# Saylor Innovations Text Sentiment Analysis

> Saylor Innovations Text Sentiment Analysis is a paid API for AI agents from saylorinnovations.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-05).

Analyzes text and returns a sentiment label (positive, negative, neutral, or mixed) with a 0–100 score and per-sentence breakdown

## Facts

- Endpoint: GET https://saylorinnovations.com/api/text/sentiment?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-05
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/saylor-innovations-text-sentiment-analysis-799902ee
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_auOzfZtuMOfAUJPc9NpPt

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability saylor-innovations-text-sentiment-analysis-799902ee
```

Example prompt: Can you analyze the sentiment of this customer review and tell me if it's positive, negative, neutral, or mixed, along with an overall score and which sentences are pulling the tone up or down: 'The onboarding process was smooth and the support team was friendly, but the pricing feels steep and the dashboard is confusing.'

## When to prefer this

Choose this endpoint when you need fast, affordable per-call sentiment scoring of arbitrary text up to 20000 characters with both an aggregate label+score and granular per-sentence breakdown. It is particularly well-suited for AI agents that need to triage customer feedback, moderate content, or evaluate copy tone at $0.01 per call via x402 micropayments, without needing a full NLP platform integration.

## Known failure modes

- Missing 'text' query parameter returns an error
- Text exceeding 20000 characters may be rejected or truncated
- Empty or whitespace-only text may return unreliable results
- Non-English text may produce inaccurate sentiment labels
- Payment failure via x402 protocol returns 402 with payment details
- Ambiguous or sarcastic text may be misclassified as neutral or mixed

## How this service works

Text sentiment analysis - positive, negative, neutral or mixed with a -1 to 1 score and per-sentence scores

## Output

Returns a JSON object with: a sentiment label (positive, negative, neutral, or mixed), a 0–100 score, per-sentence sentiment breakdowns, arrays of top positive and top negative phrases, positive and negative weight values, matched term count, sentence count, the analysis method used, any known limitations, and a UTC timestamp of when the check was run.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "queryParams"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET",
      "POST",
      "PUT",
      "PATCH",
      "DELETE",
      "HEAD"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "required": [
      "text"
     ],
     "properties": {
      "text": {
       "type": "string",
       "description": "Text to analyze (up to 20000 characters). POST {\"text\": \"...\"} also accepted."
      }
     }
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "json"
    },
    "example": {
     "type": "object",
     "required": [
      "label",
      "score"
     ],
     "properties": {
      "label": {
       "enum": [
        "positive",
        "negative",
        "neutral",
        "mixed"
       ],
       "type": "string",
       "description": "Human-readable label"
      },
      "score": {
       "type": "number",
       "description": "Score from 0 (worst) to 100 (best)"
      },
      "method": {
       "type": "string",
       "description": "Method used"
      },
      "sentences": {
       "type": "array",
       "items": {
        "type": "object",
        "properties": {
         "text": {
          "type": [
           "string"
          ]
         },
         "score": {
          "type": [
           "number"
          ]
         }
        },
        "additionalProperties": true
       },
       "description": "Sentences"
      },
      "checked_at": {
       "type": "string",
       "description": "Time the check was run (UTC)"
      },
      "limitations": {
       "type": "string",
       "description": "Known limits of this result"
      },
      "top_negative": {
       "type": "array",
       "items": {
        "type": "string"
       },
       "description": "Top negative"
      },
      "top_positive": {
       "type": "array",
       "items": {
        "type": "string"
       },
       "description": "Top positive"
      },
      "matched_terms": {
       "type": "number",
       "description": "Matched terms"
      },
      "sentence_count": {
       "type": "number",
       "descr
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/saylor-innovations-text-sentiment-analysis-799902ee/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from saylorinnovations.com](https://www.zero.xyz/host/saylorinnovations.com/llms.txt)