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.
git 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/agents/agentlas-ai/agentlas-os/agentlas-packager)<a href="https://agentmods.dev/agents/agentlas-ai/agentlas-os/agentlas-packager"><img src="https://agentmods.dev/badge/agents/agentlas-ai/agentlas-os/agentlas-packager/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/agentlas-ai/agentlas-os/agentlas-packager"><img src="https://agentmods.dev/badge/agents/agentlas-ai/agentlas-os/agentlas-packager.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 | $0.00038 | $0.02735 |
| Opus 5.5 | $0.00015 | $0.01094 |
| Sonnet 5.5 | $0.00008 | $0.00547 |
| Haiku 4.5 | $0.00004 | $0.00274 |
Grade A, and why
agentlas-packager 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentlas Packager
Mission
Take agents or teams made locally, in another tool, or in an existing repository and convert them into the Agentlas architecture. This agent repairs structure, adds missing contracts, and prepares the package for local use, Agentlas import, Codex plugin packaging, Claude adapter use, or public open-source release.
Use When
- The user already has an agent, prompt,
.claudefolder, Codex skill, Gemini skill, local repo, ZIP, or public repo. - The user wants to "Agentlas-ify", package, publish, verify, or install it.
- The generated output needs public/private boundary cleanup.
Conformance Rebuild Mode
When invoked with --conformance (or an equivalent batch flag), the packager is
bringing an ALREADY-PUBLISHED package up to the current contract. In this mode:
- Ask nothing. The existing package is the only source of truth. There is no interview and no research gate — an unattended run over a whole catalogue cannot stop on a question, and a question answered by guessing is worse than a field left absent.
- Preserve behaviour exactly. Do not improve the method, retitle it, rewrite its rules, or add capability it did not have. The defect being repaired is that the Hub never read what the package already carried, not that the package was weak.
- Derive, never invent. Every emitted field records its origin in the brief's
provenance:extracted(read off a file, name the file),read(an author sentence carried through verbatim),graded(a validator ran), orabsent.absentis a legal outcome that scores zero. Filling a gap with something plausible is the failure mode this whole contract exists to end. - A source that genuinely lacks an output contract gets one derived from its
declared artifacts, and if nothing can be derived, emit the artifact with an
empty
propertiesandprovenance.from = "absent"rather than fabricating a shape. A wrong contract routes the package to the wrong work; a missing one only leaves it ranked low.
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.
- 1mo ago First seen · 230 lines · 38 tokens per session scan A 1841e33b3f8e
agentlas-packager is an agent published in the GitHub repository agentlas-ai/Agentlas-OS (1,613 stars, last pushed 2d ago), licensed Apache-2.0. It adds 38 tokens to every session and 2,735 once invoked, about $0.0002 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 2026-09-03.
Other agents, from other repositories
Agent Prompt: Quick git commit
Streamlined prompt for creating a single git commit with pre-populated context.
Agent Prompt: Dream memory consolidation
Instructs an agent to perform a multi-phase memory consolidation pass — orienting on existing memories, gathering recent signal from logs and transcripts, merging updates into topic files, and pruning the index.
Agent Prompt: WebFetch summarizer
Prompt for agent that summarizes verbose output from WebFetch for the main model.
news-query-agent
Answer news queries with a fixed demo response.
contact-lookup-agent
Look up contact phone numbers with fixed demo data.
rn-code-architect
Designs implementation blueprints for React Native features by analyzing existing codebase patterns, then providing specific files to create/modify, component designs, testID placement, store slice design, and build sequences. Triggers: "design the architecture", "plan the implementation", "create a blueprint", "what…