Text Classifier — Topic Categories & Readability
APIFreeText classification API for AI agents. Classify text into topic categories with confidence scores, readability metrics (Flesch-Kincaid), and content type detection (article, review, email, code, etc.). Tools: text_classify_content. Use this for content routing, auto-tagging, spam detection, or org
- Best for
- topic category classification with confidence scoring, readability assessment using flesch-kincaid metrics, content type detection for diverse formats
- Type
- API · Free
- Score
- 34/100
- Best alternative
- PostHog
Capabilities3 decomposed
topic category classification with confidence scoring
Medium confidenceThis capability classifies input text into predefined topic categories using a machine learning model trained on a diverse dataset. It employs a probabilistic approach to assign confidence scores to each category, allowing users to understand the model's certainty in its classifications. The architecture is designed for high efficiency, enabling quick responses without requiring an API key, making it accessible for various applications.
Utilizes a lightweight model optimized for fast inference, allowing for micropayment-based usage without API key restrictions, which is uncommon in similar services.
More cost-effective for high-volume usage compared to traditional APIs that require subscriptions or API keys.
readability assessment using flesch-kincaid metrics
Medium confidenceThis capability evaluates the readability of input text by calculating Flesch-Kincaid scores, which assess text complexity based on sentence length and word syllable count. The implementation leverages natural language processing techniques to analyze the text structure efficiently, providing a quantitative measure of readability that can be used to tailor content for specific audiences.
Integrates readability scoring directly into the classification API, providing a dual-functionality that is rare in standalone readability tools.
Offers combined text classification and readability assessment in one API call, reducing the need for multiple integrations.
content type detection for diverse formats
Medium confidenceThis capability identifies the type of content (e.g., article, review, email, code) by analyzing the structure and keywords within the text. It employs a classification model that has been trained on labeled examples of various content types, allowing it to distinguish between formats effectively. This feature is particularly useful for applications that need to route content based on its type.
Combines multiple content type detection capabilities into a single API, allowing for streamlined processing without the need for separate services.
More versatile than single-function classifiers by handling multiple content types in one call.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓content managers organizing large volumes of text
- ✓developers building AI-driven content routing systems
- ✓content creators aiming for audience engagement
- ✓educators developing instructional materials
- ✓developers building content management systems
- ✓businesses automating customer feedback processing
Known Limitations
- ⚠Accuracy may vary based on the diversity of the training data, especially for niche topics.
- ⚠Limited to predefined categories, which may not cover all user needs.
- ⚠Readability scores are language-specific; results may not be accurate for non-English texts.
- ⚠Does not provide qualitative feedback on content quality.
- ⚠May struggle with ambiguous content that fits multiple categories.
- ⚠Accuracy depends on the quality of the training dataset.
Requirements
Input / Output
UnfragileRank
UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.
Repository Details
About
Text classification API for AI agents. Classify text into topic categories with confidence scores, readability metrics (Flesch-Kincaid), and content type detection (article, review, email, code, etc.). Tools: text_classify_content. Use this for content routing, auto-tagging, spam detection, or organizing unstructured text. IMPORTANT: For sentiment analysis, use text_analyze_sentiment instead. Returns: {categories[], readability, contentType, confidence}. No API key required — x402 micropayment $0.005/call on Base L2.
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