Generated banner for Finance Sentiment
Generated logo for Finance Sentiment

Finance Sentiment

Alex YangCommunityCreated by Alex Yang

  • Skill
  • Tool integration
  • Data and AI
  • MIT
  • No issues found

From the author

Fetch normalized stock sentiment across Reddit, X.com, financial news, and Polymarket from the Adanos Finance API: buzz score, bullish percentage, mention or trade counts, and trend. Use this skill whenever the user asks how much a stock is being discussed or how hot it is on social platforms, how many Reddit mentions or Polymarket bets a company has, whether Reddit, X, and news agree, or wants to compare stock buzz and sentiment across tickers. Read-only: it never places trades or modifies anything.
— the description by Alex Yang

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Finance Sentiment skill provides a structured interface to the Adanos Finance API, enabling users to retrieve normalized sentiment metrics for stocks. It aggregates data from Reddit, X.com, financial news, and Polymarket to deliver insights on buzz scores, bullish percentages, mention or trade counts, and trend directions. Designed for research purposes, this skill helps users quickly assess market attention and sentiment consensus across multiple platforms without needing to process raw social feeds.

What it does

  • Fetches normalized stock sentiment metrics from multiple sources.
  • Supports batch comparisons of up to 10 tickers simultaneously.
  • Provides standardized reporting for buzz, bullish percentage, and trend.
  • Synthesizes cross-source data to identify alignment or divergence in market sentiment.
  • Offers a read-only interface for objective market research.

When to use it

  • When you need to gauge the current social media or news buzz surrounding a specific stock.
  • When comparing sentiment signals between different platforms like Reddit and X.com.
  • When analyzing whether prediction market activity aligns with general social chatter.
  • When you need to rank multiple stocks based on their recent market attention.

Advantages

  • Reduces complex social and news data into actionable, normalized research signals.
  • Enables rapid multi-source and multi-ticker comparisons.
  • Maintains a consistent reporting format for easy interpretation.
  • Focuses on research-grade metrics rather than raw, noisy data.

Usage examples

“How much are Reddit users talking about TSLA?”
The agent queries the Reddit compare endpoint and reports the buzz score, bullish percentage, mention count, and trend for TSLA over the last 7 days.
“Compare sentiment on AMD vs NVDA.”
The agent fetches data for both tickers across requested sources and presents a ranked comparison based on buzz score, highlighting any significant differences in sentiment.
“Is Reddit aligned with X on META?”
The agent retrieves sentiment data from both Reddit and X.com for META, compares the bullish percentages and trends, and provides a synthesis of whether the platforms are aligned.
“How many Polymarket bets are active on Microsoft?”
The agent queries the Polymarket compare endpoint to return the trade count, buzz score, and bullish percentage for MSFT.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/himself65/finance-sentiment/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip finance-sentiment.zip -d .agents/skills

Documentation by Alex Yang

Finance Sentiment Skill

If your host has not already executed the shell probes below (for example, in Codex), run the commands inside the ! wrappers with its shell tool before choosing a setup path. Use the actual output; if shell access is unavailable, report that limitation.

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 RequestEndpoint PatternNotes
"How much are Reddit users talking about TSLA?"/reddit/stocks/v1/compareUse mentions, buzz_score, bullish_pct, trend
"How hot is NVDA on X.com?"/x/stocks/v1/compareUse mentions, buzz_score, bullish_pct, trend
"How many Polymarket bets are active on Microsoft?"/polymarket/stocks/v1/compareUse trade_count, buzz_score, bullish_pct, trend
"Compare sentiment on AMD vs NVDA"compare endpoints for the requested sourcesBatch tickers in one request
"Is Reddit aligned with X on META?"Reddit compare + X compareCompare bullish_pct, buzz_score, trend
"Give me a full sentiment snapshot for TSLA"compare endpoints across Reddit, X.com, news, PolymarketSynthesize cross-source view
"Go deeper on one ticker"/stock/{ticker} detail endpointUse 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.

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs network access, Needs an API key, Needs Python

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Alex Yang
Publisher
Alex Yang (Community)
Source
himself65/finance-skills · plugins/data-providers/skills/finance-sentiment · commit a085078
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Alex Yang or Alex Yang.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download finance-sentiment.zip