Superlearn AGENTS.md

Superlearn AGENTS.md is an instructions file for Codex, OpenCode from raiyanyahya/Superlearn. It costs 383 tokens per session, scanned A, original, MIT.

Repository instructions for Superlearn, a tool that turns a learning request into a researched, interactive learning board. They also describe how to develop and test the Superlearn codebase.

In plain words
What is it for?
Use them when someone wants to learn, study, or research a topic, or when working on Superlearn's Python scripts and single-file web app.
Why use it?
They give the coding agent a required workflow for researching topics and clear rules for changing this repository safely.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/raiyanyahya/superlearn/agents-md
Clone the repo
git clone --depth 1 https://github.com/raiyanyahya/Superlearn

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for Superlearn AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/raiyanyahya/superlearn/agents-md.svg)](https://agentmods.dev/instructions/raiyanyahya/superlearn/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/raiyanyahya/superlearn/agents-md"><img src="https://agentmods.dev/badge/instructions/raiyanyahya/superlearn/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 383 This file is loaded in full into every session.
When invoked 383 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00383 $0.00383
Opus 5 $0.00192 $0.00192
Sonnet 5 $0.00077 $0.00077
Haiku 4.5 $0.00038 $0.00038

Measured 5d ago against content hash 7a072a5988d3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Superlearn AGENTS.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 5d 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.

AGENTS.md · 31 lines

What it actually says

Superlearn

Superlearn turns "I want to learn X" into a researched, interactive learning board served at http://localhost:4321. It ships as a Claude Code plugin and as a standard Agent Skill for OpenAI Codex, Kilo (formerly Kilo Code), and any agent that reads SKILL.md.

If the user asks to learn, study, or research a topic

Follow the pipeline in .agents/skills/superlearn/SKILL.md — research first, plan, iterate until saturated, author and validate the board, serve, keep iterating. Do not improvise a different flow, and never author a board before research is saturated. (skills/superlearn/SKILL.md is the same playbook in its Claude Code plugin edition.)

Working on this repo

  • Zero dependencies by design: every script in scripts/ is Python 3.9+ standard library, and the app is one file (app/index.html) with no build step. Keep it that way.
  • Run the tests with python3 -m unittest discover -s tests -v.
  • The board contract lives in scripts/validate_board.py; if you change it, update the schema documentation in skills/superlearn/SKILL.md (and vice versa) so they never disagree.
  • .agents/skills/superlearn/SKILL.md must end with the body of skills/superlearn/SKILL.md verbatim — a unit test enforces this. Edit the Claude edition first, then regenerate or mirror the portable copy.
  • The scrapers must stay polite: identify honestly, tiny request volume, no login walls, no paywall or CAPTCHA circumvention — see "The researched data isn't ours" in the README.
Changes

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.

  1. 5d ago First seen · 31 lines · 383 tokens per session scan A 7a072a5988d3

Subscribe to this mod's changes

Superlearn AGENTS.md is an instructions file published in the GitHub repository raiyanyahya/Superlearn (109 stars, last pushed 20d ago), licensed MIT. It adds 383 tokens to every session, about $0.0019 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 2026-08-30.

Related

Other instructions, from other repositories