Awesome Finance Skills is a collection of add-ons that give AI agents tools for financial news, market data, sentiment analysis, forecasting, investment signals, and market-impact diagrams. It is for people who want agents to analyze stocks and financial events.
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.
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-litegit clone --depth 1 https://github.com/RKiding/Awesome-finance-skillsWrote 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.
[](https://agentmods.dev/skills/rkiding/awesome-finance-skills/alphaear-deepear-lite)<a href="https://agentmods.dev/skills/rkiding/awesome-finance-skills/alphaear-deepear-lite"><img src="https://agentmods.dev/badge/skills/rkiding/awesome-finance-skills/alphaear-deepear-lite/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.
<a href="https://agentmods.dev/skills/rkiding/awesome-finance-skills/alphaear-deepear-lite"><img src="https://agentmods.dev/badge/skills/rkiding/awesome-finance-skills/alphaear-deepear-lite.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.00226 |
| Opus 5 | $0.00023 | $0.00113 |
| Sonnet 5 | $0.00009 | $0.00045 |
| Haiku 4.5 | $0.00005 | $0.00023 |
Grade A, and why
alphaear-deepear-lite 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 13d ago.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- alphaear-deepear-lite — 100% identical, 0 lines differ
What it actually says
DeepEar Lite Skill
Overview
Fetch high-frequency financial signals, including titles, summaries, confidence scores, and reasoning directly from the DeepEar Lite platform's real-time data source.
Capabilities
1. Fetch Latest Financial Signals
Use scripts/deepear_lite.py via DeepEarLiteTools.
- Fetch Signals:
fetch_latest_signals()- Retrieves all latest signals from
https://deepear.vercel.app/latest.json. - Returns a formatted report of signal titles, sentiment/confidence metrics, summaries, and source links.
- Retrieves all latest signals from
Dependencies
requests,loguru- No local database required for this skill.
Testing
Run the test script to verify the connection and data fetching:
python scripts/deepear_lite.py
What ships with it
1 file 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.
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.
- 13d ago First seen · 33 lines · 46 tokens per session scan A 032ce1e42aed
alphaear-deepear-lite is a skill published in the GitHub repository RKiding/Awesome-finance-skills (3,002 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 226 once invoked, about $0.0002 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 2026-08-30.
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