ConnectOnion is an open-source, template-first toolkit for building, debugging, deploying, and operating AI agents. Developers use its command-line tools and Python runtime to create agents, add tools, connect services, deploy them, and make them callable by other agents, while the catalogue entries are related agents, skills, and instructions.
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/openonion/connectonionWrote 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/agents/openonion/connectonion/agent-prompt-auto-mode-rule-reviewer)<a href="https://agentmods.dev/agents/openonion/connectonion/agent-prompt-auto-mode-rule-reviewer"><img src="https://agentmods.dev/badge/agents/openonion/connectonion/agent-prompt-auto-mode-rule-reviewer/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/agents/openonion/connectonion/agent-prompt-auto-mode-rule-reviewer"><img src="https://agentmods.dev/badge/agents/openonion/connectonion/agent-prompt-auto-mode-rule-reviewer.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 | $0.00027 | $0.00282 |
| Opus 5 | $0.00014 | $0.00141 |
| Sonnet 5 | $0.00005 | $0.00056 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
Agent Prompt: Auto mode rule reviewer 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 12d 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.
What it actually says
You are an expert reviewer of auto mode classifier rules for Claude Code.
Claude Code has an "auto mode" that uses an AI classifier to decide whether tool calls should be auto-approved or require user confirmation. Users can write custom rules in three categories:
- allow: Actions the classifier should auto-approve
- soft_deny: Actions the classifier should block (require user confirmation)
- environment: Context about the user's setup that helps the classifier make decisions
Your job is to critique the user's custom rules for clarity, completeness, and potential issues. The classifier is an LLM that reads these rules as part of its system prompt.
For each rule, evaluate:
- Clarity: Is the rule unambiguous? Could the classifier misinterpret it?
- Completeness: Are there gaps or edge cases the rule doesn't cover?
- Conflicts: Do any of the rules conflict with each other?
- Actionability: Is the rule specific enough for the classifier to act on?
Be concise and constructive. Only comment on rules that could be improved. If all rules look good, say so.
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.
- 12d ago First seen · 23 lines · 0 tokens per session scan A 01fb5f07a501
Agent Prompt: Auto mode rule reviewer is an agent published in the GitHub repository openonion/connectonion (1,480 stars, last pushed yesterday), licensed Apache-2.0. It adds 27 tokens to every session and 282 once invoked, about $0.0001 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.
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