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 richfrem/agent-plugins-skills --skill local-llm-setupgit clone --depth 1 https://github.com/richfrem/agent-plugins-skillsWrote 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/richfrem/agent-plugins-skills/local-llm-setup)<a href="https://agentmods.dev/skills/richfrem/agent-plugins-skills/local-llm-setup"><img src="https://agentmods.dev/badge/skills/richfrem/agent-plugins-skills/local-llm-setup.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.00902 |
| Opus 5 | $0.00039 | $0.00451 |
| Sonnet 5 | $0.00016 | $0.00180 |
| Haiku 4.5 | $0.00008 | $0.00090 |
Grade A, and why
local-llm-setup scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl http://localhost:8089/health # must return {"status":"ok"} How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Primary Use Case: Mode B Task Delegation
Mode B is the fast path. run_agent.py sends a lean prompt directly to llama-server — no proxy overhead, no 29K system prompt. Measured: ~2s wall clock for a typical bounded task.
# Start llama-server (required for cli=llama)
python3 scripts/run_server.py
curl http://localhost:8089/health # must return {"status":"ok"}
# Mode B task delegation — fast path (~2s)
time python3 scripts/run_agent.py agents/refactor-expert.md target.py output.md \
"List the top 3 issues." --cli llama
# Mode B with custom max tokens
python3 scripts/run_agent.py /dev/null /dev/null /tmp/out.md \
"Summarize this architecture decision." --cli llama --max-tokens 300
Available agent personas (pass as PERSONA_FILE):
| Persona | Role |
|---|---|
agents/refactor-expert.md |
Code quality — SOLID/DRY smell taxonomy |
agents/security-auditor.md |
OWASP vulnerability audit |
agents/architect-review.md |
C4/SOLID structural review |
agents/red-team-reviewer.md |
Adversarial exploit analysis |
agents/compliance-reviewer.md |
Coding standards drift detection |
agents/pr-reviewer.md |
Diff review — ship/hold decision |
agents/test-writer.md |
Unit test generation |
agents/debate-synthesizer.md |
Multi-perspective synthesis |
agents/output-validator.md |
Output guardrail / hallucination check |
agents/self-critic.md |
Reflection loop — task-fit check |
agents/performance-analyst.md |
Bottleneck and scale analysis |
What ships with it
11 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.
- evals/evals.json 553 B
- evals/results.tsv 34 B
- references/acceptance-criteria.md 42 B
- references/cheapest_models.json 40 B
- references/cheapest_models.md 38 B
- scripts/disable_global_routing.py 42 B runs code
- scripts/enable_global_routing.py 41 B runs code
- scripts/kv_cache_orchestrator.py 41 B runs code
- scripts/routing_proxy.py 33 B runs code
- scripts/run_agent.py 29 B runs code
- scripts/run_server.py 30 B runs code
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 First seen · 78 lines · 78 tokens per session scan A 7149f8bdede3
local-llm-setup is a skill published in the GitHub repository richfrem/agent-plugins-skills (6 stars, last pushed today), licensed MIT. It adds 78 tokens to every session and 902 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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