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 agentmods add skills/kimmingul/xllm/xllm-setupnpx skills add kimmingul/xllm --skill xllm-setupgit clone --depth 1 https://github.com/kimmingul/xllmWrote 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/kimmingul/xllm/xllm-setup)<a href="https://agentmods.dev/skills/kimmingul/xllm/xllm-setup"><img src="https://agentmods.dev/badge/skills/kimmingul/xllm/xllm-setup.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.00957 |
| Opus 5 | $0.00018 | $0.00478 |
| Sonnet 5 | $0.00007 | $0.00191 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
xllm-setup 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 5d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/xllm-setup — Install health check
<state>= project state dir:.xllm/(default) or legacy.grok/when the project already uses it.
Run these steps (do not only describe them).
1. Resolve + remember advisor path
Find xllm-advisor.js via (first hit):
.xllm/xllm-advisor-path(legacy:.grok/xllm-advisor-path)XLLM_ADVISOR_PATH/GROK_PLUGIN_ROOT/XLLM_PLUGIN_ROOT./scripts/xllm-advisor.js- plugin checkout path the user has open
Then run:
node <advisor.js> --remember
node <advisor.js> --which
Confirm .xllm/xllm-advisor-path (or legacy .grok/) exists and points at a
real file.
2. Artifact directories
Ensure:
<state>/artifacts/ask|xllm|proposals|exec/
(--remember / --doctor also create these.)
2.5 Project advisor wizard (posture packs — optional)
Resolve pins deterministically; the skill only renders and confirms.
-
Preview the recommended pack (default
balanced):node <advisor.js> --setup balanced --jsonThe resolver returns
{ roles, warnings, evidence, recommended_packs }.balancedleaves analysis/design OPEN (measured routing) and pins at most a free local critic — a pin FREEZES measured routing, so packs pin only genuine constraints.quality= max-spend lock,frugal= cost lock,local= offline lock,skip= clear pins. -
Ask ONE question, offering the first four of
recommended_packs(always includeskip). Show the effort legend (Quick=low / Standard=medium / Deep=high) and one-line role glosses. Never invent cloud model names — cloud pins omit the model. -
Show the resolved preview (roles + warnings + which stay OPEN and why), then on the user's accept:
node <advisor.js> --setup <pack> --applyPartial tweak:
--role analysis=grok@high(validated; one bad override writes nothing). Reverting:node <advisor.js> --setup skip --applyclears the posture pins. Verify withnode <advisor.js> --profile-show.
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.
- 5d ago First seen · 135 lines · 36 tokens per session scan A e3960fdd5a93
xllm-setup is a skill published in the GitHub repository kimmingul/xllm (2 stars, last pushed 13d ago), licensed MIT. It adds 36 tokens to every session and 957 once invoked, about $0.0002 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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