---
name: infra-advisor
description: "Instructions for the upstream workflow: Audit the local cluster's hardware/software/MCP setup and recommend changes that cut token cost — GPU upgrades, Hailo NPU for vision, moving the inference node to Linux, running Qdrant locally, wiring MCP — with an ASCII cluster diagram. Also provides an auto one-pass audit (directives + infra + code duplication + skills) on the project. Use when the user asks how to reduce token/usage cost via hardware/infra, wants cluster setup tips, an ASCII diagram of their setup, or a quick all-in-one audit."
license: MIT
metadata:
  version: "1.0.0"
  domain: agent-skills
  canonical-name: infra_advisor
---
# infra-advisor — cut token cost beyond the code

## Package scope and prerequisites

This catalog ships instructions, not the executable runtime. Python modules, scripts, local services and optional tools named below must be installed separately from the upstream project. Check their availability before running commands; if they are missing, explain the prerequisite instead of claiming execution or results. The host agent may use model tokens while following these instructions.

Most audits only look at code. This looks at the **machine and the local cluster**
and recommends concrete hardware/software/infra changes that move work off paid
cloud models — then bundles a fast one-pass audit of the project.

## Commands

```bash
# Cluster tips + ASCII diagram
python -m skills.infra_advisor.cli tips
python -m skills.infra_advisor.cli tips --subnet --json

# One-pass audit on the project where the toolkit is installed
python -m skills.infra_advisor.cli auto .
python -m skills.infra_advisor.cli auto /path/to/project --json
```

## Infra tips (rules, prioritized P0→P3)

- **Install a local LLM** (LM Studio/Ollama) if none — the foundation for any saving.
- **Add/upgrade a GPU** (≥12-16 GB VRAM) → run a 7-14B coder locally.
- **Add a Hailo-8 / 8L / 10 NPU** → a possible vision adapter to evaluate; the current `media_loader` prototype contains placeholders, not verified extraction.
- **Move the always-on inference node to Linux/WSL2** → no forced Windows reboots/updates
  killing the endpoint; more free VRAM/RAM.
- **Run Qdrant locally** → support workflows that actually implement a vector service; `ResponseCache`'s main fuzzy lookup currently uses lexical overlap.
- **Dedicate the strongest host** as a shared inference node for all projects.
- **Wire the MCP server** (`bootstrap`) so the agent actually uses the local tools.

Each tip carries `why` and an `impact` (expected token/cost effect). An ASCII
cluster diagram is rendered by default (`--json` for machine-readable).

## Auto audit

`auto` combines the cheap, reliable passes into one report:
**directives** health (`directives_audit`) · **infra** tips + diagram · **duplicate
function bodies** across files (upstream AST analysis; measure total host and runtime costs) · **skill catalog** size · plus
pointers to deeper passes (full `mousquetaires`/fallow pipeline, `skill_project_optimizer`,
`understand-anything`, `botte` terminal compression).

Exposed via [[llm-mcp]] as `infra_tips` and `auto_audit`. Related: [[bootstrap]],
[[llm-backends]], [[directives-audit]], [[skill-finder]].