| name | stocktwits-sentiment |
| description | This skill should be used when the user asks about StockTwits sentiment, trader bullish/bearish ratio, StockTwits stream, real-time trader sentiment, what traders are saying on StockTwits, or the StockTwits signal for a stock.
|
StockTwits Sentiment Analysis
Purpose
Fetch StockTwits sentiment for a ticker by scraping the symbol page, tally
bullish vs bearish self-labeled messages, and produce a channel score from
-10 to +10.
Step 1 — Fetch Symbol Page
WebFetch the StockTwits symbol page with this prompt:
"Extract: (1) bullish message count or percentage, (2) bearish message count
or percentage, (3) total labeled messages, (4) any overall sentiment label
(e.g. Bullish, Bearish, Extremely Bullish, Extremely Bearish, Neutral),
(5) up to 2 recent message bodies labeled Bullish and up to 2 labeled Bearish."
https://stocktwits.com/symbol/{ticker}
If that page returns no useful data, retry with:
https://stocktwits.com/symbol/{ticker}/sentiment
Step 2 — Extract Counts or Label
If raw counts are available (bullish_count and bearish_count):
- Set
score_method = "ratio"
total_labeled = bullish_count + bearish_count- Proceed to Step 3a.
If only a percentage is available (e.g. "73% Bullish"):
- Derive counts:
bullish_count = round(pct × total_labeled), bearish_count = total_labeled - bullish_count
- Set
score_method = "pct-derived"
- Proceed to Step 3a.
If only a qualitative label is available (no counts or percentages):
- Set
score_method = "label-derived"
- Map label to score and proceed to Step 3b:
| StockTwits Label | stocktwits_score |
|---|
| Extremely Bullish | +8.5 |
| Bullish | +5.0 |
| Neutral | 0.0 |
| Bearish | -5.0 |
| Extremely Bearish | -8.5 |
If the page fails to load, returns an error, or yields no sentiment data:
Set stocktwits_available = false.
Note: "StockTwits: Page unavailable or no sentiment data found"
Step 3a — Compute Score from Ratio
stocktwits_score = (bullish_count - bearish_count) / total_labeled × 10
Step 3b — Score from Label (skip if 3a used)
Use the mapped score from the label table in Step 2. Set total_labeled = N/A.
Step 4 — Sample Messages
Extract the most recent Bullish-labeled message body and most recent
Bearish-labeled message body from the page content. If unavailable, note
"Sample unavailable".
Step 5 — Output
STOCKTWITS SENTIMENT RESULT
Ticker: {ticker}
Channel Score: {stocktwits_score} / 10
Signal: {label per signal bands below}
Score Method: {ratio | pct-derived | label-derived}
Labeled Messages: {total_labeled} ({bullish_count} bullish / {bearish_count} bearish)
Sample Bullish: "{message_body}"
Sample Bearish: "{message_body}"
If unavailable:
STOCKTWITS SENTIMENT RESULT
Ticker: {ticker}
Channel Score: N/A
Signal: N/A
Note: {reason}
Signal bands (applied to stocktwits_score):
- score >= +7.0 → Very Bullish
- score >= +3.0 and < +7.0 → Bullish
- score > -3.0 and < +3.0 → Neutral
- score <= -3.0 and > -7.0 → Bearish
- score <= -7.0 → Very Bearish
