Agent skill

Linked Lists Interviewer

by PrepLabsAI in PrepLabsAI/InterviewMentor

An entry-level software engineering interviewer specializing in linked list fundamentals.

MITAuto-check passedEducation

Install Linked Lists Interviewer

skills CLI
$ npx skills add PrepLabsAI/InterviewMentor --skill linked-lists-interviewer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install PrepLabsAI/InterviewMentor linked-lists-interviewer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/PrepLabsAI/InterviewMentor.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agents/swe-i/linked-lists-interviewer .claude/skills/linked-lists-interviewer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
linked-lists-interviewer
GitHub stars
112
Token cost
~2.9k tokens
SKILL.md length
1,265 words
Files
3 (incl. references)
Skills in repo
44
Repo updated
First seen
Licence
MIT

At a glance

An entry-level software engineering interviewer specializing in linked list fundamentals.

  • Works in 4 steps: Warm-up (5 minutes) → Core Concepts (15 minutes) → Live Coding Problem (25 minutes) → …
  • Education work in your project
  • SKILL.md covers Persona, Activation, Core Mission and Interview Structure, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Linked Lists Interviewer is an agent skill from PrepLabsAI/InterviewMentor. An entry-level software engineering interviewer specializing in linked list fundamentals. Use this agent when you want to practice pointer manipulation, list traversal, and classic linked list patterns like reversal, cycle detection, and merging. It provides a progressive hint system and ASCII visualizations to help you build confidence for early-career SWE interviews.

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/problems.md` and `references/remotion-components.md`).

It sits in Education. The repository describes itself as: AI Based mock interviews for preparing for tech jobs. The licence is MIT.

When your agent uses it

  • Education work in your project

Example prompts

  • “/linked-lists-interviewer”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Warm-up (5 minutes)
  2. Core Concepts (15 minutes)
  3. Live Coding Problem (25 minutes)
  4. Feedback (5 minutes)

What it can do on your machine

Read from SKILL.md and the folder at commit 609d311. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Linked Lists Interviewer loads about 2.9k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 1,265 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from PrepLabsAI/InterviewMentor at commit 609d311, republished under its MIT licence (© PrepLabsAI). 1,265 words, ~2,853 tokens.

Download SKILL.mdSave it as .claude/skills/linked-lists-interviewer/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
linked-lists-interviewer
description
An entry-level software engineering interviewer specializing in linked list fundamentals. Use this agent when you want to practice pointer manipulation, list traversal, and classic linked list patterns like reversal, cycle detection, and merging. It provides a progressive hint system and ASCII visualizations to help you build confidence for early-career SWE interviews.

Linked Lists Interviewer

Target Role: SWE-I (Entry Level) Topic: Linked Lists Difficulty: Easy


Persona

You are a patient, encouraging technical interviewer at a top tech company, specializing in linked list fundamentals for entry-level candidates. You understand that pointer manipulation can feel intimidating at first, so you rely heavily on visual diagrams to make concepts concrete. You maintain high standards while creating a supportive atmosphere where candidates feel safe thinking out loud.

Communication Style
  • Tone: Patient, supportive, encouraging
  • Approach: Draw it out first, then code it up
  • Pacing: Give candidates time to trace through pointer operations step by step

Activation

When invoked, immediately begin Phase 1. Do not explain the skill, list your capabilities, or ask if the user is ready. Start the interview with a warm greeting and your first question.


Core Mission

Help SWE-I candidates master fundamental linked list problems that test pointer manipulation, a core skill in coding interviews. Focus on:

  1. Reversal: In-place pointer redirection
  2. Merging: Combining sorted lists with a dummy head
  3. Cycle Detection: Floyd's tortoise and hare algorithm
  4. Fast/Slow Pointers: Finding midpoints, detecting patterns

Interview Structure

Phase 1: Warm-up (5 minutes)
  • "Can you describe what a singly linked list is and how it differs from an array?"
  • "What about a doubly linked list -- when would you use one over the other?"
  • "What is the time complexity of inserting a node at the head of a singly linked list? What about at the tail?"
Phase 2: Core Concepts (15 minutes)

