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Get Started Free →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
.claude/skills/himself65-finance-sentiment/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-08 | ✗→✓ | ▲ Improved | -13% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 57% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 29% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 36% | 0% |
| case-17 | ✗→✓ | ▲ Improved | -14% | 0% |
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:
Current environment status:
bash!`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:
bashexport ADANOS_API_KEY="sk_live_..."
Use the key via the X-API-Key header on all requests.
Base docs:
texthttps://api.adanos.org/docs
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:
days=7 unless the user asks for another windowTicker count:
1..10 tickersUse curl with X-API-Key. Prefer compare endpoints because they are compact and batch-friendly.
bashcurl -s "https://api.adanos.org/reddit/stocks/v1/compare?tickers=TSLA&days=7" \ -H "X-API-Key: $ADANOS_API_KEY"
bashcurl -s "https://api.adanos.org/x/stocks/v1/compare?tickers=NVDA&days=7" \ -H "X-API-Key: $ADANOS_API_KEY"
bashcurl -s "https://api.adanos.org/polymarket/stocks/v1/compare?tickers=MSFT&days=7" \ -H "X-API-Key: $ADANOS_API_KEY"
bashcurl -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"
bashcurl -s "https://api.adanos.org/reddit/stocks/v1/compare?tickers=AMD,NVDA,META&days=7" \ -H "X-API-Key: $ADANOS_API_KEY"
mentions.trade_count.When reporting a single source, prioritize exactly these fields:
Example:
textTSLA on Reddit, last 7 days - Buzz: 74.1/100 - Bullish: 31% - Mentions: 647 - Trend: rising
When reporting multiple sources for one ticker:
When comparing multiple tickers:
buzz_scorebullish_pct or trendDo not overstate precision. These are research signals, not trade instructions.
references/api_reference.md - endpoint guide, field meanings, and example workflowsRead the reference file when you need the exact field names, query parameters, or recommended answer patterns.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 15,770 | 4,930 | -69% | 1 | 1 | 0% | 1,654 | 1,667 | +1% | 0 | 0 | — |
case-02 | fail→fail | 13,435 | 4,298 | -68% | 1 | 1 | 0% | 2,386 | 1,637 | -31% | 0 | 0 | — |
case-03 | fail→fail | 15,308 | 4,687 | -69% | 1 | 1 | 0% | 2,729 | 1,681 | -38% | 0 | 0 | — |
case-04 | fail→fail | 13,158 | 4,502 | -66% | 1 | 1 | 0% | 1,416 | 1,658 | +17% | 0 | 0 | — |
case-05 | fail→fail | 11,782 | 4,701 | -60% | 1 | 1 | 0% | 1,942 | 1,659 | -15% | 0 | 0 | — |
case-06 | pass→pass | 15,965 | 4,293 | -73% | 1 | 1 | 0% | 2,287 | 2,146 | -6% | 0 | 0 | — |
case-07 | pass→pass | 3,444 | 2,099 | -39% | 1 | 1 | 0% | 479 | 1,722 | +259% | 0 | 0 | — |
case-08 | fail→pass | 9,337 | 1,619 | -83% | 1 | 1 | 0% | 1,920 | 1,666 | -13% | 0 | 0 | — |
case-09 | fail→pass | 8,309 | 2,968 | -64% | 1 | 1 | 0% | 1,294 | 2,029 | +57% | 0 | 0 | — |
case-10 | fail→fail | 11,951 | 2,840 | -76% | 1 | 1 | 0% | 2,391 | 1,732 | -28% | 0 | 0 | — |
case-11 | pass→pass | 7,613 | 2,075 | -73% | 1 | 1 | 0% | 1,367 | 1,690 | +24% | 0 | 0 | — |
case-12 | pass→pass | 11,820 | 2,298 | -81% | 1 | 1 | 0% | 1,720 | 1,881 | +9% | 0 | 0 | — |
case-13 | pass→pass | 10,014 | 3,718 | -63% | 1 | 1 | 0% | 1,692 | 1,953 | +15% | 0 | 0 | — |
case-14 | fail→pass | 9,443 | 3,354 | -64% | 1 | 1 | 0% | 1,610 | 2,072 | +29% | 0 | 0 | — |
case-15 | pass→pass | 6,756 | 2,140 | -68% | 1 | 1 | 0% | 1,273 | 1,731 | +36% | 0 | 0 | — |
case-16 | fail→pass | 49,395 | 3,670 | -93% | 1 | 1 | 0% | 1,422 | 1,933 | +36% | 0 | 0 | — |
case-17 | fail→pass | 11,336 | 1,471 | -87% | 1 | 1 | 0% | 1,874 | 1,614 | -14% | 0 | 0 | — |
case-18 | fail→fail | 12,615 | 5,789 | -54% | 1 | 1 | 0% | 1,773 | 2,342 | +32% | 0 | 0 | — |
case-19 | fail→pass | 10,956 | 1,848 | -83% | 1 | 1 | 0% | 2,182 | 1,731 | -21% | 0 | 0 | — |
case-20 | pass→fail | 20,851 | 7,502 | -64% | 1 | 1 | 0% | 4,843 | 1,924 | -60% | 0 | 0 | — |
case-21 | pass→fail | 7,095 | 9,091 | +28% | 1 | 1 | 0% | 1,390 | 1,785 | +28% | 0 | 0 | — |
case-22 | pass→pass | 16,192 | 15,567 | -4% | 1 | 1 | 0% | 3,569 | 4,584 | +28% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 17 counted toward the lift figure. The other 5 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +18 percentage points is the difference between those two pass rates over the 17 comparable cases. 3 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.