OpenAgent is a self-hostable personal AI assistant that combines language models, document-based retrieval, and autonomous agent loops. It lets people connect model providers and their own knowledge bases, then have agents browse the web, run code, use computers, and call MCP-compatible tools.
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 the-open-agent/openagent --skill healthcheckgit clone --depth 1 https://github.com/the-open-agent/openagentWrote 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/the-open-agent/openagent/healthcheck)<a href="https://agentmods.dev/skills/the-open-agent/openagent/healthcheck"><img src="https://agentmods.dev/badge/skills/the-open-agent/openagent/healthcheck/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/the-open-agent/openagent/healthcheck"><img src="https://agentmods.dev/badge/skills/the-open-agent/openagent/healthcheck.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 | $0.00070 | $0.02401 |
| Opus 5 | $0.00035 | $0.01201 |
| Sonnet 5 | $0.00014 | $0.00480 |
| Haiku 4.5 | $0.00007 | $0.00240 |
Grade A, and why
healthcheck 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
- healthcheck — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenClaw Host Hardening
Overview
Assess and harden the host running OpenClaw, then align it to a user-defined risk tolerance without breaking access. Use OpenClaw security tooling as a first-class signal, but treat OS hardening as a separate, explicit set of steps.
Core rules
- Recommend running this skill with a state-of-the-art model (e.g., Opus 4.5, GPT 5.2+). The agent should self-check the current model and suggest switching if below that level; do not block execution.
- Require explicit approval before any state-changing action.
- Do not modify remote access settings without confirming how the user connects.
- Prefer reversible, staged changes with a rollback plan.
- Never claim OpenClaw changes the host firewall, SSH, or OS updates; it does not.
- If role/identity is unknown, provide recommendations only.
- Formatting: every set of user choices must be numbered so the user can reply with a single digit.
- System-level backups are recommended; try to verify status.
Workflow (follow in order)
0) Model self-check (non-blocking)
Before starting, check the current model. If it is below state-of-the-art (e.g., Opus 4.5, GPT 5.2+), recommend switching. Do not block execution.
1) Establish context (read-only)
Try to infer 1–5 from the environment before asking. Prefer simple, non-technical questions if you need confirmation.
Determine (in order):
- OS and version (Linux/macOS/Windows), container vs host.
- Privilege level (root/admin vs user).
- Access path (local console, SSH, RDP, tailnet).
- Network exposure (public IP, reverse proxy, tunnel).
- OpenClaw gateway status and bind address.
- Backup system and status (e.g., Time Machine, system images, snapshots).
- Deployment context (local mac app, headless gateway host, remote gateway, container/CI).
- Disk encryption status (FileVault/LUKS/BitLocker).
- OS automatic security updates status. Note: these are not blocking items, but are highly recommended, especially if OpenClaw can access sensitive data.
- Usage mode for a personal assistant with full access (local workstation vs headless/remote vs other).
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 · 246 lines · 70 tokens per session scan A adba53ffae39
healthcheck is a skill published in the GitHub repository the-open-agent/openagent (5,607 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 2,401 once invoked, about $0.0003 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
documents
Create, read, edit, review, comment on, sanitize, render, and validate Microsoft Word DOCX documents. Use whenever a DOCX or Word document is a primary input or deliverable, including reports, proposals, forms, templates, tracked revisions, comments, tables, images, headers, footers, and style-preserving edits.
Read, create, inspect, merge, split, rotate, encrypt, fill, and validate PDF files. Use when the user asks to work with a PDF or convert supported Markdown into a polished PDF in AstrBot.
skill-creator
Create, revise, and validate AstrBot Skills built around SKILL.md instruction bundles. Use when the user asks to create, scaffold, improve, package, or review a Skill for an AstrBot workspace, local installation, or plugin.
spreadsheets
Create, read, edit, analyze, convert, chart, and validate spreadsheet files including XLSX, XLSM, XLS, CSV, and TSV. Use when a spreadsheet is a primary input or deliverable, or when tabular data must remain editable and auditable in workbook form.
session-rag-eval
Run and debug Chatbox session attachment RAG model evaluation with synthetic and real long-file fixtures.
codebase-classification
Classify codebases before modification to choose appropriate development approach.