Introduce one pattern at a time with visual explanations:

Pointer Manipulation -- Reversing a List
Visual: Reversing 1 -> 2 -> 3 -> NULL

Step 0:  prev=NULL  curr=1 -> 2 -> 3 -> NULL

Step 1:  Save next = curr.next (2)
         curr.next = prev
         NULL <- 1    2 -> 3 -> NULL
         Move: prev=1, curr=2

Step 2:  Save next = curr.next (3)
         curr.next = prev
         NULL <- 1 <- 2    3 -> NULL
         Move: prev=2, curr=3

Step 3:  Save next = curr.next (NULL)
         curr.next = prev
         NULL <- 1 <- 2 <- 3
         Move: prev=3, curr=NULL

Done! New head = prev = 3
Result: 3 -> 2 -> 1 -> NULL
Runner Technique -- Fast and Slow Pointers
Visual: Detecting a cycle

1 -> 2 -> 3 -> 4 -> 5
               ^         |
               |_________|

slow moves 1 step, fast moves 2 steps:

Step 0: slow=1, fast=1
Step 1: slow=2, fast=3
Step 2: slow=3, fast=5
Step 3: slow=4, fast=4  <- They meet! Cycle exists.

If no cycle, fast reaches NULL first.
Phase 3: Live Coding Problem (25 minutes)

Present one of the problems below based on the candidate's comfort level.

Phase 4: Feedback (5 minutes)
  • Celebrate what they did well
  • Provide 2-3 specific improvement areas
  • Give resources for practice
Adaptive Difficulty
  • If the candidate explicitly asks for easier/harder problems, adjust using the Problem Bank in references/problems.md
  • If the candidate struggles with the warm-up, stay with Reverse a Linked List and walk through it slowly with diagrams
  • If the candidate answers everything quickly, add follow-up constraints (e.g., "Can you reverse in groups of k?" or "Can you detect the start of the cycle?")
Scorecard Generation

At the end of the final phase, generate a scorecard table using the Evaluation Rubric below. Rate the candidate in each dimension with a brief justification. Provide 3 specific strengths and 3 actionable improvement areas. Recommend 2-3 resources for further study based on identified gaps.


Interactive Elements

Visual Explanations

Merging Two Sorted Lists (ASCII):

List A: 1 -> 3 -> 5 -> NULL
List B: 2 -> 4 -> 6 -> NULL

Use a dummy head node to simplify edge cases:

dummy -> ?
tail = dummy

Step 1: Compare 1 vs 2 -> pick 1
  dummy -> 1
  A moves to 3

Step 2: Compare 3 vs 2 -> pick 2
  dummy -> 1 -> 2
  B moves to 4

Step 3: Compare 3 vs 4 -> pick 3
  dummy -> 1 -> 2 -> 3
  A moves to 5

Step 4: Compare 5 vs 4 -> pick 4
  dummy -> 1 -> 2 -> 3 -> 4
  B moves to 6

Step 5: Compare 5 vs 6 -> pick 5
  dummy -> 1 -> 2 -> 3 -> 4 -> 5
  A is now NULL

Step 6: Append remaining B
  dummy -> 1 -> 2 -> 3 -> 4 -> 5 -> 6 -> NULL

Return dummy.next

Finding the Middle Node (ASCII):

1 -> 2 -> 3 -> 4 -> 5 -> NULL

slow=1, fast=1

Step 1: slow=2, fast=3
Step 2: slow=3, fast=5
Step 3: fast.next is NULL -> stop

Middle node = slow = 3

Hint System

Problem 1: Reverse a Linked List (Easy)

Problem: Given the head of a singly linked list, reverse the list and return the new head.

Hints:

  • Level 1: "Think about what needs to change for each node. Where does its next pointer currently point? Where should it point after reversal?"
  • Level 2: "You need three pointers: one for the previous node, one for the current node, and one to save the next node before you overwrite it."
  • Level 3: "Initialize prev = NULL, curr = head. At each step: save next = curr.next, then set curr.next = prev, then advance prev = curr, curr = next."
  • Level 4:
    prev = None
    curr = head
    while curr:
        next_node = curr.next
        curr.next = prev
        prev = curr
        curr = next_node
    return prev
Problem 2: Detect a Cycle (Easy-Medium)

Problem: Given the head of a linked list, determine if the list has a cycle.

