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 Lingtai-AI/lingtai --skill preset-healthgit clone --depth 1 https://github.com/Lingtai-AI/lingtaiWrote 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/lingtai-ai/lingtai/preset-health)<a href="https://agentmods.dev/skills/lingtai-ai/lingtai/preset-health"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/preset-health/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/lingtai-ai/lingtai/preset-health"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/preset-health.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 | $0.00129 | $0.02643 |
| Opus 5 | $0.00064 | $0.01321 |
| Sonnet 5 | $0.00026 | $0.00529 |
| Haiku 4.5 | $0.00013 | $0.00264 |
Grade A, and why
preset-health 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.
How it starts
The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preset Health Check (read-only)
A repeatable, read-only procedure for testing whether saved presets are healthy, classifying any failures, and producing an actionable report — without printing or mutating credentials.
Read-only contract. This reference enumerates, probes, and reports. It does not edit
~/.lingtai-tui/presets/saved/*.json, agentinit.json, or anymanifest.preset.allowedlist. Remediation is described as a recommendation for the human to confirm and apply (or to explicitly authorize you to apply through the normal preset tooling). Never run a "fix" step automatically.
When to use
- The human asks "are my presets still working?" or "which preset is broken?"
system(action="presets")surfaced a non-okconnectivity status (for exampleno_credentials, an auth failure, or an unreachable endpoint).- A provider rotated keys, retired a model, or moved an endpoint and you need to find every saved preset affected.
- A new agent needs a clear procedure to triage presets before relying on them.
Where saved presets live
Saved (user-owned) presets are JSON files here:
~/.lingtai-tui/presets/saved/*.json
Built-in templates live under ~/.lingtai-tui/presets/templates/ and are
rewritten on every lingtai-tui bootstrap — the directory itself is the marker
distinguishing built-in from user-owned, so a health check focuses on
saved/. The skill tree this reference ships in is extracted to
~/.lingtai-tui/utilities/swiss-knife/reference/preset-health/SKILL.md.
Each preset's relevant shape (other fields omitted):
{
"manifest": {
"llm": {
"provider": "gemini",
"model": "gemini-2.0-flash",
"base_url": "https://...",
"api_key_env": "GEMINI_API_KEY"
}
}
}
The credential is referenced indirectly through api_key_env (an environment
variable name), not stored inline. That indirection is what lets a health
check report "credential missing" without ever reading the secret value.
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 · 229 lines · 129 tokens per session scan A 6fb0d566f897
preset-health is a skill published in the GitHub repository Lingtai-AI/lingtai (677 stars, last pushed yesterday), licensed Apache-2.0. It adds 129 tokens to every session and 2,643 once invoked, about $0.0006 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 2026-09-03.
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