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/penso/arbor/agents-mdgit clone --depth 1 https://github.com/penso/arborWhat 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 | $0.02986 | $0.02986 |
| Opus 5 | $0.01493 | $0.01493 |
| Sonnet 5 | $0.00597 | $0.00597 |
| Haiku 4.5 | $0.00299 | $0.00299 |
Grade A, and why
arbor 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.
How it starts
The opening of the file, as written. The whole thing — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file defines how coding agents should behave in this repository.
Priorities
- Keep code simple, explicit, and maintainable.
- Fix root causes, avoid temporary band-aids.
- Preserve user changes, never revert unrelated edits.
Workflow
- Read this file at task start.
- Prefer
justrecipes for common tasks. - Before committing code, always run
just formatandjust lintand fix any failures. - Before handoff, run relevant checks for touched code.
UI Parity
- Arbor has two user-facing UI surfaces:
arbor-guiandarbor-web-ui. - When adding, changing, or removing a user-visible feature in one surface, check whether the other surface needs the same capability.
- Default to keeping both surfaces in parity. If parity is intentionally deferred, call that out clearly in the handoff and create follow-up work instead of silently shipping only one side.
- UI verification should cover both surfaces when the feature is meant to exist in both.
GPUI Threading Rules
- Treat the GPUI app/window/entity context as the UI thread unless you have explicitly moved work off it.
- Be extremely careful not to block the UI thread with disk I/O, network I/O, daemon RPCs, SSH, git/process spawning, sleeps, waits, or CPU-heavy work. If it can stall a frame, assume it is forbidden on the UI thread.
- GPUI/Zed guidance matters here:
App::spawn,Context::spawn_in, andAsyncWindowContext::spawnrun futures that are polled on the main thread. Do not put blocking or CPU-intensive work directly inside those futures. - Use
cx.background_spawn(...)or aBackgroundExecutorfor blocking or CPU-heavy work. Use the foreground task only to kick work off, await the result, and then hop back intoupdate(...)to apply state changes. - If you must adapt a synchronous blocking function, run it on a background thread/executor. Prefer GPUI background tasks, and use
smol::unblockwhen you need to wrap a blocking call into a future. Do not introduce Tokio. - Render paths must be pure state reads. Never do filesystem scans, config loads, git queries, daemon calls, SSH work, process spawning, or expensive recomputation from
render_*methods. - Event handlers and hot paths must stay thin.
on_action,listener, websocket/message handlers, timers, auto-refresh loops, and key/mouse handlers should schedule background work and return quickly instead of doing the slow part inline. - Cache derived data that is expensive to compute or load. If the UI needs it often, compute it in the background, store it in state, and render from the cached state.
- When reviewing GPUI code, ask two questions every time:
could this block?andcould this run during render or a hot UI path?If yes, move it off-thread.
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 · 255 lines · 2,986 tokens per session scan A d2999c6358cf
arbor AGENTS.md is an instructions file published in the GitHub repository penso/arbor (809 stars, last pushed 2mo ago), licensed MIT. It adds 2,986 tokens to every session, about $0.0149 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 2026-08-30.
Other instructions, from other repositories
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.
buildNext
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).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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).
spec-kit 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.
langchain 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.