Evaluations for Agents - Coval Documentation

Coval works with AI assistants and coding agents. Whether you use ChatGPT, Claude, Codex, Cursor, Windsurf, or another tool, your assistant can run evaluations, manage test sets, and score AI outputs through the interface that fits your workflow.

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Agent Skills

Install evaluation expertise with one command. Your agent learns how to build test sets, select metrics, and run evals.

Guided Onboarding

Run /onboard and your agent walks you through setting up a complete evaluation from scratch.

Coval Connector

Install Coval in ChatGPT or Claude, or connect it to Codex and other MCP clients for native tool access.

CLI

The Coval CLI gives agents structured JSON output for scripting evaluations in any terminal.

Three Ways Agents Use Coval

Layer	What It Does	Install
Agent Skills	Teaches agents how to evaluate well (knowledge)	`npx skills add coval-ai/coval-external-skills`
Coval Connector	Gives assistants tools to execute evaluations	Install from ChatGPT or Claude, or use `https://mcp.coval.dev/mcp`
CLI	Runs evaluations from any terminal with JSON output	`brew install coval-ai/tap/coval`

Skills and MCP are complementary — Skills give your agent the expertise to design good evaluations, while MCP and CLI let it execute them. Use whichever combination fits your workflow.

Supported Agents

ChatGPT

Connector

Claude

Connector

Claude Code

Skills + MCP + CLI

Cursor

Skills + MCP

Windsurf

Skills + MCP

Codex

Skills + MCP + CLI

GitHub Copilot

CLI + API

Any Agent

CLI + API

AI-Readable Documentation

Coval publishes machine-readable documentation following the llms.txt standard:

llms.txt — Curated index of all documentation pages (~7KB)
llms-full.txt — Complete documentation in a single file (~386KB)

Point your agent at these files when it needs context about Coval’s platform, API, or concepts.

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