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-signal-trackergit 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-signal-tracker)<a href="https://agentmods.dev/skills/rkiding/awesome-finance-skills/alphaear-signal-tracker"><img src="https://agentmods.dev/badge/skills/rkiding/awesome-finance-skills/alphaear-signal-tracker/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-signal-tracker"><img src="https://agentmods.dev/badge/skills/rkiding/awesome-finance-skills/alphaear-signal-tracker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk warn
- 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 | $0.00040 | $0.00434 |
| Opus 5 | $0.00020 | $0.00217 |
| Sonnet 5 | $0.00008 | $0.00087 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
alphaear-signal-tracker 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
2 near-identical copies found in the catalogue:
- alphaear-signal-tracker — 100% identical, 0 lines differ
- AlphaEar Signal Tracker — 86% identical, 16 lines differ
What it actually says
AlphaEar Signal Tracker Skill
Overview
This skill provides logic to track and update investment signals. It assesses how new market information impacts existing signals (Strengthened, Weakened, Falsified, or Unchanged).
Capabilities
1. Track Signal Evolution
1. Track Signal Evolution (Agentic Workflow)
YOU (the Agent) are the Tracker. Use the prompts in references/PROMPTS.md.
Workflow:
- Research: Use FinResearcher Prompt to gather facts/price for a signal.
- Analyze: Use FinAnalyst Prompt to generate the initial
InvestmentSignal. - Track: For existing signals, use Signal Tracking Prompt to assess evolution (Strengthened/Weakened/Falsified) based on new info.
Tools:
- Use
alphaear-searchandalphaear-stockskills to gather the necessary data. - Use
scripts/fin_agent.pyhelper_sanitize_signal_outputif needing to clean JSON.
Key Logic:
- Input: Existing Signal State + New Information (News/Price).
- Process:
- Compare new info with signal thesis.
- Determine impact direction (Positive/Negative/Neutral).
- Update confidence and intensity.
- Output: Updated Signal.
Example Usage (Conceptual):
# This skill is currently a pattern extracted from FinAgent.
# In a future refactor, it should be a standalone utility class.
# For now, refer to `scripts/fin_agent.py`'s `track_signal` method implementation.
Dependencies
agno(Agent framework)sqlite3(built-in)
Ensure DatabaseManager is initialized correctly.
What ships with it
35 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 2.0 KB
- scripts/__init__.py 0 B runs code
- scripts/fin_agent.py 3.8 KB runs code
- scripts/prompts/fin_agent.py 6.6 KB runs code
- scripts/prompts/forecast_analyst.py 1.9 KB runs code
- scripts/prompts/intent_agent.py 2.2 KB runs code
- scripts/prompts/isq_prompt_generator.py 1.8 KB runs code
- scripts/prompts/report_agent.py 18 KB runs code
- scripts/prompts/trend_agent.py 7.4 KB runs code
- scripts/prompts/visualizer.py 2.0 KB runs code
- scripts/schema/isq_template.py 14 KB runs code
- scripts/schema/models.py 6.1 KB runs code
- scripts/tools/__init__.py 448 B runs code
- scripts/tools/toolkits.py 19 KB runs code
- scripts/utils/__init__.py 25 B runs code
- scripts/utils/content_extractor.py 4.7 KB runs code
- scripts/utils/database_manager.py 21 KB runs code
- scripts/utils/hybrid_search.py 8.0 KB runs code
- scripts/utils/json_utils.py 6.2 KB runs code
- scripts/utils/llm/capability.py 2.8 KB runs code
- scripts/utils/llm/factory.py 3.6 KB runs code
- scripts/utils/llm/router.py 2.8 KB runs code
- scripts/utils/logging_setup.py 1.0 KB runs code
- scripts/utils/md_to_html.py 4.8 KB runs code
- scripts/utils/news_tools.py 9.9 KB runs code
- scripts/utils/predictor/evaluation.py 5.6 KB runs code
- scripts/utils/predictor/kline_generate.py 7.6 KB runs code
- scripts/utils/predictor/model/__init__.py 394 B runs code
- scripts/utils/predictor/model/kronos.py 30 KB runs code
- scripts/utils/predictor/model/module.py 22 KB runs code
- scripts/utils/predictor/training.py 18 KB runs code
- scripts/utils/search_tools.py 29 KB runs code
- scripts/utils/sentiment_tools.py 9.9 KB runs code
- scripts/utils/stock_tools.py 9.8 KB runs code
- tests/test_tracker.py 565 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.
- 13d ago First seen · 52 lines · 40 tokens per session scan A f049b077fd8e
alphaear-signal-tracker 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 40 tokens to every session and 434 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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