What is cli AGENTS.md?

Project instructions for using belt, a command-line tool that connects coding agents to apps, persistent notes, reusable workflows, and external services. They describe what belt is, when to use it, and how to format commands and output.

Use them when working in a project with belt to generate media, save knowledge, find workflows, connect services, search the web, or follow the expected output conventions.

They give agents the project-specific rules needed to use belt consistently. This avoids guessing which command or service interface applies.

cli AGENTS.md — Instructions file by belt-sh

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add instructions/belt-sh/cli/agents-md

Clone the repo

git clone --depth 1 https://github.com/belt-sh/cli

Made for: Codex, OpenCode.

Per session 475 This file is loaded in full into every session.

When invoked 475 The same file — it is already loaded in full.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00475	$0.00475
Opus 5	$0.00237	$0.00237
Sonnet 5	$0.00095	$0.00095
Haiku 4.5	$0.00047	$0.00047

Measured 2d ago against content hash 4760ea04b1a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cli AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 41 lines

What it actually says

agents working with belt

this file provides context for any ai agent (claude, cursor, copilot, etc.) working in a project where belt is available.

what belt is

belt is a cli that gives agents access to:

250+ ai apps — image generation (gpt-image, reve, pruna), video (veo, seedance), audio (tts, music), llms (claude, gemini), search (tavily, exa), 3d, and more
knowledge system — persistent memory that survives across sessions. save observations, concepts, skills, references
skill registry — reusable agent workflows. search, install, publish
mcp connectors — connect to any mcp-compatible service through the platform

when to use belt

generating media: belt app search "image" → belt app run openai/gpt-image-2 --input '{"prompt": "..."}'
remembering something: belt know create - --name finding --type observation <<< "learned X"
looking for a workflow: belt skill search "deploy" or belt suggest "how to do X"
connecting to services: belt mcp connect slack → belt mcp run slack send_message
web search / research: belt app run tavily/search --input '{"query": "..."}'

output format

tty mode: human-readable, colored output
piped/--json: structured json, safe for parsing
always use --json when you need to process output programmatically

conventions

app inputs are always json (--input flag or file path)
knowledge types: skill, concept, observation, reference, preference
skill names follow namespace/name format
apps follow owner/app-name or owner/app-name@version format

error handling

belt exits non-zero on failure with a descriptive error message. common issues:

not authenticated → belt login
app not found → check spelling, try belt app search
invalid input → use belt app sample to generate valid input schema

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2d ago First seen · 41 lines · 475 tokens per session scan A 4760ea04b1a6

Subscribe to this mod's changes

cli AGENTS.md is an instructions file published in the GitHub repository belt-sh/cli (7 stars, last pushed 1mo ago), licensed MIT. It adds 475 tokens to every session, about $0.0024 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Productivity Research

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

cli AGENTS.md