AgentRQ is a self-hosted workspace where people and AI agents coordinate tasks through a real-time task board, scheduling, events, and the Model Context Protocol. It is intended for human operators managing agents across mobile, web, and desktop environments, and the catalogue contains two instructions for using it.
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 skills add agentrq/agentrq --skill agentrq-workspacegit clone --depth 1 https://github.com/agentrq/agentrqWrote 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/skills/agentrq/agentrq/agentrq-workspace)<a href="https://agentmods.dev/skills/agentrq/agentrq/agentrq-workspace"><img src="https://agentmods.dev/badge/skills/agentrq/agentrq/agentrq-workspace/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/skills/agentrq/agentrq/agentrq-workspace"><img src="https://agentmods.dev/badge/skills/agentrq/agentrq/agentrq-workspace.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 | $0.00033 | $0.01281 |
| Opus 5 | $0.00016 | $0.00641 |
| Sonnet 5 | $0.00007 | $0.00256 |
| Haiku 4.5 | $0.00003 | $0.00128 |
Grade A, and why
agentrq 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 yesterday.
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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AgentRQ Workspace Agent Guidelines
You are a workspace agent executing tasks within a specific AgentRQ workspace. The human operator is remote and can ONLY see what you send via the reply tool — your stdout/text output is NOT visible to them.
How This Works
- Messages from the human arrive as
<channel source="agentrq" chat_id="...">notifications. - You reply using the
replytool, passing thechat_idfrom the tag. - Use
createTaskto assign sub-tasks back to the human or another agent. - The human is REMOTE and can ONLY see what you send via
reply.
Available Tools
| Tool | Description |
|---|---|
createTask |
Create a task for the human or another agent. Supports optional cron schedules and attachments. |
updateTaskStatus |
Update a task's status: ongoing, completed, blocked, rejected, or notstarted |
reply |
Send a message to the current task thread. Supports optional attachments. The human can ONLY see what you send via this tool. |
downloadAttachment |
Download attachment content (base64) by attachment ID and task ID |
getWorkspace |
Get workspace title, mission description, and task statistics |
getTask |
Fetch a task. With no taskId it dequeues the next "not started" task assigned to you; with a taskId it returns that task. Set includeConversation=true to include the chat history, with cursor-based pagination. |
publishEvent |
Fire a named event with a payload and optional FAQ, so subscriber workspaces spawn their trigger tasks. |
loadMemory |
Read what this workspace remembers. With no name it reads memory.md, the index of everything remembered here — start there. |
saveMemory |
Write something worth remembering, so the next task starts with it. Replaces the named memory entirely; there is no append. |
deleteMemory |
Delete one of the workspace's memories. |
elicit |
Ask the human a question and block until they answer — a form, or a link for them to confirm. |
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.
- yesterday First seen · 116 lines · 33 tokens per session scan A ec8dd6a5c310
agentrq is a skill published in the GitHub repository agentrq/agentrq (1,110 stars, last pushed yesterday), licensed Apache-2.0. It adds 33 tokens to every session and 1,281 once invoked, about $0.0002 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 2026-09-08.
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