Agent Skillshimself65/finance-skills › finance-sentiment

finance-sentiment

GitHub

调用 Adanos Finance API 获取股票在 Reddit、X.com、新闻及 Polymarket 的跨平台情绪数据,支持查询热度、提及量及多源对比,仅供研究参考。

plugins/data-providers/skills/finance-sentiment/SKILL.md himself65/finance-skills

Trigger Scenarios

查询特定股票的社会媒体热度或提及量 对比不同平台(如 Reddit 与 X)的股票情绪一致性 查看 Polymarket 上针对某公司的投注数量 获取股票的多源情绪快照或看涨百分比

Install

npx skills add himself65/finance-skills --skill finance-sentiment -g -y
More Options

Non-standard path

npx skills add https://github.com/himself65/finance-skills/tree/main/plugins/data-providers/skills/finance-sentiment -g -y

Use without installing

npx skills use himself65/finance-skills@finance-sentiment

指定 Agent (Claude Code)

npx skills add himself65/finance-skills --skill finance-sentiment -a claude-code -g -y

安装 repo 全部 skill

npx skills add himself65/finance-skills --all -g -y

预览 repo 内 skill

npx skills add himself65/finance-skills --list

SKILL.md

Frontmatter
{
    "name": "finance-sentiment",
    "description": "Fetch structured stock sentiment across Reddit, X.com, news, and Polymarket using the Adanos Finance API. Use this skill whenever the user asks how much people are talking about a stock, how hot a ticker is on social platforms, how many Polymarket bets exist for a company, whether sources are aligned, or to compare stock sentiment across multiple tickers. Triggers include: \"social sentiment on TSLA\", \"how hot is NVDA on X.com\", \"how many Reddit mentions does AAPL have\", \"compare sentiment on AMD vs NVDA\", \"how many Polymarket bets on Microsoft\", \"is Reddit aligned with X on META\", \"stock buzz\", \"bullish percentage\", and any mention of cross-source stock sentiment research. This skill is READ-ONLY and does not place trades or modify anything."
}

Finance Sentiment Skill

Fetches structured stock sentiment from the Adanos Finance API.

This skill is read-only. It is designed for research questions that are easier to answer with normalized sentiment signals than with raw social feeds.

Use it when the user wants:

  • cross-source stock sentiment
  • Reddit/X.com/news/Polymarket comparisons
  • buzz, bullish percentage, mentions, trades, or trend
  • a quick answer to "what is the market talking about?"

Step 1: Ensure the API Key Is Available

Current environment status:

!`python3 - <<'PY'
import os
print("ADANOS_API_KEY_SET" if os.getenv("ADANOS_API_KEY") else "ADANOS_API_KEY_MISSING")
PY`

If ADANOS_API_KEY_MISSING, ask the user to set:

export ADANOS_API_KEY="sk_live_..."

Use the key via the X-API-Key header on all requests.

Base docs:

https://api.adanos.org/docs

Step 2: Identify What the User Needs

Match the request to the lightest endpoint that answers it.

User Request Endpoint Pattern Notes
"How much are Reddit users talking about TSLA?" /reddit/stocks/v1/compare Use mentions, buzz_score, bullish_pct, trend
"How hot is NVDA on X.com?" /x/stocks/v1/compare Use mentions, buzz_score, bullish_pct, trend
"How many Polymarket bets are active on Microsoft?" /polymarket/stocks/v1/compare Use trade_count, buzz_score, bullish_pct, trend
"Compare sentiment on AMD vs NVDA" compare endpoints for the requested sources Batch tickers in one request
"Is Reddit aligned with X on META?" Reddit compare + X compare Compare bullish_pct, buzz_score, trend
"Give me a full sentiment snapshot for TSLA" compare endpoints across Reddit, X.com, news, Polymarket Synthesize cross-source view
"Go deeper on one ticker" /stock/{ticker} detail endpoint Use only when the user asks for expanded detail

Default lookback:

  • use days=7 unless the user asks for another window

Ticker count:

  • use compare endpoints for 1..10 tickers

Step 3: Execute the Request

Use curl with X-API-Key. Prefer compare endpoints because they are compact and batch-friendly.

Single-source examples

curl -s "https://api.adanos.org/reddit/stocks/v1/compare?tickers=TSLA&days=7" \
  -H "X-API-Key: $ADANOS_API_KEY"
curl -s "https://api.adanos.org/x/stocks/v1/compare?tickers=NVDA&days=7" \
  -H "X-API-Key: $ADANOS_API_KEY"
curl -s "https://api.adanos.org/polymarket/stocks/v1/compare?tickers=MSFT&days=7" \
  -H "X-API-Key: $ADANOS_API_KEY"

Multi-source snapshot for one ticker

curl -s "https://api.adanos.org/reddit/stocks/v1/compare?tickers=TSLA&days=7" -H "X-API-Key: $ADANOS_API_KEY"
curl -s "https://api.adanos.org/x/stocks/v1/compare?tickers=TSLA&days=7" -H "X-API-Key: $ADANOS_API_KEY"
curl -s "https://api.adanos.org/news/stocks/v1/compare?tickers=TSLA&days=7" -H "X-API-Key: $ADANOS_API_KEY"
curl -s "https://api.adanos.org/polymarket/stocks/v1/compare?tickers=TSLA&days=7" -H "X-API-Key: $ADANOS_API_KEY"

Multi-ticker comparison

curl -s "https://api.adanos.org/reddit/stocks/v1/compare?tickers=AMD,NVDA,META&days=7" \
  -H "X-API-Key: $ADANOS_API_KEY"

Key rules

  1. Prefer compare endpoints over stock detail endpoints for quick research.
  2. Use only the sources needed to answer the question.
  3. For Reddit, X.com, and news, the volume field is mentions.
  4. For Polymarket, the activity field is trade_count.
  5. Treat missing source data as "no data", not bearish or neutral.
  6. Never execute trades or convert the result into trading instructions.

Step 4: Present the Results

When reporting a single source, prioritize exactly these fields:

  • Buzz
  • Bullish %
  • Mentions or Trades
  • Trend

Example:

TSLA on Reddit, last 7 days
- Buzz: 74.1/100
- Bullish: 31%
- Mentions: 647
- Trend: rising

When reporting multiple sources for one ticker:

  • show one block per source
  • then add a short synthesis:
    • aligned bullish
    • aligned bearish
    • mixed / diverging

When comparing multiple tickers:

  • rank by the metric the user cares about
  • default to buzz_score
  • call out large gaps in bullish_pct or trend

Do not overstate precision. These are research signals, not trade instructions.


Reference Files

  • references/api_reference.md - endpoint guide, field meanings, and example workflows

Read the reference file when you need the exact field names, query parameters, or recommended answer patterns.

Version History

  • fa526ce Current 2026-07-25 10:58

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Metadata

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Version
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Hash
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Indexed
2026-07-25 10:58

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