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 skills add agentlas-ai/Agentlas-OS --skill team-builder-packaginggit 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/skills/agentlas-ai/agentlas-os/team-builder-packaging)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-os/team-builder-packaging"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-os/team-builder-packaging/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/agentlas-ai/agentlas-os/team-builder-packaging"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-os/team-builder-packaging.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.00618 |
| Opus 5.5 | $0.00017 | $0.00247 |
| Sonnet 5.5 | $0.00009 | $0.00124 |
| Haiku 4.5 | $0.00004 | $0.00062 |
Grade A, and why
team-builder-packaging 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Team Builder Packaging
Procedure
-
Start with the orchestrator/HQ.
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Run
contracts/builder-interview-research-gate.mdbefore writing the roster: ask an 8-12 question first batch, research official sources, similar agent repositories or comparables, academic/professional theory, and plugin docs, compare tool/plugin choices, and write the domain-expert synthesis plus prompt-performance contract. -
Add PM Soul or project owner.
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Add Memory Curator and Memory Ticket handoff.
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Add Policy Gate, eval judge, and QA/evidence gate.
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Add workers only for real domain ownership proved by interview or research.
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Add
docs/builder-interview.md,docs/research-sources.md,docs/tool-selection.md,docs/domain-expert-synthesis.md,docs/prompt-performance-contract.md, and.agentlas/capability-eval-plan.jsonunless explicitly creating a minimal private scaffold. -
Encode handoff and return contracts.
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Emit one orchestrator/HQ global command in
.agentlas/global-commands.jsonand runtime command files. Do not expose worker commands unless requested. 9b. Declare the execution graph inmanifest.json. This is what the Hub runtime reads to build the team; a package that omits it is published, charged for as a team, and can never be called:{ "entrypoints": { "orchestrator": "agents/00-orchestrator/agent.md" }, "roster": ["agents/10-<role>/agent.md", "agents/20-<role>/agent.md"] }Write both keys explicitly. The runtime also accepts older spellings (
entrypoint,orchestrator,entry;workers,members,team) and can derive the roster fromagents/<name>/agent.md, but relying on that leaves the team's shape implicit and it drifts. Note thatentryinagentlas.jsonis the PACKAGE entrypoint, not the team manager — never reuse it for that. -
Emit runtime adapters and package verification.
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Run
scripts/verify-team-package.sh <package-root>before reportingcompleted. If it fails, do not hand off a result; correct the package by adding an orchestrator/HQ plus company-blueprint topology or by collapsing it to a valid single-agent package.
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 · 54 lines · 43 tokens per session scan A 39e9b4cfa3dd
team-builder-packaging is a skill published in the GitHub repository agentlas-ai/Agentlas-OS (1,582 stars, last pushed today), licensed Apache-2.0. It adds 43 tokens to every session and 618 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 2026-08-30.
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