Olares is an open-source personal cloud operating system that uses Kubernetes to combine a user’s hardware, storage, networking, applications, AI agents, and language models in one self-hosted environment. Individuals and small teams use it to run agents and local AI on computers they own while accessing their resources through a browser. The catalogue skills help users manage and operate Olares.
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 beclab/Olares --skill olares-dashboardgit clone --depth 1 https://github.com/beclab/OlaresWrote 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/beclab/olares/olares-dashboard)<a href="https://agentmods.dev/skills/beclab/olares/olares-dashboard"><img src="https://agentmods.dev/badge/skills/beclab/olares/olares-dashboard/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/beclab/olares/olares-dashboard"><img src="https://agentmods.dev/badge/skills/beclab/olares/olares-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 55 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00071 | $0.00913 |
| Opus 5 | $0.00036 | $0.00456 |
| Sonnet 5 | $0.00014 | $0.00183 |
| Haiku 4.5 | $0.00007 | $0.00091 |
Grade A, and why
olares-dashboard 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 9d 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 ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 58 lines · 71 tokens per session scan A 91a0ff65bbbf
olares-dashboard is a skill published in the GitHub repository beclab/Olares (5,257 stars, last pushed yesterday), licensed AGPL-3.0. It adds 71 tokens to every session and 913 once invoked, about $0.0004 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 skills, from other repositories
nvcf-explore-stack
Navigate and explain the NVCF self-hosted stack inside the monorepo. Maps helmfile releases to their charts, image-source subtrees, helm hooks, namespaces, and needs: dependency chains. Reads deploy/stacks/self-managed/helmfile.d/.yaml.gotmpl and deploy/stacks/nvcf-compute-plane/helmfile.d/.yaml.gotmpl as the source…
aima-tts
Text-to-speech using AIMA's current local TTS model. Generate audio files from text.
aima-asr
Transcribe audio files using AIMA's current local ASR model (speech-to-text).
aima-image-gen
Generate images using AIMA's local z-image model (OpenAI-compatible API).
aima-control
Manage local AIMA deployments and device state through the built-in AIMA MCP server.
family-knowledge
Family knowledge base for recording and retrieving household facts (members, allergies, dietary rules, doctors, schedules, house rules, pets, important dates).