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/spytensor/openmozi/claude-mdgit clone --depth 1 https://github.com/spytensor/openmoziWhat 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 | $0.05975 | $0.05975 |
| Opus 5 | $0.02988 | $0.02988 |
| Sonnet 5 | $0.01195 | $0.01195 |
| Haiku 4.5 | $0.00598 | $0.00598 |
Grade A, and why
openmozi 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 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 — 424 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — Instructions for Claude Code
Repo-wide constitutional rules live in docs/CONSTITUTION.md. If this file and the constitution diverge, follow the constitution and update this file.
Design Philosophy — Read This First
MOZI = Jarvis. The sole purpose of MOZI is to solve the user's problems. Every design decision must serve this goal.
- MOZI is a personal Agent OS first. Optimize for one operator getting real work done on a real machine. Multi-tenant or platform-scale concerns must not override the current product goal, but interfaces should remain extensible so future growth does not require a rewrite.
- The chosen LLM is replaceable. Models are schedulers/reasoners that can be swapped. The runtime is the durable operating substrate.
- Skills are part of execution, not decoration. Prefer Anthropic-compatible
SKILL.mdstyle assets and local skill packs over bespoke one-off prompt logic when the same workflow can be expressed as a reusable skill. - Default to autonomous recovery. If the task can be recovered safely by retrying, repairing, or choosing a better route, do it. Interrupt the user only for approval, ambiguity, irreversible risk, or a hard block.
- The LLM Brain makes ALL decisions. Infrastructure (gateway, TEL, tools, proactive engine) exists only to execute what the Brain decides. Never add hardcoded logic that overrides, second-guesses, or teaches the LLM how to think — that's the Brain's job.
- If a change doesn't help the user get things done faster or better, don't make it. "More autonomous", "more observable", "more intelligent infrastructure" are not valid justifications. The user doesn't care about internal metrics, system status reports, or self-monitoring — they care about results.
- Don't build scaffolding around the Brain. No fake user messages, no invented worker progress, no placeholder "queued" success, and no vague fallback narration that hides runtime truth.
- Complexity must be justified by user impact. Every line of code is a liability. Before adding a feature, ask: "Will the user notice this?" If not, don't ship it.
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 · 424 lines · 5,975 tokens per session scan A 9239965da4bf
openmozi CLAUDE.md is an instructions file published in the GitHub repository spytensor/openmozi (210 stars, last pushed 26d ago), licensed MIT. It adds 5,975 tokens to every session, about $0.0299 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
lobu AGENTS.md
Instructions for lobu-ai/lobu, covering repo map, unrecoverable — never do these, facts you cannot derive, ship a change and how to work.
Memoh AGENTS.md
AGENTS.md instructions for felinics/Memoh, covering agents.md, project overview, architecture overview, tech stack and backend (go).
lobu CLAUDE.md
Instructions for lobu-ai/lobu, a project described as: Open-source control plane and runtime for organisational agents: shared company context, isolated execution, approvals and MCP.
Memoh CLAUDE.md
Claude Code instructions for felinics/Memoh, a project described as: ✨ The open-source multi-agent platform. Every agent gets its own computer, desktop, network, and long-term memory. You can bring your own key, or host your coding agent like Claude Code, Codex and so on.
InvestSkill GEMINI.md
Instructions for yennanliu/InvestSkill, covering investskill — gemini cli setup & usage guide, installation & setup, quick start, navigate to the investskill directory and start gemini cli (loads gemini.md automatically).
she-love-me CLAUDE.md
Instructions for 863401402/she-love-me, covering claude.md and 唯一工作流.