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Agent skill

Interview Prep

by RightNow-AI in RightNow-AI/openfang

Technical interview preparation expert for algorithms, system design, and behavioral questions

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Interview Prep

skills CLI
$ npx skills add RightNow-AI/openfang --skill interview-prep -a claude-code

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

GitHub CLI
$ gh skill install RightNow-AI/openfang interview-prep --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/RightNow-AI/openfang.git skills-src && mkdir -p .claude/skills && cp -r skills-src/crates/openfang-skills/bundled/interview-prep .claude/skills/interview-prep && 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
interview-prep
GitHub stars
18k
Token cost
~973 tokens
SKILL.md length
480 words
Files
1
Skills in repo
68
Repo updated
First seen
Licence
Apache-2.0

At a glance

Technical interview preparation expert for algorithms, system design, and behavioral questions

  • Tasks that involve Interview preparation
  • SKILL.md covers Key Principles, Techniques, Common Patterns and Pitfalls to Avoid
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Interview Prep is an agent skill from RightNow-AI/openfang. Technical interview preparation expert for algorithms, system design, and behavioral questions

Its SKILL.md is about 970 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Interview preparation. The repository describes itself as: Open-source Agent Operating System. The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Interview preparation

Example prompts

  • “/interview-prep”

What it can do on your machine

Read from SKILL.md and the folder at commit acf2587. 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

Interview Prep loads about 973 tokens when it runs. Until then it costs about 27 tokens; SKILL.md has 480 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~27
When it runs · the whole SKILL.md, loaded when a task matches
~973

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 RightNow-AI/openfang at commit acf2587, republished under its Apache-2.0 licence (© RightNow-AI). 480 words, ~973 tokens.

Download SKILL.mdSave it as .claude/skills/interview-prep/SKILL.md (or your agent's skills folder).
name
interview-prep
description
Technical interview preparation expert for algorithms, system design, and behavioral questions

Technical Interview Preparation Expert

A seasoned engineering hiring manager and interview coach with deep experience across algorithm challenges, system design rounds, and behavioral assessments at top technology companies. This skill provides structured preparation strategies, pattern recognition frameworks, and practice methodologies to help candidates perform confidently and systematically in technical interviews.

Key Principles

  • Master the fundamental patterns rather than memorizing individual problems; most algorithm questions are variations of 10-15 core patterns
  • Communicate your thought process out loud during coding interviews; interviewers evaluate problem-solving approach as much as the final solution
  • Practice system design using a repeatable framework: clarify requirements, estimate scale, design the architecture, then drill into specific components
  • Prepare behavioral stories in advance using the STAR method (Situation, Task, Action, Result) with quantifiable outcomes where possible
  • Time-box your preparation: focus on weak areas identified through practice, not on re-solving problems you already understand

Techniques

  • Study algorithm patterns systematically: two pointers (sorted arrays, palindromes), sliding window (subarrays, substrings), BFS/DFS (graphs, trees), dynamic programming (optimization, counting), binary search (sorted data, search space reduction), and backtracking (permutations, combinations)
  • Analyze time and space complexity for every solution: express Big-O in terms of input size, identify the dominant term, and explain tradeoffs between time and space
  • Follow a system design framework: gather functional and non-functional requirements, perform back-of-envelope estimation (QPS, storage, bandwidth), draw a high-level architecture with components and data flow, then deep-dive into database schema, caching strategy, and scalability patterns
  • Structure coding interviews: restate the problem, clarify edge cases with examples, discuss your approach before coding, implement cleanly, test with examples, then optimize
  • Prepare 6-8 behavioral stories covering leadership, conflict resolution, failure and learning, technical decision-making, collaboration, and delivering under pressure
  • Practice mock interviews with a timer to simulate real pressure; record yourself to identify filler words and unclear explanations
Show full SKILL.md (184 more words)Show less

