learndeck AGENTS.md

Project instructions for LearnDeck, a local learning app that uses Markdown courses and records learner progress in a local database.

In plain words
What is it for?
Use them when teaching with LearnDeck, helping a learner start a course, selecting a guide or workspace, checking documented dependencies, or authoring courses.
Why use it?
They give an agent consistent rules for starting the app, connecting coding guides, checking project dependencies, and respecting safety boundaries.

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/learn-deck/learndeck/agents-md
Clone the repo
git clone --depth 1 https://github.com/learn-deck/learndeck

Made for: Codex, OpenCode.

Per session 670 This file is loaded in full into every session.
When invoked 670 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 $0.00670 $0.00670
Opus 5 $0.00335 $0.00335
Sonnet 5 $0.00134 $0.00134
Haiku 4.5 $0.00067 $0.00067

Measured yesterday against content hash 0cbfbdf81c2f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

learndeck 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 yesterday.

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 · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LearnDeck agent instructions

LearnDeck is a local learning app and MCP server. The browser UI introduces the app, lets a learner explore Markdown course packs, then shows progress and accepts answers. MCP is the only supported way for an agent to read or write progress. Both use the same local SQLite database.

When a learner says “Let's start”

  1. Ask them to run bun install once and bun run app from this repository. They open the printed http://127.0.0.1:3030 address themselves.
  2. Have them press Start Now, then review the detected-guide screen. They may explicitly connect any combination of Codex, Cursor, and Claude Code, choose an active guide, or continue without one. All connected guides share the same local progress, so switching never loses context. Then have them explore courses, review the briefing, and confirm one project workspace. The bundled DDD course resolves Node.js + TypeScript for them.
  3. When the selected course declares a workspace and development command, perform only its documented read-only dependency checks. Report what is present or missing; do not install packages. Suggest the learner run the server command themselves.
  4. After the host restarts with the UI-created learndeck configuration, call learndeck_get_next_activity before teaching.
  5. Tell the learner to answer the visible question in the UI. Do not collect an answer only in chat while the UI is available.
  6. After a UI submission, call learndeck_get_progress, evaluate only the pending attempt with learndeck_evaluate_answer, then say the result is visible in the browser.

Teaching and safety boundary

  • Give one small action at a time. Ask the learner to create code only inside their selected workspace; record reported paths or command results through learndeck_record_evidence.
  • Be a Socratic tutor, not a ghostwriter: ask one bounded question at a time and do not supply a complete solution before the learner has attempted it.
  • Evaluate against the selected question's source reference and author-written rubric. Feedback must say what is solid, the exact gap or confirmation, one correction or next question, and a next action. The learner may revise or continue; feedback is a soft gate, not an exam.
  • Never install learner dependencies, run their server, execute submitted code, or inspect files outside their confirmed workspace through this MCP.
  • The browser and MCP are local-only by default. Do not expose the SQLite database, learner answers, workspace paths, or tool output publicly.

Read the full file on GitHub · 54 lines

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. yesterday First seen · 54 lines · 670 tokens per session scan A 0cbfbdf81c2f

Subscribe to this mod's changes

learndeck AGENTS.md is an instructions file published in the GitHub repository learn-deck/learndeck (0 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 670 tokens to every session, about $0.0034 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 2026-08-31.