leetcode-coach
- Repo stars 2,010
- Author updated Live
- Author repo tinyfish-cookbook
- Domain
- Engineering
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @tinyfish-io · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Required · Vendor-specific
- Operating systems
- macOS · Linux · Windows
- Runtime requirements
- Python
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- External requests
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: leetcode-coach
description: Find and set up coding practice problems tailored to your weak areas, then create local files so…
category: engineering
runtime: Python
---
# leetcode-coach output preview
## PART A: Task fit
- Use case: Find and set up coding practice problems tailored to your weak areas, then create local files so you can solve them right away. Use this skill when a user wants to practice coding, asks for a LeetCode problem, says "give me a coding challenge", "I want to practice DSA", "help me prep for coding interviews", "find me a problem to solve", "I'm weak at dynamic programming", "quiz me on algorithms", or any request to practice coding with a specific language or topic focus..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Pre-flight Check (REQUIRED) / Step 1 — Gather inputs / Step 2 — Find matching problems” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Find and set up coding practice problems tailored to your weak areas, then create local files so you can solve them right away. Use this skill when a user wants to practice coding, asks for a LeetCode problem, says "give me a coding challenge", "I want to practice DSA", "help me prep for coding interviews", "find me a problem to solve", "I'm weak at dynamic programming", "quiz me on algorithms", or any request to practice coding with a specific language or topic focus.”.
- **02** When the source has headings, the agent prioritizes “Pre-flight Check (REQUIRED) / Step 1 — Gather inputs / Step 2 — Find matching problems” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; may access external network resources; requires Vendor-specific API keys.
## Running Rules
- read files, write/modify files; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/tmp`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Pre-flight Check (REQUIRED) / Step 1 — Gather inputs / Step 2 — Find matching problems”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: leetcode-coach
description: Find and set up coding practice problems tailored to your weak areas, then create local files so…
category: engineering
source: tinyfish-io/tinyfish-cookbook
---
# leetcode-coach
## When to use
- Find and set up coding practice problems tailored to your weak areas, then create local files so you can solve them ri…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Pre-flight Check (REQUIRED) / Step 1 — Gather inputs / Step 2 — Find matching problems” and keep inference separate from source facts.
- read files, write/modify files; may access external network resources; requires Vendor-specific API keys.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "leetcode-coach" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Pre-flight Check (REQUIRED) / Step 1 — Gather inputs / Step 2 — Find matching problems
rules -> SKILL.md triggers / order / output contract
runtime -> Python | read files, write/modify files | may access external network resources
guardrails -> requires Vendor-specific API keys + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} LeetCode Coach
Find coding problems matched to your weak areas from LeetCode, HackerRank, and Codeforces — then set up local files so you can start solving immediately.
Pre-flight Check (REQUIRED)
Before making any TinyFish call, always run BOTH checks:
1. CLI installed?
which tinyfish && tinyfish --version || echo "TINYFISH_CLI_NOT_INSTALLED"
If not installed, stop and tell the user:
Install the TinyFish CLI:
npm install -g @tiny-fish/cli
2. Authenticated?
tinyfish auth status
If not authenticated, stop and tell the user:
You need a TinyFish API key. Get one at: https://agent.tinyfish.ai/api-keys
Then authenticate:
tinyfish auth login
Do NOT proceed until both checks pass.
Step 1 — Gather inputs
Ask for the following if not already provided:
Required:
- Preferred language — e.g. Python, JavaScript, Java, C++, Go, Rust
Optional (but improves results):
- Weak areas / topics to focus on — e.g. "dynamic programming", "graphs", "sliding window", "binary search", "recursion", "trees"
- Difficulty — Easy / Medium / Hard (default: Medium)
If the user isn't sure of their weak areas, ask:
"What topics do you find yourself getting stuck on, or want to get better at?"
If they still aren't sure, default to: Arrays, Strings, and Hash Maps (the most commonly tested fundamentals).
