Analyze Supplied Text
Run linguistic analysis with explicit language and settings.
/oo Tisane: Analyze content [text] in language [code] with settings [JSON], then explain returned sentiment and entities.
Use AI with Tisane to inspect sentiment, entities and problematic-content signals, and detect language segments.
Copy a prompt into your agent with the oo Skill installed. Add your page links and source notes before running it.
Run linguistic analysis with explicit language and settings.
/oo Tisane: Analyze content [text] in language [code] with settings [JSON], then explain returned sentiment and entities.
Detect language segments with optional hints.
/oo Tisane: Detect languages in [text] with hints [languages], and summarize returned segments.
Set up oo CLI and the oo Skill in your agent.
Install OOMOL →Provide a Tisane API Subscription Key.
Connect Tisane →Use /oo with the pages to read, the changes to make, and where to save the result.
Connection Guide →Choose Your Agent
Use AI with Tisane to inspect sentiment, entities and problematic-content signals, and detect language segments.
Run linguistic analysis with explicit language and settings.
Detect language segments with optional hints.
Analyze text with Tisane for problematic content, sentiment, entities, topics, and other linguistic features.
tisane.analyze_text Detect the language segments used in a text fragment with optional language hints and delimiter settings.
tisane.detect_language List the languages currently supported by Tisane.
tisane.list_supported_languages Remove markup such as HTML, CSS, JavaScript, or JSON from UTF-8 text and return plain decoded text.
tisane.extract_text Calculate the semantic similarity between two text fragments, either in one language or across languages.
tisane.calculate_similarity Translate text between languages with Tisane, or paraphrase text when source and target languages match.
tisane.transform_text Compare two compound person entities with Tisane and return whether they are the same or different.
tisane.compare_entities No matching tools.
Yes. analyze_text requires a language; detect_language can help identify it first.
extract_text removes supported markup and returns decoded plain text.
Analysis requires language and content. Returned moderation signals should be interpreted with the source text and task context.
Manage which optional storage OOMOL can use. You can change these choices from the footer at any time.