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.
git clone --depth 1 https://github.com/Nauro-AI/nauroWrote 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/rules/nauro-ai/nauro/nauro-adopt)<a href="https://agentmods.dev/rules/nauro-ai/nauro/nauro-adopt"><img src="https://agentmods.dev/badge/rules/nauro-ai/nauro/nauro-adopt/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/rules/nauro-ai/nauro/nauro-adopt"><img src="https://agentmods.dev/badge/rules/nauro-ai/nauro/nauro-adopt.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 | $0.00089 | $0.06293 |
| Opus 5 | $0.00044 | $0.03146 |
| Sonnet 5 | $0.00018 | $0.01259 |
| Haiku 4.5 | $0.00009 | $0.00629 |
Grade A, and why
nauro-adopt 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 10d 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 — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Nauro adopt skill
The agent helps the user seed Nauro with context from the current repo. Before this skill runs, the user has run nauro adopt from the repo root, which created the project, wired MCP across surfaces, and installed this skill into the agent's surface directory. The agent's job here is to seed the Nauro store via MCP write tools: docs supply the rationale for documented decisions, code and config and tests and manifests and recent git history supply evidence, and the user supplies the "why" via targeted probes when only evidence is present. Do not invent rationale. Record only what was actually decided, with the reasoning that supports it.
Surface modes
The agent's behaviour depends on whether the surface can read the repo directly.
- Filesystem-capable surfaces (Claude Code, Cursor, Codex CLI). The agent runs Step 0 and Steps 1–11 in full. Step 0 is an optional rapid first pass that files only the decisions carrying two verifiable citations; Docs are read for rationale in Step 3; code, config, tests, manifests, and recent git history are inspected for evidence in Step 4; targeted probes in Step 6b turn evidence into rationale by asking the user.
- Chat surfaces (Claude.ai, Perplexity). The agent has no shell. It operates only on content the user pastes into the chat (Step 3b), and only against an already-adopted project (verified in Step 3b). Step 0 is filesystem-only and is skipped on chat surfaces, exactly as Steps 1, 2, and 4 are; the Step 6b probes are likewise unavailable, and the agent does not ask the user to paste code in lieu of running shell commands. The skill skips from Step 3b directly to Step 5.
Step 0 — Rapid Cited Seed
Filesystem-capable surfaces only; skipped on chat surfaces exactly as Steps 1, 2, and 4 are. Step 0 is a fast first pass that files only the decisions whose rationale and rejected alternative are each a verbatim span the agent can point at by file:line. It reads no new surface — only the same Step 3 doc set (README; manifests; CONTRIBUTING / ARCHITECTURE / DESIGN / CLAUDE.md / AGENTS.md; the ADR dirs; the Memory-Bank files). Steps 1–11 still run afterward as the deep follow-up; Step 0 never replaces them or lowers their bar. A thin or empty Step 0 is a correct outcome — disciplined refusal, not a missed number.
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.
- 10d ago First seen · 245 lines · 89 tokens per session scan A b05f25764cce
nauro-adopt is a cursor rule published in the GitHub repository Nauro-AI/nauro (10 stars, last pushed yesterday), licensed Apache-2.0. It adds 89 tokens to every session and 6,293 once invoked, about $0.0004 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 cursor rules, from other repositories
project-context
This project's specifics, stack, conventions, locked decisions, open work. Always on.
ai-kb
Use shared AI KB rules and context.
agent-magnet
At the start of every conversation, call injectmemory with userid "helin" and projectid "default". Prepend the returned injection to your context silently — do not announce it.
coding
Core coding behavior for this repository. Always prefer cautious, minimal, reversible changes.
execution
Repository execution and verification commands.
tell-plumbing-reference
Peer plumbing reference memory for platform/MCP/auth/design-flow plans — never name the peer in commits.