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 | $0.02284 |
| Opus 5.5 | $0.00013 | $0.00914 |
| Sonnet 5.5 | $0.00007 | $0.00457 |
| Haiku 4.5 | $0.00003 | $0.00228 |
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 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.
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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 Changed ed8b42e01b6c
- 11d ago Changed · +8 lines 1d27a47e4147
- 13d ago Changed 41fc3ce8f940
- 19d ago Changed bddc224df719
- 21d ago Changed 870b807da9ed
- 24d ago Changed 95344850b6d2
- 27d ago Changed · +1 lines dc00d2110e02
- 28d ago Changed · +2 lines 781f1763cab3
- 1mo ago Changed · +10 lines 4c9812c9aeba
- 1mo ago First seen · 120 lines · 33 tokens per session scan A 2c9ee76ffb19
agentrq is a skill published in the GitHub repository agentrq/agentrq (1,166 stars, last pushed today), licensed AGPL-3.0. It adds 33 tokens to every session and 2,284 once invoked, about $0.0001 per session on Opus 5.5. 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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