---

name: cohere-core-workflow-a description: >- Build a Cohere v2 RAG pipeline with asymmetric embeddings, retrieval, Rerank v4, grounded Chat, and citation validation. Use when implementing grounded question answering. Trigger with "Cohere RAG", "Cohere retrieval", or "Cohere citations". argument-hint: "[repository-path] [retrieval-backend]" allowed-tools: Read, Glob, Grep, WebFetch, Write, Edit version: 1.6.0 author: Jeremy Longshore jeremy@intentsolutions.io license: MIT tags:

• saas
• cohere
• rag model: inherit effort: high compatibility: Designed for Claude Code; live verification requires network access and an approved Cohere API key

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Cohere Retrieval-Augmented Generation

Overview

Create a measurable retrieval pipeline that separates indexing, query embedding, candidate retrieval, reranking, generation, and citation checks.

Prerequisites

• The target repository, runtime, environment, and accountable owner
• An approved Cohere team and key for any live verification
• Current quality, security, privacy, capacity, and change-control requirements

Tool Discipline

Use Read, Glob, and Grep to inspect code, configuration, and evidence. Use WebFetch only for current Cohere primary documentation. Use Write or Edit only when the user requested implementation and the exact target files are known; never write credentials or customer content.

Current Contract

• Embed indexed passages with input_type=search_document and user queries with input_type=search_query.
• Keep the embedding model, output type, dimensions, normalization, and document schema in index metadata.
• Use Rerank v4 on a bounded candidate set before generation and retain document IDs.
• Pass selected documents to Chat v2 and validate returned citations against those IDs.

Authentication

Use an environment-specific key injected from an approved secret manager. Never print, persist, commit, or place CO_API_KEY in an example. Confirm access with the least costly bounded operation appropriate to the task, and treat key creation, rotation, revocation, role changes, and production-capacity requests as owner-approved actions.

Instructions

1. Define document IDs, chunking rules, metadata filters, and an evaluation query set.
2. Resolve and pin a live Embed model, then index documents with the document input type.
3. Embed each query with the query input type and retrieve a bounded candidate set.
4. Rerank candidates with a live v4 model and record scores and selected IDs.
5. Generate from only the selected evidence with citation options appropriate to the use case.
6. Evaluate retrieval recall, rerank quality, answer faithfulness, citation validity, latency, and cost before release.

Approval Boundaries

Do not expose or rotate keys, change Cohere Team roles, accept commercial terms, enable sensitive production data, increase spend or capacity, switch production models, send a support bundle, or execute model-proposed side effects without the accountable owner's approval. Keep diagnosis read-only unless implementation was requested.

Output

Return the resolved API and model contract, files or settings inspected, evidence collected, validation result, remaining risk, owner, and rollback or next action. Redact keys, authorization headers, prompts, retrieved documents, embeddings, customer identifiers, and unrestricted environment output.

Error Handling

Condition	Response
Dimension mismatch	Stop and rebuild or select the index matching its recorded model contract.
No candidates	Return a grounded no-answer result instead of unconstrained generation.
Invalid citation	Reject or flag the answer and retain the evidence bundle.
Context overflow	Reduce or rechunk evidence; v2 does not provide legacy prompt truncation.

Examples

Use this compact handoff shape to keep the selected scope, validation evidence, and operational result reviewable.

Input:

query=approved-fixture; retrieve=40; rerank=8; require-citations=true

Expected handoff:

answer=grounded; citations=valid; selected-doc-ids=recorded; eval=pass

Resources

• Skill-specific official documentation
• Embed API
• Rerank models