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.
npx agentmods add instructions/regen-coordination/org-os-template/agents-mdgit clone --depth 1 https://github.com/regen-coordination/org-os-templateWrote 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/regen-coordination/org-os-template/agents-md)<a href="https://agentmods.dev/instructions/regen-coordination/org-os-template/agents-md"><img src="https://agentmods.dev/badge/instructions/regen-coordination/org-os-template/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 | $0.03964 | $0.03964 |
| Opus 5 | $0.01982 | $0.01982 |
| Sonnet 5 | $0.00793 | $0.00793 |
| Haiku 4.5 | $0.00396 | $0.00396 |
Grade A, and why
org-os-template 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 5d 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 — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Organizational OS Workspace — Agent Guide
Operating instructions for AI agents (OpenClaw, Cursor, or custom runtimes) working in organizational workspaces.
🎯 START HERE: Read MASTERPLAN.md
For organization-specific agents, the canonical source is:
MASTERPLAN.md — Your Strategic Vision & Operating Manual
This file contains your mandate, activations, research directions, success metrics, and boundaries. It's how operators steer your autonomous behavior. Read it fully before proceeding with AGENTS.md.
⚠️ Workspace Safety — Before Any Destructive Git Op
Read docs/VAULT-SAFETY.md before running any git operation that touches the working tree (merge, rebase, pull, reset, checkout across branches, clean, stash, large git add -A).
Hard rules:
- Never
git stashin a workspace with precious untracked content (instances withmemory/, drafts, daily notes). Usenpm run vault:snapshot -- "<reason>"instead — it creates a permanentrefs/snapshots/<...>ref without disturbing the tree. - Never
git clean— those untracked files are content, not build artifacts. - Never
git reset --hardwhile uncommitted content exists. --no-verifyis forbidden unless the user explicitly authorizes it.mainis the only branching base. Feature-off-feature branches require a DECISIONS.md entry stating why; every session that creates commits pushes its branch before/closecompletes.- Superseded branches are archived as
archive/<name>tags, never left as branches.
After any risky op: npm run vault:audit (loud failure if files vanished).
Full protocol + 7-layer recovery runbook: docs/VAULT-SAFETY.md.
1. Deterministic Session Startup Sequence
Recommended: Run /initialize (OpenCode) or npm run initialize to get a visual dashboard of the full workspace state — projects, tasks, calendar, funding deadlines, cheatsheets. This reads all files below automatically and renders them as an actionable overview.
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.
- 5d ago First seen · 469 lines · 3,964 tokens per session scan A e8940d64d9ec
org-os-template AGENTS.md is an instructions file published in the GitHub repository regen-coordination/org-os-template (5 stars, last pushed 5d ago), licensed MIT. It adds 3,964 tokens to every session, about $0.0198 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
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).
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.
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 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.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.