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/CLAUDE.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/claude-md)<a href="https://agentmods.dev/instructions/learningmatter-mit/atomisticskills/claude-md"><img src="https://agentmods.dev/badge/instructions/learningmatter-mit/atomisticskills/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 5.1 | $0.00820 | $0.00820 |
| Opus 5 | $0.00410 | $0.00410 |
| Sonnet 5 | $0.00164 | $0.00164 |
| Haiku 4.5 | $0.00082 | $0.00082 |
Grade A, and why
AtomisticSkills 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 90 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.
Project Rules
Read these rules files at the start of every conversation (imported below via @):
.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— conda environment to MCP server mapping
@.agents/rules/coding-standards.md @.agents/rules/mcp-environments.md @.agents/rules/research-standards.md
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.agents/rules/release-standards.md— for preparing a release tag
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 (
.agents/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 .agents/skills/. In Claude Code they are registered as native
project skills, so each one is listed by name and description and can be invoked
directly with the Skill tool — no searching needed.
If the skills are not listed, they have not been configured yet. Run:
python configure_mcp.py --agent claude
This symlinks every .agents/skills/<name> into .claude/skills/<name>, which
Claude Code discovers automatically. .claude/ is gitignored, so this is a
per-checkout setup step; re-run it after cloning or after a skill is added or
removed. .agents/skills/ stays the single source of truth — the symlinks are
never copies.
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.
- 3d ago First seen · 90 lines · 820 tokens per session scan A 0e380696e77e
AtomisticSkills CLAUDE.md is an instructions file published in the GitHub repository learningmatter-mit/AtomisticSkills (161 stars, last pushed 3d ago), licensed MIT. It adds 820 tokens to every session, about $0.0041 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 2026-09-03.
Other instructions, from other repositories
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.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
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).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
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.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.