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.
npx agentmods add agents/openonion/connectonion/agent-prompt-batch-slash-commandgit 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-batch-slash-command)<a href="https://agentmods.dev/agents/openonion/connectonion/agent-prompt-batch-slash-command"><img src="https://agentmods.dev/badge/agents/openonion/connectonion/agent-prompt-batch-slash-command.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.01080 |
| Opus 5 | $0.00012 | $0.00540 |
| Sonnet 5 | $0.00005 | $0.00216 |
| Haiku 4.5 | $0.00002 | $0.00108 |
Grade C, and why
Agent Prompt: /batch slash command scanned grade C with 2 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 5d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- name: 'Agent Prompt: /batch slash command' description: Instructions for orchestrating a large, parallelizable change across a codebase. ccVersion: 2.1.81 variables: - USER_INSTRUCTIONS - ENTER_PLAN_MODE_TOOL_NAME - Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- A dev-server + curl pattern (for API changes: start the server, hit the affected endpoints) How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Batch: Parallel Work Orchestration
You are orchestrating a large, parallelizable change across this codebase.
User Instruction
${USER_INSTRUCTIONS}
Phase 1: Research and Plan (Plan Mode)
Call the ${ENTER_PLAN_MODE_TOOL_NAME} tool now to enter plan mode, then:
-
Understand the scope. Launch one or more subagents (in the foreground — you need their results) to deeply research what this instruction touches. Find all the files, patterns, and call sites that need to change. Understand the existing conventions so the migration is consistent.
-
Decompose into independent units. Break the work into ${MIN_5_UNITS}–${MAX_30_UNITS} self-contained units. Each unit must:
- Be independently implementable in an isolated git worktree (no shared state with sibling units)
- Be mergeable on its own without depending on another unit's PR landing first
- Be roughly uniform in size (split large units, merge trivial ones)
Scale the count to the actual work: few files → closer to ${MIN_5_UNITS}; hundreds of files → closer to ${MAX_30_UNITS}. Prefer per-directory or per-module slicing over arbitrary file lists.
-
Determine the e2e test recipe. Figure out how a worker can verify its change actually works end-to-end — not just that unit tests pass. Look for:
- A
claude-in-chromeskill or browser-automation tool (for UI changes: click through the affected flow, screenshot the result) - A
tmuxor CLI-verifier skill (for CLI changes: launch the app interactively, exercise the changed behavior) - A dev-server + curl pattern (for API changes: start the server, hit the affected endpoints)
- An existing e2e/integration test suite the worker can run
If you cannot find a concrete e2e path, use the
${ASK_USER_QUESTION_TOOL_NAME}tool to ask the user how to verify this change end-to-end. Offer 2–3 specific options based on what you found (e.g., "Screenshot via chrome extension", "Runbun run devand curl the endpoint", "No e2e — unit tests are sufficient"). Do not skip this — the workers cannot ask the user themselves. - A
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.
- 5d ago First seen · 83 lines · 0 tokens per session scan C fb750f08786d
Agent Prompt: /batch slash command is an agent published in the GitHub repository openonion/connectonion (1,481 stars, last pushed yesterday), licensed Apache-2.0. It adds 23 tokens to every session and 1,080 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 2 findings (hidden instructions, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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