Borrowing it
Nothing to install: this file belongs to Platano78/wigi-llm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Platano78/wigi-llm/master/CLAUDE.mdgit clone --depth 1 https://github.com/Platano78/wigi-llmWrote 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/instructions/platano78/wigi-llm/claude-md)<a href="https://agentmods.dev/instructions/platano78/wigi-llm/claude-md"><img src="https://agentmods.dev/badge/instructions/platano78/wigi-llm/claude-md/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/instructions/platano78/wigi-llm/claude-md"><img src="https://agentmods.dev/badge/instructions/platano78/wigi-llm/claude-md.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 | $0.00747 | $0.00747 |
| Opus 5 | $0.00374 | $0.00374 |
| Sonnet 5 | $0.00149 | $0.00149 |
| Haiku 4.5 | $0.00075 | $0.00075 |
Grade A, and why
wigi-llm CLAUDE.md 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 9d 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.
- router-control.sh must work standalone without dependencies beyond curl, bash, and jq How it starts
The opening of the file, as written. The whole thing — 44 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wigi-LLM
First, read
AGENTS.mdin this directory and follow its routing. It is the canonical brain (areas, Inputs tables, pickup/handoff). This file is retained as Layer-3 reference detail (key files, architecture, build rules) for the area you route into.
A widget suite for the G.SKILL WigiDash touchscreen panel providing hardware-level control and monitoring for local LLM infrastructure.
What This Is
Six C# WigiDash widgets that turn the panel into a dedicated control surface for local AI. The daily-driver is the LLM Launcher (config-driven via buttons.json); the rest are experimental — model dashboards, brain monitors, router health, clipboard-to-LLM pipeline.
Key Files
scripts/router-control.sh— CLI wrapper for llama.cpp router API (sourcesvram-utils.sh, callsstart-router.sh)scripts/start-router.sh— Router server lifecycle (start/stop/status); the "Router ON" button runs thisscripts/kill-all-llm.sh— KILL button script: stops router + flushes VRAMscripts/vram-utils.sh— VRAM helper functions sourced by router-control.shscripts/gpu-vram-server.py— Remote GPU VRAM HTTP serverwigidash/examples/— Example buttons.json configurationswigidash/icons/— Pixel art icon set for model buttonswigidash/src/LLMLauncherWidget/— The daily-driver widget (reads buttons.json at runtime)wigidash/src/Shared/GpuInfo.cs— Shared GPU VRAM detection helper used by the experimental widgetswigidash/src/Shared/WslPaths.cs— Shared WSL POSIX → Windows path translation helperwigidash/src/*Widget/(all except LLMLauncherWidget) — Experimental C# widgets; the complete, current list lives in theAGENTS.mdAreas table
Architecture
Panel → Windows → WSL exec → router-control.sh → llama.cpp router API (port 8081) → GPU Widgets → nvidia-smi.exe (local VRAM) or gpu-vram-server.py (remote VRAM)
Rules
- Keep buttons.json examples valid JSON at all times
- router-control.sh must work standalone without dependencies beyond curl, bash, and jq
- Icons are paired: always provide both
icon_name_active.pngandicon_name_off.png - Do not hardcode user-specific paths — use YOUR_USER placeholders in examples
- Do not hardcode GPU VRAM sizes — use GpuInfo.cs for auto-detection
- Do not hardcode personal IPs, usernames, or domains in any shared file
- C# widgets target .NET Framework 4.7.2 and must reference WigiDashWidgetFramework.dll (HintPath = bare filename, drop the DLL next to the .csproj when building)
- The experimental widgets link to Shared/GpuInfo.cs via
<Compile Include="..\Shared\GpuInfo.cs" Link="GpuInfo.cs" />— LLMLauncherWidget is self-contained and does NOT depend on it - LLMLauncherWidget reads buttons.json from its widget directory at runtime; the JSON is per-user config, never bundled into the DLL
- LLMLauncherWidget has known hardcoded constants for ROUTER_API_HOST/PORT and LLM_SERVER_PORTS at top of WidgetInstance.cs — fine for now, fix if a user reports needing non-default ports
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.
- 9d ago First seen · 44 lines · 747 tokens per session scan A e39c08ad92ba
wigi-llm CLAUDE.md is an instructions file published in the GitHub repository Platano78/wigi-llm (2 stars, last pushed 2mo ago), licensed MIT. It adds 747 tokens to every session, about $0.0037 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 2026-08-31.
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