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gov.halowerk.com Sentiment Analysis
x402
gov.halowerk.com Sentiment Analysis is a paid API for AI agents from gov.halowerk.com, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).
Tokenizes text against an English/German unigram lexicon and returns a normalized polarity score with lexicon coverage statistics
Price / call$0.002
Success—
StatusUnknown
How this service works
Tokenizes caller-supplied text and counts matches against a small declared English/German unigram lexicon. It reports coverage and a normalized polarity score; it does not understand context, sarcasm, negation, policy merit, or public opinion.
Output
Returns a normalized polarity score (likely -1 to +1 range) and lexicon coverage metrics indicating what fraction of tokens matched the declared English/German unigram lexicon. Does not account for context, negation, sarcasm, or semantic meaning beyond direct lexicon matches.
Example use cases
Screening governance proposal tone
“Can you run a sentiment score on this governance proposal text? I want to know its polarity and how much of the text matched the lexicon: 'This amendment reduces treasury overhead and reallocates funds to public goods, strengthening long-term protocol health.'”
Monitoring community forum posts
“Score the sentiment of this forum comment for me: 'Der Vorschlag ist gut gemeint, aber die Umsetzung wirkt überstürzt und unausgereift.' — I need the normalized polarity value and lexicon coverage percentage.”
Comparing sentiment across proposal drafts
“I have two versions of a policy statement and want to compare their polarity scores — can you run sentiment analysis on each: first 'This measure protects participants and builds trust', then 'This rule restricts access and reduces flexibility'?”
Technical details
Endpoint
POSThttps://gov.halowerk.com/v1/sentiment-analysisWhen to prefer
Choose this endpoint when you need a fast, deterministic, lexicon-based polarity score for English or German text without requiring deep semantic understanding. Ideal for governance-adjacent pipelines (proposal scoring, comment screening) where reproducibility and transparency of the scoring method matter more than nuanced sentiment. Prefer alternatives when negation handling, sarcasm detection, or contextual understanding is required.
Side effects
- Empty or missing text field returns validation error
- Text exceeding 50,000 characters is rejected
- Non-English and non-German text produces low or zero coverage with unreliable scores
- Heavily negated or sarcastic text produces misleading polarity due to lack of context modeling
- Payment failure or insufficient USDC balance returns 402 error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | Text to score. |
Tags
x402
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