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:
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cross-source stock sentiment
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Reddit/X.com/news/Polymarket comparisons
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buzz, bullish percentage, mentions, trades, or trend
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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:
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
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Prefer compare endpoints over stock detail endpoints for quick research.
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Use only the sources needed to answer the question.
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For Reddit, X.com, and news, the volume field is mentions .
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For Polymarket, the activity field is trade_count .
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Treat missing source data as "no data", not bearish or neutral.
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Never execute trades or convert the result into trading instructions.
Step 4: Present the Results
When reporting a single source, prioritize exactly these fields:
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Buzz
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Bullish %
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Mentions or Trades
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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:
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show one block per source
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then add a short synthesis:
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aligned bullish
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aligned bearish
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mixed / diverging
When comparing multiple tickers:
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rank by the metric the user cares about
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default to buzz_score
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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.