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 instructions/ericyuan2007/gpuplane/claude-mdgit clone --depth 1 https://github.com/EricYuan2007/GPUPlaneWrote 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/ericyuan2007/gpuplane/claude-md)<a href="https://agentmods.dev/instructions/ericyuan2007/gpuplane/claude-md"><img src="https://agentmods.dev/badge/instructions/ericyuan2007/gpuplane/claude-md.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 | $0.01804 | $0.01804 |
| Opus 5 | $0.00902 | $0.00902 |
| Sonnet 5 | $0.00361 | $0.00361 |
| Haiku 4.5 | $0.00180 | $0.00180 |
Grade A, and why
GPUPlane CLAUDE.md 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 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.
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.
This is a copy
92% identical to GPUPlane AGENTS.md — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — GPUPlane (mirrors AGENTS.md, the canonical agent guide)
This file is kept in sync with
AGENTS.md. Edit one, mirror to the other. Claude Code auto-loads this file; other agents (Codex/Cursor) load AGENTS.md.
Canonical agent guidance for this repo.
CLAUDE.mdmirrors it; keep both in sync when editing. Load this before working in GPUPlane.
GPUPlane is an agent-native training control plane for personal GPUs. This
file is the short rulebook an AI agent (Claude Code, Codex, Cursor, …) follows
when running or extending it. The full design lives in docs/.
What this project is (and isn't)
- Is: a control plane that schedules training jobs on a single workstation / small GPU fleet, observes them with training semantics (run / checkpoint / evaluation), and exposes a read+write MCP surface so an agent can drive the experiment loop.
- Isn't: a W&B/MLflow replacement (no experiment tracking ambition), a Docker/K8s orchestrator (jobs are bare processes on the agent host), or a multi-tenant cloud product.
Stay on the bare-process + SQLite side of the line. Do not add containers, queues-as-a-service, or cloud SDKs to satisfy a request that "would be nicer in the cloud" — the whole value proposition is low-infra local GPU.
The experiment loop
run-experiment → monitor-experiment → analyze-results → (keep / revert)
submit_job get_run_summary compare_runs checkpoint path
list_events get_best_checkpoint git keep/revert
diagnose_run evaluate_checkpoint
The three skills in .claude/skills/gpu-training/ encode this loop. Prefer
invoking them over improvising with the MCP tools directly — they carry the
conventions below.
Conventions
Metrics
- Training scripts must log metrics via the GPUPlane SDK or TensorBoard.
Without metrics,
diagnose_run/ anomaly detection / recommendation have nothing to read. Metric names are namespaced (train/loss,eval/loss). - One primary metric drives every "best" decision. It resolves through
experiment → project → global inheritance; cross-scope comparisons use only
their common scope or an explicit metric. Default
eval/loss(minimize) oreval/accuracy(maximize). Don't multi-objective.
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 · 149 lines · 1,804 tokens per session scan A 0c8829c55b59
GPUPlane CLAUDE.md is an instructions file published in the GitHub repository EricYuan2007/GPUPlane (0 stars, last pushed 9d ago), licensed Apache-2.0. It adds 1,804 tokens to every session, about $0.0090 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to GPUPlane AGENTS.md, differing in 6 lines, and is treated as a copy.
Other instructions, from other repositories
bio-gene-to-reference-tree copilot-instructions.md
Copilot instructions for Hongda-Zhao/bio-gene-to-reference-tree, a project described as: Auditable agent skill for resolving protein queries, selecting references, and planning reproducible phylogenetic trees.
braina GEMINI.md
Instructions for brainets/braina, covering project: braina (brain interaction analysis), 1. project context & purpose, 2. commands, verify environment (all core dependencies) and run the verification test suite for frites + hoi.
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Instructions for lucafusarbassini/research-automation, covering ricet - research automation framework, project overview, claude-flow mcp, workflow habits and file organization.
shannon-prover CLAUDE.md
Claude Code instructions for SkyShannonProver/shannon-prover, covering shannon prover: claude entry point, current boundary, easycrypt environment, eval safety and current documentation.
SciCrucible CLAUDE.md
Claude Code instructions for Xinyang-Li666/SciCrucible, covering 科学知识库, 知识库结构, 可用命令, 项目目录 and 工作原则.
torchcell CLAUDE.md
Claude Code instructions for Mjvolk3/torchcell, covering vision -- the virtual cell (north star), for local configs, git worktrees, programming guide and provenance & reproducibility.