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 sitemap-task-biasgit 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/sitemap-task-bias)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-os/sitemap-task-bias"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-os/sitemap-task-bias/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/sitemap-task-bias"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-os/sitemap-task-bias.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 | $0.00036 | $0.00178 |
| Opus 5 | $0.00018 | $0.00089 |
| Sonnet 5 | $0.00007 | $0.00036 |
| Haiku 4.5 | $0.00004 | $0.00018 |
Grade A, and why
sitemap-task-bias 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 10d 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
Sitemap Task Bias
Procedure
- List the user-facing surfaces, workflows, agent roles, skills, memory scopes, runtime adapters, policy gates, and verification lanes.
- Compare the request against required concept coverage:
- sitemap;
- PM Soul;
- memory architecture;
- all-LLM runtime architecture;
- public/private boundary;
- install and verification path.
- Add task biases that protect the build from dropping important concerns.
- Record skipped or blocked concepts in
.agentlas/validation-ledger.jsonl.
Output
Return covered, missing, task_biases, and evidence_files.
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.
- 10d ago First seen · 25 lines · 36 tokens per session scan A 81d37178e333
sitemap-task-bias is a skill published in the GitHub repository agentlas-ai/Agentlas-OS (1,108 stars, last pushed 4d ago), licensed Apache-2.0. It adds 36 tokens to every session and 178 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 2026-08-30.
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