Step 2 — Find matching problems
Fire parallel TinyFish agents across LeetCode, HackerRank, and Codeforces to find real problems matching the topic and difficulty.
# Agent 1 — LeetCode problem search
tinyfish agent run \
--url "https://leetcode.com/problemset/?difficulty={DIFFICULTY}&topicSlugs={TOPIC_SLUG}" \
"You are on the LeetCode problem set page filtered by difficulty and topic.
Find 3 problems that match the topic: {TOPIC}.
For each problem extract:
- title
- difficulty (Easy/Medium/Hard)
- acceptance rate
- topic tags
- direct URL to the problem (e.g. https://leetcode.com/problems/two-sum/)
STRICT RULES:
- Do NOT click any problem to open it
- Read only the problem listing visible on this page
- Return exactly 3 problems, no more
- Skip premium-only problems (marked with a lock icon)
Return JSON array: [{title, difficulty, acceptance_rate, tags, url}]" \
--sync > /tmp/lc_leetcode.json &
# Agent 2 — HackerRank problem search
tinyfish agent run \
--url "https://www.hackerrank.com/domains/algorithms?filters%5Bsubdomains%5D%5B%5D={TOPIC_SLUG}" \
"You are on HackerRank's algorithms problem listing filtered by topic.
Find 2 problems that match the topic: {TOPIC} at {DIFFICULTY} level.
For each problem extract:
- title
- difficulty
- score/points
- topic tags
- direct URL to the problem
STRICT RULES:
- Do NOT click any problem
- Read only the visible listing
- Return up to 2 problems
- Skip problems requiring premium or contests
Return JSON array: [{title, difficulty, score, tags, url}]" \
--sync > /tmp/lc_hackerrank.json &
# Agent 3 — Codeforces problem search
tinyfish agent run \
--url "https://codeforces.com/problemset?tags={TOPIC_SLUG}" \
"You are on Codeforces problem set filtered by tag.
Find 2 problems matching the topic: {TOPIC} at approximately {DIFFICULTY} level
(Easy ≈ rating 800-1200, Medium ≈ 1300-1800, Hard ≈ 1900+).
For each problem extract:
- problem ID (e.g. 1A, 158B)
- title
- rating
- tags
- direct URL (e.g. https://codeforces.com/problemset/problem/1/A)
STRICT RULES:
- Do NOT click any problem
- Read only the visible listing
- Return up to 2 problems
Return JSON array: [{id, title, rating, tags, url}]" \
--sync > /tmp/lc_codeforces.json &
wait
echo "=== LEETCODE ===" && cat /tmp/lc_leetcode.json
echo "=== HACKERRANK ===" && cat /tmp/lc_hackerrank.json
echo "=== CODEFORCES ===" && cat /tmp/lc_codeforces.json
Before running, replace:
{DIFFICULTY}— Easy / Medium / Hard{TOPIC}— human-readable topic e.g.dynamic programming{TOPIC_SLUG}— URL-friendly e.g.dynamic-programming
Step 3 — Present problem options
From the results, pick the 3 best problems across all sources. Prefer:
- LeetCode problems (widest community support, best editorial availability)
- Problems with clear descriptions visible from the listing
- Problems with acceptance rates between 30-60% for Medium difficulty
Present them like this:
Here are 3 problems matched to your focus on **{TOPIC}** in **{LANGUAGE}**:
**Option 1 — {Title}** ({difficulty}) · {source}
Tags: {tags}
Acceptance: {rate}
🔗 {url}
**Option 2 — {Title}** ({difficulty}) · {source}
Tags: {tags}
🔗 {url}
**Option 3 — {Title}** ({difficulty}) · {source}
Tags: {tags}
🔗 {url}
Which one do you want to tackle? (1, 2, or 3)
Wait for the user to choose a problem before proceeding.
Step 3b — Ask how they want to solve it
Once the user picks a problem, ask:
How do you want to solve it?
