Borrowing it
Nothing to install: this file belongs to learningmatter-mit/AtomisticSkills. 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/learningmatter-mit/AtomisticSkills/main/GEMINI.mdgit clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkillsWrote 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/learningmatter-mit/atomisticskills/gemini-md)<a href="https://agentmods.dev/instructions/learningmatter-mit/atomisticskills/gemini-md"><img src="https://agentmods.dev/badge/instructions/learningmatter-mit/atomisticskills/gemini-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/learningmatter-mit/atomisticskills/gemini-md"><img src="https://agentmods.dev/badge/instructions/learningmatter-mit/atomisticskills/gemini-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 | $0.00696 | $0.00696 |
| Opus 5.5 | $0.00278 | $0.00278 |
| Sonnet 5.5 | $0.00139 | $0.00139 |
| Haiku 4.5 | $0.00070 | $0.00070 |
Grade A, and why
AtomisticSkills GEMINI.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 22d 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
100% identical to AtomisticSkills AGENTS.md — 2 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AtomisticSkills Agent Instructions
You are an atomistic research agent with access to literature, Skills, and MCP tools.
Read these rules files at the start of every conversation:
.agents/rules/research-standards.md— research protocol, intent classification, plan workflow.agents/rules/coding-standards.md— coding rules, environment management, MCP stability.agents/rules/mcp-environments.md— uv environment and MCP server runtime mapping
Read these on demand when the task requires it:
.agents/rules/skill-standards.md— for creating or editing a skill.agents/rules/workflow-standards.md— for creating or editing a workflow.agents/rules/plot-standards.md— for creating or editing a plotting script
Framework Overview
This project decomposes complex research tasks into three levels:
- Tools (
src/mcp_server/): Low-level operations exposed via MCP (relax structure, run MD, query databases). Strict typed I/O. - Skills (
skills/): Mid-level tutorials combining tools and scripts to solve focused tasks. Each has aSKILL.mdwith step-by-step instructions. - Workflows (
.agents/workflows/): High-level research campaigns that chain multiple skills.
When a user asks a research question, check workflows first for end-to-end protocols, then find the relevant skill(s).
Skill Discovery
Skills are at skills/. Scan frontmatter descriptions to find relevant ones:
grep -r "^description:" skills/*/SKILL.md
Then read the full SKILL.md for any matching skill and follow its numbered instructions.
Executing Skills
Skill commands run through the launcher venv/run:
venv/run <venv>[+<extra>] python skills/<skill-name>/scripts/<script>.py ...
Where <venv> is a shared project (cpu, mlip, fairchem) or a research stack (adit, diffcsp, mattergen, msms, reactot, scd), matching metadata.venv in the skill's SKILL.md, with optional extras if needed (e.g. cpu+openmm, mlip+lammps).
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.
- 22d ago Changed · +1 lines · +133 tokens per session 7b56155f23d4
- 1mo ago First seen · 61 lines · 563 tokens per session scan A d65ae6a2baff
AtomisticSkills GEMINI.md is an instructions file published in the GitHub repository learningmatter-mit/AtomisticSkills (186 stars, last pushed yesterday), licensed MIT. It adds 696 tokens to every session, about $0.0028 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to AtomisticSkills AGENTS.md, differing in 2 lines, and is treated as a copy.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.