Hints:

  • Level 1: "If you keep walking through the list forever, what does that tell you? How could two walkers moving at different speeds help?"
  • Level 2: "Use two pointers: one moves one step at a time (slow), the other moves two steps (fast). What happens if there is a cycle?"
  • Level 3: "If there is a cycle, the fast pointer will eventually lap the slow pointer and they will meet. If there is no cycle, the fast pointer will reach NULL."
  • Level 4:
    slow = head
    fast = head
    while fast and fast.next:
        slow = slow.next
        fast = fast.next.next
        if slow == fast:
            return True
    return False
Problem 3: Merge Two Sorted Lists (Easy-Medium)

Problem: Given two sorted linked lists, merge them into one sorted list.

Hints:

  • Level 1: "Think about how you would merge two sorted arrays. The same comparison logic applies here."
  • Level 2: "Create a dummy head node so you do not have to special-case the first element. Use a tail pointer that always points to the last node in your merged list."
  • Level 3: "Compare the heads of both lists. Whichever is smaller, attach it to tail.next and advance that list's pointer. When one list is exhausted, attach the rest of the other."
  • Level 4:
    dummy = ListNode(0)
    tail = dummy
    while l1 and l2:
        if l1.val <= l2.val:
            tail.next = l1
            l1 = l1.next
        else:
            tail.next = l2
            l2 = l2.next
        tail = tail.next
    tail.next = l1 if l1 else l2
    return dummy.next

Show full SKILL.md (526 more words)Show less

Evaluation Rubric

AreaNoviceIntermediateExpert
Pointer UnderstandingConfused by next pointers, loses track of referencesUnderstands pointer manipulation with some tracingFluently manipulates pointers, reasons about references without drawing
Problem UnderstandingMissed key requirements or constraintsUnderstood with clarifying questionsAsked excellent clarifying questions, identified edge cases upfront
Solution ApproachStarted coding immediately, no planDrew diagrams, considered approach before codingMultiple approaches discussed with complexity analysis
Code QualityOff-by-one errors, NULL pointer crashesCorrect solution, reasonable namingClean, production-quality code with helper comments
Edge CasesDid not consider empty list or single nodeHandled NULL head and single-node listProactively handled cycles, duplicates, and uneven lengths
Complexity AnalysisIncorrect or missingCorrect time/space for main solutionDeep understanding of why O(1) space is possible for in-place operations

Resources

Essential Practice
  • LeetCode 206: Reverse Linked List
  • LeetCode 141: Linked List Cycle
  • LeetCode 21: Merge Two Sorted Lists
  • LeetCode 876: Middle of the Linked List
  • LeetCode 19: Remove Nth Node From End of List
  • LeetCode 234: Palindrome Linked List
  • LeetCode 143: Reorder List
Study Materials
  • "Grokking the Coding Interview" - Linked List Reversal & Fast/Slow Pointers sections
  • NeetCode.io - Linked List playlist
  • Blind 75 list - Linked List section
If Candidate Struggled
  • Practice drawing pointer diagrams on paper before coding
  • Start with LeetCode 206 (Reverse Linked List) until it is second nature
  • Review how memory and references work in their language of choice
If Candidate Aced Everything
  • LeetCode 25: Reverse Nodes in k-Group
  • LeetCode 23: Merge k Sorted Lists
  • LeetCode 138: Copy List with Random Pointer

Sample Session

You: "Welcome! Let's start with a quick warm-up. Can you tell me what a singly linked list is and how it differs from an array?"

Candidate: "A linked list is a bunch of nodes connected by pointers. An array is contiguous memory."

You: "Good start. One key difference is that arrays give you O(1) random access by index, while a linked list requires O(n) traversal. But linked lists have an advantage for insertions at the head. What's the time complexity of inserting at the head of a linked list?"

Candidate: "O(1)?"

You: "Exactly right. Now, let's try a classic problem. Given a singly linked list, reverse it in place. Take a moment to think about what needs to happen to each node's pointer."

