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-searchgit 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-search)<a href="https://agentmods.dev/skills/rkiding/awesome-finance-skills/alphaear-search"><img src="https://agentmods.dev/badge/skills/rkiding/awesome-finance-skills/alphaear-search/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-search"><img src="https://agentmods.dev/badge/skills/rkiding/awesome-finance-skills/alphaear-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00047 | $0.00299 |
| Opus 5.5 | $0.00019 | $0.00120 |
| Sonnet 5.5 | $0.00009 | $0.00060 |
| Haiku 4.5 | $0.00005 | $0.00030 |
Grade A, and why
alphaear-search 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 2mo 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-search — 100% identical, 0 lines differ
What it actually says
AlphaEar Search Skill
Overview
Unified search capabilities: web search (Jina/DDG/Baidu) and local RAG search.
Capabilities
1. Web Search
Use scripts/search_tools.py via SearchTools.
- Search:
search(query, engine, max_results)- Engines:
jina,ddg,baidu,local. - Returns: JSON string (summary) or List[Dict] (via
search_list).
- Engines:
- Smart Cache (Agentic): If you want to avoid redundant searches, use the Search Cache Relevance Prompt in
references/PROMPTS.md. Read the cache first and decide if it's usable. - Aggregate:
aggregate_search(query)- Combines results from multiple engines.
2. Local RAG
Use scripts/hybrid_search.py or SearchTools with engine='local'.
- Search: Searches local
daily_newsdatabase.
Dependencies
duckduckgo-search,requestsscripts/database_manager.py(search cache & local news)
What ships with it
12 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.
- references/PROMPTS.md 679 B
- scripts/__init__.py 0 B runs code
- scripts/content_extractor.py 4.7 KB runs code
- scripts/database_manager.py 5.8 KB runs code
- scripts/hybrid_search.py 8.0 KB runs code
- scripts/llm/__init__.py 0 B runs code
- scripts/llm/capability.py 2.8 KB runs code
- scripts/llm/factory.py 3.6 KB runs code
- scripts/llm/router.py 2.8 KB runs code
- scripts/search_tools.py 22 KB runs code
- scripts/sentiment_tools.py 9.9 KB runs code
- tests/test_search.py 861 B runs code
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.
- 2mo ago First seen · 36 lines · 47 tokens per session scan A 979d1d6887d8
alphaear-search is a skill published in the GitHub repository RKiding/Awesome-finance-skills (3,100 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 47 tokens to every session and 299 once invoked, about $0.0002 per session on Opus 5.5. 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.
alphaear-search compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| alphaear-searchRKiding/Awesome-finance-skills | Skill | 3.1k | 7mo ago | Apache-2.0 | A | 47 | Claude Code, Codex |
| tinker-training-costsynthetic-sciences/openscience | Skill | 4.3k | 2d ago | Apache-2.0 | A | 55 | Claude Code, Codex |
| check-modelginlix-ai/LangAlpha | Skill | 2.2k | today | Apache-2.0 | A | 72 | Claude Code, Codex |
| check-deckginlix-ai/LangAlpha | Skill | 2.2k | today | Apache-2.0 | A | 63 | Claude Code, Codex |
| chart-annotationginlix-ai/LangAlpha | Skill | 2.2k | today | Apache-2.0 | A | 43 | Claude Code, Codex |
| impact-analysisginlix-ai/LangAlpha | Skill | 2.2k | today | Apache-2.0 | A | 56 | Claude Code, Codex |
| trade-pitchginlix-ai/LangAlpha | Skill | 2.2k | today | Apache-2.0 | A | 61 | Claude Code, Codex |