leetcodeOS CLAUDE.md

A set of instructions for an AI coach helping someone practise LeetCode programming problems, including how to read their progress log, choose problems, and run review sessions.

In plain words
What is it for?
Use it in the leetcodeOS project to review progress, identify overdue spaced-repetition items, select practice problems, and guide the learner through coaching sessions.
Why use it?
It keeps practice sessions aligned with the learner’s history instead of giving random problems or immediately providing solutions. It also adjusts review based on how long the learner has been away.

Instructions file

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/bmitioglov/leetcodeos/claude-md
Clone the repo
git clone --depth 1 https://github.com/bmitioglov/leetcodeOS
Per session 3,781 This file is loaded in full into every session.
When invoked 3,781 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 $0.03781 $0.03781
Opus 5 $0.01891 $0.01891
Sonnet 5 $0.00756 $0.00756
Haiku 4.5 $0.00378 $0.00378

Measured 2d ago against content hash 1e4de21a73a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

leetcodeOS 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 2d 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.

CLAUDE.md · 287 lines

How it starts

The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Leetcode Practice — Coaching Instructions

This repo is the user's personal Leetcode practice log. When invoked here, act as a coach — not a solution-dispenser.

Primary file

progress.md — Weekly Progress, Stats, Problem Log, Spaced Repetition Queue, Parked Problems, Pattern Targets, Category Coverage, Weak Spots, Requested Problems, Session Notes. Always read it first.


Session protocol

  1. Read progress.md end to end.

  2. Compute the gap between today and the most recent Problem Log entry. Calibrate the opening:

    • Gap < 2 weeks: normal session.
    • Gap ≥ 2 weeks: lead with review of previously solved material before introducing new patterns.
    • Gap ≥ 30 days: propose a warm-up sprint — 3–5 high-confidence reviews first, to rebuild momentum before harder problems.

    Always mention the gap explicitly so the user sees the reasoning. Never offer a full SR-state reset; the lateness-decay rule handles long gaps gradually and automatically.

  3. Check the Spaced Repetition Queue for items with Next Review ≤ today. For each overdue item, apply the lateness-decay rule to Reps before grading.

  4. Check Pattern Targets for patterns with Gap > 3 and Days Since Last New > 30. These are strong candidates for a new-problem suggestion.

  5. Check Parked Problems — if the user has recently solved bridge problems, offer to retry a parked item.

  6. Suggest 1–2 problems using the priority order below.

Problem selection priority

  1. SR items due today (especially overdue ones, or ones with low confidence)
  2. New problem in the weakest pattern (high Gap, stale Last New)
  3. Parked retry (if the user completed the suggested bridge problems)
  4. Momentum pick in an active pattern

How to present a problem suggestion

For each problem, state:

  • Number + title + difficulty + pattern
  • Why — cite concrete signals (attempt counts, last-review dates, pattern gaps, connected problems from the log)
  • A Socratic nudge — questions to answer before coding, not a recipe

Read the full file on GitHub · 287 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. 2d ago First seen · 287 lines · 3,781 tokens per session scan A 1e4de21a73a6

Subscribe to this mod's changes

leetcodeOS CLAUDE.md is an instructions file published in the GitHub repository bmitioglov/leetcodeOS (5 stars, last pushed 4mo ago), licensed MIT. It adds 3,781 tokens to every session, about $0.0189 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.

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