Agentlas OS is a local-first system for creating, storing, borrowing, and running specialist AI agents and temporary agent teams through supported hosts and models. It serves people who want reusable agents that remain available across computers and model workspaces, and the catalogue contains its skills, commands, hooks, agents, instructions, plugin, and rule.
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 commands/agentlas-ai/agentlas-os/agentlas-uploadgit clone --depth 1 https://github.com/agentlas-ai/Agentlas-OSWrote 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/commands/agentlas-ai/agentlas-os/agentlas-upload)<a href="https://agentmods.dev/commands/agentlas-ai/agentlas-os/agentlas-upload"><img src="https://agentmods.dev/badge/commands/agentlas-ai/agentlas-os/agentlas-upload.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 | $0.00013 | $0.00143 |
| Opus 5 | $0.00006 | $0.00072 |
| Sonnet 5 | $0.00003 | $0.00029 |
| Haiku 4.5 | $0.00001 | $0.00014 |
Grade A, and why
agentlas-upload 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 4d 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
/agentlas-upload
Identical to /hep-upload and /agentlas upload <request>. Locate the file named hep-upload.md in the exact same directory this file was loaded from, read it, and follow its instructions exactly — treating everything typed after /agentlas-upload as that command's request.
Do not improvise a separate workflow and do not summarize hep-upload.md from memory; that file is the sole authority for this command's behavior.
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.
- 4d ago First seen · 11 lines · 13 tokens per session scan A b3f4c093a98d
agentlas-upload is a command published in the GitHub repository agentlas-ai/Agentlas-OS (1,099 stars, last pushed 2d ago), licensed Apache-2.0. It adds 13 tokens to every session and 143 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.
Other commands, from other repositories
dashboard-flow-auto
Toggle autonomous mode for a session's flow. Usage /dashboard:flow-auto.
dashboard-git-branches
List git branches for the current dir (current marked ). Runs locally, no LLM.
greet
Say hello to the user and offer to summarize a note.
run-action
Execute a learned Maestro flow ("action") by name with optional -e KEY=VALUE parameters. Looks the flow up via packages/rn-dev-agent-core/dist/learned-actions.js (same inventory as /rn-dev-agent:list-learned-actions), then replays it via cdprunaction — auto-repair-aware orchestration with structured RunRecords (GH.
nav-graph
Extract, inspect, and query the app navigation graph — a complete map of all screens and navigators.
doctor
Diagnose installation health. Check Node, CDP bridge, rn-fast-runner (iOS), rn-android-runner (Android), maestro-runner, simulators, Metro, CDP, injected helpers, ffmpeg, physical devices, plugin version, Vercel rules sync. Reports what's missing — does NOT modify your project.