Agent skill · writing content · aiskillstore
cohere-v2-python
Master Cohere v2 Chat API with Python, specializing in entity extraction using JSON Schema mode for structured outputs. Use when extracting entities from text, building data extraction pipelines, implementing NER systems, or requiring validated JSON responses from LLMs.
Why this skill is useful
Provides specific integration patterns and JSON Schema configurations for entity extraction that the AI wouldn't reliably generate on its own.
What it needs
Requires cohere account access. About 6k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Cohere v2 Python Overview Cohere's v2 Chat API provides powerful conversational AI capabilities with a specialized focus on structured outputs through JSON Schema mode. This skill covers entity extraction, data validation, and integration patterns for building production-ready systems that require consistent, validated responses from LLMs. When to Use This Skill Apply this skill when: Extracting structured entities from unstructured text (names, dates, locations, organizations) Building Named Entity Recognition (NER) systems Implementing data extraction pipelines with validated outputs Requiring JSON responses that conform to specific schemas Processing documents for information extraction Building classification systems with constrained outputs Integrating LLM responses with downstream databases or APIs Core Capabilities 1. Basic Chat API Initialize and use the Cohere Client for conversational tasks: Available models: command-a-03-2025 - Latest generation model For comprehensive API parameters, streaming, RAG, and tool use, refer to references/chatapi.md. 2. Entity Extraction with JSON Schema Mode The primary strength of Cohere v2 is structured outputs using JSON Schema mode, which guarantees responses conform to your specified schema. Simple Entity Extraction: Key Principles: Top-level type must be "object" At least one field must be in "required" array Schema is strictly enforced - invalid responses are regenerated First request has latency overhead; subsequent requests are cached 3. Multiple Entity Extraction Extract arrays of entities for batch processing: 4. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/cohere-v2-python