Forecasting trends for stocks or other financial instruments over a chosen period and refining the forecast when new news changes the outlook.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/leecyno1/boutique-skills/alphaear-predictor
View source ↗ leecyno1/boutique-skills
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 leecyno1/boutique-skills --skill alphaear-predictor
Clone the repo
git clone --depth 1 https://github.com/leecyno1/boutique-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 alphaear-predictor

README.md
[![agentmods](https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphaear-predictor/github.svg)](https://agentmods.dev/skills/leecyno1/boutique-skills/alphaear-predictor)
Your own site
<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphaear-predictor"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphaear-predictor/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 alphaear-predictor

Your own site · 80×15
<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphaear-predictor"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphaear-predictor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 522 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.
Origin 100% copy Near-identical to another mod 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 $0.00029 $0.00522
Opus 5 $0.00015 $0.00261
Sonnet 5 $0.00006 $0.00104
Haiku 4.5 $0.00003 $0.00052

Measured 12d ago against content hash cbba615e281b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

alphaear-predictor 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 12d ago.

The scan reads SKILL.md. This mod also ships 32 executable files (scripts/__init__.py, scripts/forecast_agent.py, scripts/json_utils.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

This is a copy

100% identical to alphaear-predictor — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/default/alphaear-predictor/SKILL.md · 64 lines

What it actually says

AlphaEar Predictor Skill

Overview

This skill utilizes the Kronos model (via KronosPredictorUtility) to perform time-series forecasting and adjust predictions based on news sentiment.

Capabilities

1. Forecast Market Trends

1. Forecast Market Trends

Workflow:

  1. Generate Base Forecast: Use scripts/kronos_predictor.py (via KronosPredictorUtility) to generate the technical/quantitative forecast.
  2. Adjust Forecast (Agentic): Use the Forecast Adjustment Prompt in references/PROMPTS.md to subjectively adjust the numbers based on latest news/logic.

Key Tools:

  • KronosPredictorUtility.get_base_forecast(df, lookback, pred_len, news_text): Returns List[KLinePoint].

Example Usage (Python):

from scripts.utils.kronos_predictor import KronosPredictorUtility
from scripts.utils.database_manager import DatabaseManager

db = DatabaseManager()
predictor = KronosPredictorUtility()

# Forecast
forecast = predictor.predict("600519", horizon="7d")
print(forecast)

Configuration

This skill requires the Kronos model and an embedding model.

  1. Kronos Model:
    • Ensure exports/models directory exists in the project root.
    • Place trained news projector weights (e.g., kronos_news_v1.pt) in exports/models/.
    • Or depend on the base model (automatically downloaded).

[!CAUTION] Model Security: This skill loads model weights from exports/models. We use weights_only=True and only scan for the kronos_news_*.pt pattern. Ensure you only place trusted checkpoints in this directory.

  1. Environment Variables:
    • EMBEDDING_MODEL: Path or name of the embedding model (default: sentence-transformers/all-MiniLM-L6-v2).
    • KRONOS_MODEL_PATH: Optional path to override model loading.

Dependencies

  • torch
  • transformers
  • sentence-transformers
  • pandas
  • numpy
  • scikit-learn
Files

What ships with it

34 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. 12d ago First seen · 64 lines · 29 tokens per session scan A cbba615e281b

Subscribe to this mod's changes

alphaear-predictor is a skill published in the GitHub repository leecyno1/boutique-skills (5 stars, last pushed today), licensed MIT. It adds 29 tokens to every session and 522 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to alphaear-predictor, differing in 0 lines, and is treated as a copy.

Analytics and metricsFinance and fintech
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