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 AIops-tools/AI-Guardian --skill ai-guardiangit clone --depth 1 https://github.com/AIops-tools/AI-GuardianWrote 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/aiops-tools/ai-guardian/ai-guardian)<a href="https://agentmods.dev/skills/aiops-tools/ai-guardian/ai-guardian"><img src="https://agentmods.dev/badge/skills/aiops-tools/ai-guardian/ai-guardian/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/aiops-tools/ai-guardian/ai-guardian"><img src="https://agentmods.dev/badge/skills/aiops-tools/ai-guardian/ai-guardian.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 | $0.00419 | $0.04005 |
| Opus 5 | $0.00210 | $0.02003 |
| Sonnet 5 | $0.00084 | $0.00801 |
| Haiku 4.5 | $0.00042 | $0.00400 |
Grade A, and why
ai-guardian 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.
How it starts
The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Guardian
Disclaimer: Community-maintained open-source project, not affiliated with, endorsed by, or sponsored by Ollama, IGEL, or any AI-security vendor. Product and trademark names belong to their owners. Source at github.com/AIops-tools/AI-Guardian under the MIT license.
Governed observability + governance for on-endpoint local LLMs (Ollama) —
21 MCP tools, every one wrapped with the bundled @governed_tool harness: a
local unified audit log under ~/.ai-guardian/, token/runaway budget guard,
undo-token recording, and descriptive risk tiers. It is the
complement to IGEL AI Armor: AI Armor governs whether a local model may run;
ai-guardian records what it did and gates what leaves in the prompt.
Ollama keeps no queryable prompt history (context is client-supplied each
request), so ai-guardian observes on two fronts: passive inventory / state
auditing over /api/tags, /api/ps, /api/show, /api/version; and opt-in
route-through content governance — a caller sends a prompt through
guarded_generate / observe_chat, which scans + policy-gates + records it and
only then calls Ollama.
Standalone: the governance harness is bundled in the package (
ai_guardian.governance) — no external skill-family dependency. A transparent capture proxy for other clients' traffic is v0.2 roadmap, and IGEL AI Armor interop is doc-level positioning.
What This Skill Does
| Group | Tools | Count | Read/Write |
|---|---|---|---|
| Inventory / state | list_models, running_models, model_details, server_status, vram_usage |
5 | read |
| Policy / provenance | policy_view, model_provenance |
2 | read |
| Content governance (read) | scan_prompt, usage_events, anomaly_report |
3 | read |
| Model lifecycle | pull_model (medium), remove_model (high), unload_model (medium) |
3 | write |
| Policy writes | set_model_allowlist, set_model_denylist, pin_model_digest (all medium) |
3 | write |
| Route-through guard | guarded_generate, observe_chat (medium) |
2 | write |
| Undo | undo_list, undo_apply |
2 | undo |
What ships with it
4 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.
- 10d ago First seen · 206 lines · 419 tokens per session scan A 2fa412b5f1b3
ai-guardian is a skill published in the GitHub repository AIops-tools/AI-Guardian (0 stars, last pushed 8d ago), licensed MIT. It adds 419 tokens to every session and 4,005 once invoked, about $0.0021 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 2026-08-31.
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