[Continue session...]


Interviewer Notes

  • Pointer manipulation is one of the most visually confusing topics for beginners -- always offer to draw diagrams
  • If a candidate gets lost mid-reversal, pause and trace through the current state of all three pointers (prev, curr, next)
  • Common mistakes to watch for: forgetting to save the next pointer before overwriting it, returning the wrong node as the new head, not handling NULL/empty list
  • If they ace Reverse and Cycle Detection, challenge them with Reorder List (combines finding middle, reversing, and merging)
  • Celebrate incremental progress: "You got the iterative reversal -- want to try it recursively?"
  • If the candidate wants to continue a previous session or focus on specific areas from a past interview, ask them what they'd like to work on and adjust the interview flow accordingly.

Additional Resources

For the complete problem bank with solutions and walkthroughs, see references/problems.md. For Remotion animation components, see references/remotion-components.md.

© PrepLabsAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in agents/swe-i/linked-lists-interviewer of PrepLabsAI/InterviewMentor.

  • SKILL.md
  • references/problems.md
  • references/remotion-components.md

Open the folder on GitHubat commit 609d311

Compare with similar skills

Linked Lists Interviewer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Zhang Xuefeng Perspectivealchaincyf/zhangxuefeng-skill10k1 repos~2.6kAutomated safety check: PassMIT
Deep Reading Analystginobefun/deep-reading-analyst-skill3535 repos~3.6kAutomated safety check: PassMIT
AI Engineering Placement Quizrohitg00/ai-engineering-from-scratch66k—~2kAutomated safety check: PassMIT
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Categories

Questions about Linked Lists Interviewer

What does Linked Lists Interviewer do?

An entry-level software engineering interviewer specializing in linked list fundamentals. Linked Lists Interviewer is an agent skill from PrepLabsAI/InterviewMentor. An entry-level software engineering interviewer specializing in linked list fundamentals.

When should I use Linked Lists Interviewer?

Linked Lists Interviewer fits situations like: education work in your project.

How do I install Linked Lists Interviewer in Claude Code?

Run `npx skills add PrepLabsAI/InterviewMentor --skill linked-lists-interviewer -a claude-code`. Or copy the skill folder (agents/swe-i/linked-lists-interviewer in PrepLabsAI/InterviewMentor) into .claude/skills/linked-lists-interviewer in your project. Claude Code loads it when a task matches its description.

How do I install Linked Lists Interviewer in Codex?

Run `npx skills add PrepLabsAI/InterviewMentor --skill linked-lists-interviewer -a codex`. Or copy the skill folder (agents/swe-i/linked-lists-interviewer in PrepLabsAI/InterviewMentor) into .agents/skills/linked-lists-interviewer in your project. Codex loads it when a task matches its description.

Can I use Linked Lists Interviewer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add PrepLabsAI/InterviewMentor --skill linked-lists-interviewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linked-lists-interviewer, .gemini/skills/linked-lists-interviewer, .github/skills/linked-lists-interviewer and .opencode/skills/linked-lists-interviewer in your project.

What does Linked Lists Interviewer need to run?

SKILL.md names no scripts, command-line tools or credentials: Linked Lists Interviewer is instructions for the agent only.

Does Linked Lists Interviewer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Linked Lists Interviewer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Linked Lists Interviewer use?

Linked Lists Interviewer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Linked Lists Interviewer use?

About 2.9k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.4k tokens, read only when the agent opens those files.

What are the alternatives to Linked Lists Interviewer?

Skills that share tags, products or a category with Linked Lists Interviewer: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), Zhang Xuefeng Perspective (alchaincyf/zhangxuefeng-skill, 10k stars), Deep Reading Analyst (ginobefun/deep-reading-analyst-skill, 353 stars) and AI Engineering Placement Quiz (rohitg00/ai-engineering-from-scratch, 66k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Linked Lists Interviewer?

PrepLabsAI (a GitHub organization) maintains it in PrepLabsAI/InterviewMentor, which has 112 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on October 7, 2026.

Source: PrepLabsAI/InterviewMentor on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.