Borrowing it
Nothing to install: this file belongs to RightNow-AI/auto. 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/RightNow-AI/auto/main/CLAUDE.mdgit clone --depth 1 https://github.com/RightNow-AI/autoWrote 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/rightnow-ai/auto/claude-md)<a href="https://agentmods.dev/instructions/rightnow-ai/auto/claude-md"><img src="https://agentmods.dev/badge/instructions/rightnow-ai/auto/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/rightnow-ai/auto/claude-md"><img src="https://agentmods.dev/badge/instructions/rightnow-ai/auto/claude-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.01838 | $0.01838 |
| Opus 5.5 | $0.00735 | $0.00735 |
| Sonnet 5.5 | $0.00368 | $0.00368 |
| Haiku 4.5 | $0.00184 | $0.00184 |
Grade A, and why
auto CLAUDE.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 2mo 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md, Auto (the AGI compiler)
read this fully before touching code. it records the vision, objects, pipeline, stack, norms, and guardrails we hold this project to. everyone working on the repo follows it.
what this is
Auto converts interpreted cognition into compiled cognition. today an agent run re-derives its plan token by token on a frontier model: brilliant, expensive, unbounded, unauditable. Auto records that behavior, proves what is secretly symbolic, distills what is not, verifies the result against a behavioral contract, and emits a cognition binary that is bounded, reproducible, capability-confined, roughly 1000x cheaper and 100x faster. speech, then writing, then computation, then cognition: the fourth compilation event. the interpreter is model-agnostic by design. it is a frontier LLM today, but nothing in the pipeline assumes that, so the same loop compiles the behavior of whatever sits at tier-0 next, world models included. the end state we are building toward: contracts as executable institutions, the IR as the shared language of cognitive work, binaries as the commodity form of expertise, and a tiered runtime where nothing is ever figured out twice.
the three objects
auto, the compiler. cli + service.auto record(attach to a live agent, capture traces) toauto compile --contract(lower to IR, run passes, verify) totask.cbin.- the runtime. tiered execution. tier-1: compiled fast path. tier-0: frontier model as interpreter, for novelty. guards on every compiled entry; guard trip to deopt to tier-0 to capture trace to recompile. the ratchet: every novel solve compiles back down. nothing figured out twice.
- the artifact + registry.
.cbin= code + small models + kernels + manifest (eval scores, cost/latency bounds, capability requirements, full provenance: traces, reference model, eval run ids). content-addressed, sigstore-signed. the manifest is the trust layer, it is never aspirational, only measured.
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.
- 2mo ago First seen · 91 lines · 1,838 tokens per session scan A 5888ac7d1935
auto CLAUDE.md is an instructions file published in the GitHub repository RightNow-AI/auto (131 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 1,838 tokens to every session, about $0.0074 per session on Opus 5.5. 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.
auto CLAUDE.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| auto CLAUDE.mdRightNow-AI/auto | Instructions file | 131 | 4mo ago | Apache-2.0 | A | 1,838 | Claude Code |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |