# RKiding/Awesome-finance-skills

A collection of Awesome Finance Agent Skills for free and easy to start | 一系列开源免费的金融分析Agent Skills

Repository: https://github.com/RKiding/Awesome-finance-skills
Canonical: https://ross.abutalabs.com/products/awesome-finance-skills
Language: Python
License: Apache-2.0
License Family: permissive
Topics: agent, agent-skills, finances, fintech
Last push: 2026-03-29T05:03:47+00:00

## Health v2 (maintenance only)
Score: 49/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 74, release rhythm 35, longevity 15
- inputs: {"age_days": 214, "days_push": 157, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2812, forks 367 (observed 2026-08-28T04:07:23.727835+00:00)

## What it is
A curated collection of plug-and-play Agent Skills that equip LLM-based AI agents with financial analysis capabilities, including real-time news aggregation, stock data access, sentiment analysis, market prediction, and report generation. Skills are installable via npx or manual copy into agent frameworks like OpenCode and Antigravity.

## Use cases
- add finance skills to my AI agent
- analyze how news events affect stock markets
- get real-time financial news from multiple sources
- forecast stock prices with AI
- run sentiment analysis on financial headlines
- generate professional investment reports with an LLM
- visualize market impact transmission chains
- track investment signals over time

## When to choose
- you use an agent framework like OpenCode, Antigravity, or Claude and want instant finance capabilities
- you need free, open-source financial news, stock data, and sentiment tools for LLM agents
- you want news-aware market prediction and report generation without building skills from scratch

## When to avoid
- you need a standalone production trading system rather than agent skills
- your agent framework is not among the supported integrations
- you require guaranteed data accuracy or regulated financial advice

## Facets
- artifact type: learning-resource
- maturity: active
- function: agent-framework, rag, data-visualization, machine-learning, nlp, search-engine, web-scraping, trading, sdk
- domain: fintech, artificial-intelligence, large-language-models, data-visualization, analytics, developer-tools
- platform: python, cli, cross-platform
- tags: agent-skills, finance, stock-analysis, sentiment-analysis, market-prediction, financial-news, llm-skills, awesome-list, plug-and-play, time-series-forecasting, ai-agents

## Member repositories
- RKiding/Awesome-finance-skills (main) score 49

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:23.727835+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:13:31.260534+00:00, confidence not recorded.
  - readme: https://github.com/RKiding/Awesome-finance-skills (fetched 2026-08-28T04:07:23.727835+00:00, sha 102713a1c138)
- Data as of 2026-08-30T08:39:29.467469+00:00.