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 grokgit 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/grok)<a href="https://agentmods.dev/skills/lingtai-ai/lingtai/grok"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/grok/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/grok"><img src="https://agentmods.dev/badge/skills/lingtai-ai/lingtai/grok.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 | $0.00019 | $0.00791 |
| Opus 5 | $0.00010 | $0.00396 |
| Sonnet 5 | $0.00004 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
preset-skill-grok 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 4d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
grok preset revision
Use this child for the named built-in grok preset. grokPreset in tui/internal/preset/preset.go:1375 ships grok-4.5, provider grok, OpenAI compatibility, https://opencode.ai/zen/go/v1, and OPENCODE_GO_API_KEY. This is the TUI's only verified Grok route; it has no vision capability. Custom is available for a user-owned xAI or other gateway, but is not the built-in route.
Template-specific settings
For the built-in route, read the official OpenCode Go docs and call the authenticated gateway GET https://opencode.ai/zen/go/v1/models. That served-model list is authoritative for this preset; the xAI API docs are only for model-level capability facts and do not establish an xAI route in the TUI. Preserve lowercase IDs and the shared Go credential. Do not use an xAI catalog entry as proof that OpenCode Go serves it. GROK_API_KEY is only the provider-generic fallback; the shipped default keeps OPENCODE_GO_API_KEY because the default endpoint is the shared Go gateway.
TUI surfaces to revise
Start at grokPreset in tui/internal/preset/preset.go. Revise ProviderRegionURLs["grok"] and ProviderDefaultEnv for route/env changes, providerModels["grok"] for the picker, and modelHasVision["grok-4.5"] for a reviewed vision fact in tui/internal/tui/preset_editor.go. Recheck the constructor's absent vision key and the OpenCode Go default row. Follow tui/internal/tui/SKILL.md and tui/CONTRACT.md.
The picker currently offers grok-4.5 only and modelHasVision records it false: the Go endpoint's image-input mapping is not pinned. A Custom row does not turn an xAI endpoint into the shipped route.
Reviewed deterministic revision
Prepare an evidence-bound manifest and explicit input, then run lingtai-tui presets revise --manifest PATH --input PATH --mode dry-run|check|apply [--output-dir PATH]. Review the JSON plan, use dry-run/check before apply, and apply only to a new explicit output directory. revision.go validates hashes, route bindings, and evidence and preserves unowned bytes. This amendment does record the evidence-bound no-op: Grok remains OpenCode Go-only at grok-4.5, with no product refresh to an unverified Go model or vision route.
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.
- 4d ago Changed · -19 lines · -1 tokens per session 200a946b8cbe
- 12d ago First seen · 84 lines · 20 tokens per session scan A 241e17cdbff7
preset-skill-grok is a skill published in the GitHub repository Lingtai-AI/lingtai (677 stars, last pushed yesterday), licensed Apache-2.0. It adds 19 tokens to every session and 791 once invoked, about $0.0001 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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