1. **On the website** — I'll give you the direct link and you solve it in the browser
2. **Locally** — I'll fetch the full problem and set up files on your machine so you can code in your editor
(1 or 2)
If they choose option 1 (website): Give them the direct link to the problem and wish them luck:
Here you go: {problem_url}
Good luck! Come back and paste your solution when you're done — I'll review it.
Stop here. Do not create any files.
If they choose option 2 (locally): Continue to Step 4.
Step 4 — Fetch the full problem
Once the user picks, fetch the full problem description using TinyFish.
tinyfish agent run \
--url "{CHOSEN_PROBLEM_URL}" \
"You are on a coding problem page. Extract the complete problem details.
Extract:
- title
- difficulty
- full problem description (exactly as written — do not paraphrase)
- constraints (exact list)
- all example inputs and outputs with explanations
- topic tags
- any follow-up questions mentioned
STRICT RULES:
- Do NOT click any links
- Extract the complete description verbatim — do not shorten it
- If examples have visual diagrams described in text, include them
Return JSON: {title, difficulty, description, constraints: [], examples: [{input, output, explanation}], tags: [], followup}" \
--sync
Step 5 — Create local files
Once you have the full problem, create these three files in the current working directory:
problem.md
# {Problem Title}
**Source:** {url}
**Difficulty:** {difficulty}
**Tags:** {tags}
**Language:** {language}
---
## Problem
{full problem description}
## Constraints
{constraints as bullet list}
## Examples
### Example 1
**Input:** {input}
**Output:** {output}
**Explanation:** {explanation}
### Example 2
...
---
## Notes
<!-- Add your approach notes here before coding -->
solution.{ext}
Create a starter file with the correct extension for the chosen language and a function signature scaffold. Use the appropriate extension:
| Language | Extension | Starter |
|---|---|---|
| Python | .py |
def solution(): with docstring |
| JavaScript | .js |
function solution() {} with JSDoc |
| TypeScript | .ts |
typed function signature |
| Java | .java |
class + method scaffold |
| C++ | .cpp |
#include + function |
| Go | .go |
package + func |
| Rust | .rs |
fn solution() |
Include a comment at the top:
// Problem: {title}
// Source: {url}
// Difficulty: {difficulty}
// Your approach: (fill this in before coding)
Infer the function signature from the problem description if possible (e.g. if the problem says "given an array of integers, return..."). If unclear, use a generic starter.
test_cases.md
# Test Cases — {Problem Title}
## From the problem
| # | Input | Expected Output |
|---|-------|----------------|
| 1 | {input} | {output} |
| 2 | {input} | {output} |
## Edge cases to consider
<!-- Think about: empty input, single element, negative numbers, duplicates, max constraints -->
- [ ] Empty input
- [ ] Single element
- [ ] Already sorted / already valid
- [ ] Maximum constraint size
Step 6 — Brief the user
Once the files are created, tell the user:
Files created:
- problem.md ← full problem description
- solution.{ext} ← starter template in {language}
- test_cases.md ← sample test cases + edge case checklist
Take your time and solve it. When you're done, paste your solution here and I'll review it — checking for correctness, edge cases, time complexity, and style.
Good luck!
Edge Cases
- LeetCode returns no results for topic — fall back to searching
https://leetcode.com/problemset/?search={TOPIC}without the filter - Problem URL is premium-only — skip it and pick the next best option from the results
- User doesn't know their weak areas — default to Arrays + Hash Maps (Medium), which covers the widest range of interview fundamentals
- User wants a specific problem by name — skip Steps 2-3, go straight to fetching and creating files for that problem
- Codeforces returns nothing — skip it silently, present options from LeetCode and HackerRank only
- User is a complete beginner — suggest Easy difficulty and start with Two Sum (LeetCode #1) as a warm-up before moving to their topic of interest
Decide Fit First
Design Intent
How To Use It
Boundaries And Review