What does this skill do, and when should you use it?
Algo Sensei is a prompt-only Agent Skill that turns Claude into a data structures & algorithms mentor. It automatically routes your request into one of five modes: concept tutoring, progressive hints, code review, mock interviews, and pattern recognition training. Its teaching philosophy leans on the Socratic method and progressive disclosure — hints first, deeper reveals only when you're stuck, never a bare copy-paste solution. It supports many programming languages (Python, Java, C++, Go, and more) and tracks your skill level and language preference within a session. The MIT-licensed repository centers on SKILL.md, backed by five mode files, a solution template, and a DSA complexity cheatsheet.
It reads your problem or code, detects intent, and engages the matching mode: Tutor mode explains concepts with examples and ASCII diagrams; Hint mode delivers a 5-level progressive hint ladder (from observation nudges down to a pseudocode skeleton as a last resort); Review mode audits code for correctness, time/space complexity, edge cases, and optimization opportunities; Interview mode role-plays a professional interviewer with a performance rubric and improvement plan; Pattern Mapper mode teaches you to identify which algorithmic pattern fits a problem (two pointers, sliding window, DP, monotonic stack, etc.). Solutions follow templates/solutions/solution-template.md and reference docs/dsa-cheatsheet.md for complexity standards. It runs no scripts and makes no external calls — everything is instruction-driven.
- A job seeker prepping for technical interviews who is stuck on a problem and wants a nudge, not a spoiler, to preserve independent thinking.
- A beginner who wants concepts like dynamic programming or graph algorithms explained from the ground up at their own level.
- A LeetCode practitioner who has a working solution but wants complexity analysis and optimization feedback before moving on.
- A candidate close to a FAANG interview who wants to practice explaining solutions aloud under realistic conditions with structured feedback.
- A developer working in Python, Java, C++, or Go who wants examples and idioms adapted to their preferred language.
How do you install this skill?
- The skill depends on modes/, templates/ and docs/ files; copy the full directory or mode instructions will be missing and functionality degraded.
- Documentation is English-only with no Chinese support; core experience depends on Claude Code/Claude.ai reachability, which mainland-China users should verify themselves.
- No versioning or changelog; behavior may change on update—pin a specific commit when installing.
- All effectiveness claims are static documentation statements without independent execution verification; real accuracy of 'intelligent mode detection' is unknown.
- Publisher identity is unverified and the referenced modes/ files were outside this review; read all files yourself before use.
For Claude Code (personal skills, all projects): git clone https://github.com/karanb192/algo-sensei.git, then cp -r algo-sensei ~/.claude/skills/, and restart Claude Code. For team-shared installation in a project: copy the folder to /path/to/your/project/.claude/skills/ and commit it to git. For Claude.ai: in a Project, upload SKILL.md, the 5 files from modes/, docs/dsa-cheatsheet.md, and templates/solutions/solution-template.md (a quick setup with SKILL.md alone works but omits the detailed mode instructions).
git clone --depth 1 https://github.com/karanb192/algo-sensei.git ~/.claude/skills/algo-senseiGenerated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- I'm stuck on LeetCode #3, give me a hint
- Explain dynamic programming
- Review my Two Sum solution
- Do a mock interview with a medium problem
Once installed, the skill activates automatically when you raise a DSA/LeetCode topic. Describe what you need and it picks the mode: "I'm stuck on LeetCode #3, give me a hint" triggers Hint mode; "Explain dynamic programming" triggers Tutor mode; "Review my Two Sum solution" (with code pasted) triggers Review mode; "Do a mock interview with a medium problem" triggers Interview mode; "I don't know what approach to use here" triggers Pattern Mapper mode. If you don't specify a language, it asks for your preference.
What are this skill's strengths and limitations?
- Free and MIT-licensed; purely prompt-based, so no dependencies or setup beyond copying files.
- Thoughtful 5-level progressive hint design that guides you to the answer without spoiling it.
- Intelligent mode routing means you describe the need instead of picking a feature manually.
- The README is candid about how it differs from LeetCode Premium, generic prompts, and video tutorials.
- The scripts/ directory is an empty placeholder for future features — there are no runnable test generators or complexity analyzers.
- Roadmap items like interactive visualizations, cross-session progress tracking, and spaced repetition are not yet implemented.
- Quality depends entirely on Claude's reasoning; the repo provides no evaluation benchmarks or test suite validating teaching outcomes.
- Installing only SKILL.md (quick setup) drops the mode detail, weakening the intended experience.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Algo Sensei — DSA Mentor this page | 58 · Recommended | ★ 287 | 23d ago | MIT |
| CodeRabbit Code Review | 57 · Use with care | ★ 193 | 10d ago | MIT |
| Move Code Quality Checker | 54 · Use with care | ★ 23 | 1y ago | MIT |
| CodeRabbit Review Skill | 53 · Use with care | ★ 35 | 2mo ago | Unlicense |
| Review Agent Code Review Skill ✓ OpenAI · Official | 52 · Use with care | ★ 129k | 11d ago | Apache-2.0 |
The README itself compares it against LeetCode Premium (paid, hands you solutions), generic ChatGPT/Claude prompts (unstructured), and YouTube tutorials (non-interactive): this skill is free, DSA-specialized, and offers structured progressive learning with consistent methodology. The author notes they serve different purposes and suggests using both it and LeetCode Premium.
How did FollowSkills review this skill?
Pure prompt skill: no code execution, no external calls, no sensitive-data access; least privilege is inherently satisfied; ethics section explicitly discourages handing out solutions. Deducted because the publisher is unverified and the referenced modes/ files were not shown within the assessed scope, so absence of overreach downstream cannot be confirmed.
SKILL.md is internally consistent with clear mode-detection rules and few failure paths (conversational skill). But it depends on modes/*.md, templates and docs; without them functionality degrades (README admits SKILL.md-only setup lacks detailed mode instructions). No tests, no error-handling guidance; static review caps this at 10.
Audience (LeetCode/DSA learners) and per-mode trigger conditions are explicit, giving good semantic trigger precision; multi-language code support is declared. Deducted for missing non-fit boundaries, English-only documentation with no Chinese support, and full dependence on Claude Code/Claude.ai whose reachability from mainland China is uncertain.
Well-layered docs (README/SKILL/modes/templates), MIT license, contributing guide, FAQ, roadmap, and disclosed limitations (reduced quick-setup). Deducted for no versioning or changelog, vague maintenance/update ownership (generic GitHub links), and an empty placeholder scripts directory.
Core value proposition (progressive hints, Socratic teaching, pattern training) is coherent and plausibly beats directly asking for answers; output is conversational and directly usable. Deducted because no execution evidence exists: the claimed 'intelligent mode detection' and '5-level hints' are unverified, and comparative claims (vs LeetCode Premium) are marketing statements.
Only internally consistent first-party documentation and install instructions are auditable; no test suite, no CI covering key paths, no third-party validation or demos. Static cap of 5, scored down to 3.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →