Borrowing it
Nothing to install: this file belongs to JanoshMoshiri/MarkdownLLM. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/JanoshMoshiri/MarkdownLLM/main/AGENTS.mdgit clone --depth 1 https://github.com/JanoshMoshiri/MarkdownLLMWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/janoshmoshiri/markdownllm/agents-md)<a href="https://agentmods.dev/instructions/janoshmoshiri/markdownllm/agents-md"><img src="https://agentmods.dev/badge/instructions/janoshmoshiri/markdownllm/agents-md.svg" alt="Measured on agentmods" height="20"></a>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 5.1 | $0.07346 | $0.07346 |
| Opus 5 | $0.03673 | $0.03673 |
| Sonnet 5 | $0.01469 | $0.01469 |
| Haiku 4.5 | $0.00735 | $0.00735 |
Grade A, and why
MarkdownLLM Framework 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.
How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MarkdownLLM Framework Agent
What This System Is
This is the MarkdownLLM framework — a specification for building LLM-driven systems where humans define domains, LLMs reason within them, and git-versioned markdown files are the persistent state. The framework is self-describing: its own specifications are things within the framework they define.
A Standing Truth About This Agent
You predict the next move — the next token, sentence, or action — from the stream of what comes next. You cannot predict its consequence the same way. Consequence is recoverable only in retrospect, by reasoning back over moves already made; it is not forecastable forward. Being asked to consider consequences does not change this: you can reason about them, you cannot foresee them. So when a move's consequence could not be recovered after the fact — anything that deletes, sends, spends, or otherwise cannot be taken back — that judgement belongs to the human and to the structure, not to a prediction of yours. Reach for the structure; defer the irreversible. This is orientation, not a hook the floor enforces. Full reasoning: things/insights/consequence-is-recoverable-only-in-retrospect.md.
This authority principle complements rather than replaces ordinary prospective risk analysis: a model can compare plausible outcomes, but cannot certify the future.
Three-Layer Architecture
Every domain in this framework — including the framework itself — follows the same three-layer pattern:
Layer 1: AGENTS.md ← Entry contract; delivered by the harness route; orchestrates everything
Layer 2: skills/*.md ← Reusable capabilities loaded by the agent at startup
Layer 3: things/*.md ← Data instances — the actual content the domain manages
↓
Git — accepted state, event stream, and inspectable history
| Layer | File Pattern | Purpose |
|---|---|---|
| Agent | AGENTS.md |
Startup instructions, skill inventory, commit conventions, business context |
| Skills | *-specification.skill.md |
Philosophy, principles, reasoning patterns for the domain |
*-read.thing.skill.md |
How to analyse things without modifying them | |
*-write.thing.skill.md |
How to create, update, and validate things | |
*-workflow.skill.md |
End-to-end process orchestration | |
| Things | things/**/*.md |
Data instances — every item the domain tracks |
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 Changed · +9 lines · +103 tokens per session 5977b39d159e
- 6d ago First seen · 296 lines · 7,243 tokens per session scan A a233e399eb58
MarkdownLLM Framework is an instructions file published in the GitHub repository JanoshMoshiri/MarkdownLLM (5 stars, last pushed 4d ago), licensed MIT. It adds 7,346 tokens to every session, about $0.0367 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.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
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.