Common Patterns

  • Sliding Window: Fixed or variable-size window moving across an array or string; used for substring problems, maximum sum subarrays, and finding patterns within contiguous sequences
  • Graph BFS/DFS: Level-order traversal for shortest path in unweighted graphs (BFS) and exhaustive exploration for connectivity and cycle detection (DFS)
  • Dynamic Programming Table: Define subproblems, establish recurrence relation, identify base cases, and fill the table bottom-up; common in string matching, knapsack, and path counting
  • System Design Trade-offs: Consistency vs availability (CAP theorem), latency vs throughput, storage cost vs compute cost; always articulate which trade-off you are making and why

Pitfalls to Avoid

  • Do not jump into coding without first clarifying the problem constraints, expected input size, and edge cases with the interviewer
  • Do not optimize prematurely; start with a correct brute-force solution, verify it works, then improve time or space complexity incrementally
  • Do not give vague behavioral answers; use specific examples with measurable outcomes rather than hypothetical descriptions of what you would do
  • Do not neglect to ask questions at the end of the interview; thoughtful questions about the team, technical challenges, and culture demonstrate genuine interest

© RightNow-AI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in crates/openfang-skills/bundled/interview-prep of RightNow-AI/openfang.

Open the folder on GitHubat commit acf2587

Compare with similar skills

Interview Prep 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.

Interview Prep compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Interview Prep this skillRightNow-AI/openfang18k—~973Automated safety check: PassApache-2.0
Career-Ops Job Search Centercareer-ops-hq/career-ops74k—~3.3kAutomated safety check: PassMIT
Internship Project Preparation ToolLiuMengxuan04/shushu-internship-tool2.1k—~2.3kAutomated safety check: PassCustom licence
Interview Coachnoamseg/interview-coach-skill2.3k—~3.7kAutomated safety check: PassMIT
Job Application AssistantMadsLorentzen/ai-job-search45k—~1.2kAutomated safety check: NotesMIT
Algo Senseikaranb192/algo-sensei284—~1.7kAutomated safety check: PassMIT

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Categories

Questions about Interview Prep

What does Interview Prep do?

Technical interview preparation expert for algorithms, system design, and behavioral questions. Interview Prep is an agent skill from RightNow-AI/openfang.

When should I use Interview Prep?

Interview Prep fits situations like: tasks that involve Interview preparation.

How do I install Interview Prep in Claude Code?

Run `npx skills add RightNow-AI/openfang --skill interview-prep -a claude-code`. Or copy the skill folder (crates/openfang-skills/bundled/interview-prep in RightNow-AI/openfang) into .claude/skills/interview-prep in your project. Claude Code loads it when a task matches its description.

How do I install Interview Prep in Codex?

Run `npx skills add RightNow-AI/openfang --skill interview-prep -a codex`. Or copy the skill folder (crates/openfang-skills/bundled/interview-prep in RightNow-AI/openfang) into .agents/skills/interview-prep in your project. Codex loads it when a task matches its description.

Can I use Interview Prep 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 RightNow-AI/openfang --skill interview-prep -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/interview-prep, .gemini/skills/interview-prep, .github/skills/interview-prep and .opencode/skills/interview-prep in your project.

What does Interview Prep need to run?

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

Does Interview Prep 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 Interview Prep 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 Interview Prep use?

Interview Prep is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Interview Prep use?

About 973 tokens (SKILL.md is roughly 3.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Interview Prep?

Skills that share tags, products or a category with Interview Prep: Career-Ops Job Search Center (career-ops-hq/career-ops, 74k stars), Internship Project Preparation Tool (LiuMengxuan04/shushu-internship-tool, 2.1k stars), Interview Coach (noamseg/interview-coach-skill, 2.3k stars) and Job Application Assistant (MadsLorentzen/ai-job-search, 45k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Interview Prep?

RightNow-AI (a GitHub organization) maintains it in RightNow-AI/openfang, which has 18,212 GitHub stars. The repository holds 68 skills in this directory. The repository was last updated on July 2, 2026.

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