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alphaear-signal-tracker

v1.0.0

Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if th...

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by @zhouzhonglu8-png·MIT-0
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License
MIT-0
最后更新
2026/4/1
安全扫描
VirusTotal
无害
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OpenClaw
可疑
medium confidence
The skill's stated purpose (finance signal tracking) generally matches its code and prompts, but there are transparency and scope mismatches that warrant caution (network scraping, local DB writes, and implicit config/file access not declared in the manifest).
评估建议
This skill implements an agentic financial research and signal-tracking pipeline that will: fetch web pages and news, call external data/tool skills (alphaear-search, alphaear-stock), and read/write a local sqlite database. Before installing/running: 1) Review scripts/utils/database_manager.py and scripts/utils/news_tools.py to confirm where the DB files live and what data is written (the toolkits perform SQL UPDATEs). 2) Expect runtime network requests to arbitrary URLs (fetch_news_content) and...
详细分析 ▾
✓ 用途与能力
Name/description match what the package does: the code and prompts implement research, signal parsing, tracking, and reporting for financial signals. Declared dependencies ('agno' and sqlite3) align with the toolkit and DB usage seen in scripts/tools/toolkits.py and scripts/fin_agent.py.
⚠ 指令范围
Prompts and SKILL.md instruct agents to fetch web content, call tool methods like search_ticker/get_stock_price, and run multi-step agentic workflows. The prompts require: (a) fetching arbitrary URLs and webpage content (scripts/tools/toolkits.py -> fetch_news_content), (b) updating a local database (enrich_news_content executes SQL UPDATE on daily_news), and (c) strict requirements to call tools 'for EVERY mentioned company'. These actions go beyond pure 'analysis' and involve network I/O and modifications to local storage; the SKILL.md does not explicitly call out these side-effects in a security-transparent way.
✓ 安装机制
No external install/downloads are specified (no install spec). All code is packaged with the skill, so there is no high-risk remote fetch during installation. This reduces supply-chain concerns, though running the included code will perform network I/O at runtime.
⚠ 凭证需求
The skill declares no required environment variables or config paths, but several code paths access local files and config directories (e.g., scripts/schema/isq_template.py -> load_templates_from_config reads config/isq_templates or a given config path) and a DatabaseManager (scripts/fin_agent.py, scripts/tools/toolkits.py) is used for lookups and writes. The absence of declared config/DB paths or any credential requirements reduces transparency: the skill may attempt to read local config files or create/update a local sqlite DB without notifying the user or declaring where data will be stored.
✓ 持久化与权限
The skill does not request 'always: true' and does not appear to modify other skills or system-wide agent settings. However it does perform persistent actions within its own domain (reading template JSON from config paths and writing to a local DB table daily_news). That behavior is expected for a tracker/reporting tool but should be reviewed before running with sensitive data or in privileged environments.
⚠ scripts/utils/predictor/evaluation.py:59
Dynamic code execution detected.
⚠ scripts/utils/predictor/training.py:308
Dynamic code execution detected.
安全有层次，运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发，无需署名。

运行时依赖

无特殊依赖

版本

latestv1.0.02026/4/1

AlphaEar Signal Tracker Skill v1.0.0 - Initial release of signal tracking logic for finance investment signals. - Tracks and updates investment signal states (Strengthened, Weakened, Falsified, or Unchanged) based on new market information. - Outlines an agentic workflow using research, analysis, and signal evolution tracking prompts. - Integrates with `alphaear-search` and `alphaear-stock` for data gathering. - Depends on `agno` agent framework and uses a `DatabaseManager` with `sqlite3`.

● 无害

安装命令 点击复制

官方npx clawhub@latest install alphaear-signal-tracker
镜像加速npx clawhub@latest install alphaear-signal-tracker --registry https://cn.clawhub-mirror.com

技能文档

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-search and alphaear-stock skills to gather the necessary data.
  • Use scripts/fin_agent.py helper _sanitize_signal_output if needing to clean JSON.

Key Logic:

  • Input: Existing Signal State + New Information (News/Price).
  • Process:
1. Compare new info with signal thesis. 2. Determine impact direction (Positive/Negative/Neutral). 3. 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.

数据来源：ClawHub ↗ · 中文优化：龙虾技能库
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