AgentLint
The linter for your agent harness. Works with Claude Code, Codex, and Cursor.
Install
npx agentlint-ai installclaude mcp add agentlint -- npx agentlint-ai install{
"mcpServers": {
"agentlint": {
"command": "npx",
"args": [
"agentlint-ai",
"install"
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →AgentLint
The linter for your agent harness. ESLint was for the code humans wrote.AgentLint is for the context agents read.
🌐 Site · Blog · Install · Demo · Harness 101 · Checks · Evidence · FAQ · 中文
Agent = Model + Harness. The model isn't the bottleneck anymore — the harness is.
Your
AGENTS.md,CLAUDE.md, CI config, hooks, and.gitignoreare the harness. When they're wrong, Claude Code, Cursor, and Codex ship AI slop. When they're right, agents compound.AgentLint scores your harness across 51 deterministic checks on 6 core dimensions, plus 7 opt-in extended checks (Deep + Session) that use AI sub-agents and local Claude Code session logs when available. Evidence-backed. Zero opinions.
📚 Full docs, 20+ long-form guides, and the complete check catalog live at agentlint.app. Highlights: Writing a Good CLAUDE.md · The 33-Check Catalog · AGENTS.md vs CLAUDE.md · 中文博客.
Install
npm install -g agentlint-ai # CLI only — no Claude plugin yet
npx agentlint-ai install # opt-in: register /al Claude Code plugin
The first command installs the
agentlintCLI on$PATHand does not touch~/.claude/. The second command (one-time, opt-in) detects Claude Code, copies the/alslash command into~/.claude/commands/, and registers the marketplace plugin. Side-effect details and uninstall path in INSTALL.md.
Then in any git repo:
agentlint check
In Claude Code (after running npx agentlint-ai install): run /al for the interactive scan-fix-report flow.
Using an AI coding agent? Point it at INSTALL.md — it's written to be read once and acted on.
What you get
$ /al
AgentLint — Score: 72/100 (core)
Findability ██████████████░░░░░░ 7/10
Instructions ████████████████░░░░ 8/10
Workability ████████████░░░░░░░░ 6/10
Safety ██████████░░░░░░░░░░ 5/10
Continuity ██████████████░░░░░░ 7/10
Harness ████████████████████ 10/10
Deep ░░░░░░░░░░░░░░░░░░░░ n/a (opt-in)
Session ░░░░░░░░░░░░░░░░░░░░ n/a (opt-in)
Fix Plan (7 items):
[guided] Pin 8 GitHub Actions to SHA (supply chain risk)
[guided] Add .env to .gitignore (AI exposes secrets)
[assisted] Generate HANDOFF.md
[guided] Reduce IMPORTANT keywords (7 found, Anthropic uses 4)
Select items → AgentLint fixes → re-scores → saves HTML report
The harness problem
In February 2026, Mitchell Hashimoto (HashiCorp) coined the term. OpenAI's Ryan Lopopolo formalized it days later. LangChain's Vivek Trivedy gave it the cleanest definition:
Agent = Model + Harness. If you're not the model, you're the harness.
The harness is every piece of code, configuration, and instruction that wraps an LLM and turns it into an agent. For coding agents, your harness includes:
Similar plugs
CLI proxy that reduces LLM token consumption by 60-90% on common dev commands. Single Rust binary, zero dependencies
Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1
Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro,…
Wrap Antigravity, ChatGPT Codex, Claude Code, Grok Build, Muse Code, Devin as an OpenAI/Gemini/Claude/Codex compatible API service, allowing you to enjoy the free Gemini…