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 genudo-ai/genudo_mcp --skill configure-ai-modelgit clone --depth 1 https://github.com/genudo-ai/genudo_mcpWrote 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/genudo-ai/genudo_mcp/configure-ai-model)<a href="https://agentmods.dev/skills/genudo-ai/genudo_mcp/configure-ai-model"><img src="https://agentmods.dev/badge/skills/genudo-ai/genudo_mcp/configure-ai-model/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/genudo-ai/genudo_mcp/configure-ai-model"><img src="https://agentmods.dev/badge/skills/genudo-ai/genudo_mcp/configure-ai-model.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 | $0.00072 | $0.00324 |
| Opus 5 | $0.00036 | $0.00162 |
| Sonnet 5 | $0.00014 | $0.00065 |
| Haiku 4.5 | $0.00007 | $0.00032 |
Grade A, and why
configure-ai-model 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 11d 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.
What it actually says
Configure AI Model
Set how a pipeline picks its AI model — one fixed model, or a routed pool that sends easy messages to a cheap model and hard ones to a strong model.
Discover valid options first
get_pipeline_options returns the selectable AI models (and providers, languages, dialects,
channels). Use only IDs it returns.
Single model
Set ai_model_id (and optionally model_temperature) via update_pipeline (or create_pipeline
at build time). Leave is_model_routing_enabled off.
Model pool (routing)
Set is_model_routing_enabled = true and provide model_pool with exactly four tiers:
| Tier | Handles |
|---|---|
router |
classifies each message's complexity |
simple |
trivial / FAQ turns |
moderate |
normal sales/support turns |
complex |
reasoning-heavy or high-stakes turns |
Each tier takes a provider, a model, and short instructions. Routing without all four tiers is rejected.
Confirm
Echo the chosen model(s) and cost/quality intent, then update_pipeline. Report what changed.
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.
- 11d ago First seen · 38 lines · 72 tokens per session scan A 8a6b99f02c56
configure-ai-model is a skill published in the GitHub repository genudo-ai/genudo_mcp (0 stars, last pushed 11d ago), licensed MIT. It adds 72 tokens to every session and 324 once invoked, about $0.0004 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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