Evaluate text against a natural language predicate and return true or false.
npx skills add https://github.com/bdambrosio/Cognitive_workbench --skill assess-bdambrosio
Please help me install this Agent Skill. Skill: assess Source: https://github.com/bdambrosio/Cognitive_workbench/tree/main/src/tools/assess Command: npx skills add https://github.com/bdambrosio/Cognitive_workbench --skill assess-bdambrosio
This Skill provides a way to programmatically evaluate if a piece of text meets a specific natural language condition, returning a simple true or false.
Use the assess skill to check if the text in the variable my_note is urgent.
High-intent search queries and answers about installing and using this skill.
Semantic boolean testing evaluates whether input text matches a natural language predicate by using an LLM to return a true or false result for content validation and filtering workflows.
LLM text analysis handles long documents by auto-chunking the input text and using OR aggregation to return true if any evaluated chunk contains the critical feedback predicate.
You can filter customer reviews by providing a natural language predicate such as mentions a specific product feature, allowing the LLM to perform a semantic boolean test on the text content.
Auto-chunking works by splitting long texts into manageable segments, evaluating each segment against the predicate, and applying OR aggregation to return true if any chunk matches the subjective criteria.
LLM text analysis for content validation is limited by the subjective nature of semantic boolean tests, meaning results depend on LLM interpretation of the natural language predicate rather than deterministic rules.
bdambrosioDetermine if input text contains interrogative content and return a boolean.
rudometkinSplit long text into labeled semantic chunks for language model context.
MassimilianoPiliImplement fixed-size, recursive, structure-aware, and semantic chunking for RAG systems.
iani-kuliEnforce strict structural constraints on LLM text generation using Finite State Machines and Pydantic models.
