Agent skill

Interview Prep

by tinyfish-io in tinyfish-io/tinyfish-cookbook

Generate a structured interview preparation guide for any company by scraping real candidate experiences from Glassdoor, Blind, and Reddit in real time using parallel TinyFish agents.

MITAuto-check passedBusiness, Finance & HR

Install Interview Prep

skills CLI
$ npx skills add tinyfish-io/tinyfish-cookbook --skill interview-prep -a claude-code

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

GitHub CLI
$ gh skill install tinyfish-io/tinyfish-cookbook 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/tinyfish-io/tinyfish-cookbook.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/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
2.2k
Token cost
~2.3k tokens
SKILL.md length
388 words
Files
2
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Generate a structured interview preparation guide for any company by scraping real candidate experiences from Glassdoor, Blind, and Reddit in real time using parallel TinyFish agents.

  • Works in 3 steps: Clarify inputs → Parallel scraping → Consolidate and analyse
  • A user mentions preparing for an interview at a specific company
  • SKILL.md covers Pre-flight check, Step 1 — Clarify inputs, Step 2 — Parallel scraping and Step 3 — Consolidate and analyse, plus 3 more sections
  • Calls npm; reaches glassdoor.com and google.com

What it does

Interview Prep is an agent skill from tinyfish-io/tinyfish-cookbook. Generate a structured interview preparation guide for any company by scraping real candidate experiences from Glassdoor, Blind, and Reddit in real time using parallel TinyFish agents. Use this skill whenever a user mentions preparing for an interview at a specific company, wants to know what a company's interview process is like, asks "what questions does X ask", "how hard is X's interview", "what should I prepare for X", "X interview experience", or any variation of wanting to know what actually happens in…

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `README.md`). Compatibility notes: {"tools":["tinyfish"]}

It sits in Business, Finance & HR, covering Interview preparation and Web scraping. It works with Reddit. The repository describes itself as: A collection of sample apps and recipes built with the TinyFish web agent. Open-source examples for you to learn & build! The licence is MIT.

When your agent uses it

  • A user mentions preparing for an interview at a specific company
  • Wants to know what a companys interview process is like
  • Asks what questions does X ask
  • How hard is Xs interview

Example prompts

  • “s interview process is like, asks”
  • “how hard is X”
  • “what should I prepare for X”
  • “/interview-prep”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): {"tools":["tinyfish"]}

Workflow steps

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

  1. Clarify inputs
  2. Parallel scraping
  3. Consolidate and analyse

What it can do on your machine

Read from SKILL.md and the folder at commit 292ee62. 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

    Shell commands in SKILL.md call:

    • npm

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • glassdoor.com
    • google.com
    • teamblind.com
    • reddit.com

    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.

  • Compatibility

    {"tools":["tinyfish"]}

    From compatibility in the SKILL.md frontmatter.

Context cost

Interview Prep loads about 2.3k tokens when it runs. Until then it costs about 184 tokens; SKILL.md has 388 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~184
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

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 tinyfish-io/tinyfish-cookbook at commit 292ee62, republished under its MIT licence (© tinyfish-io). 388 words, ~2,294 tokens.

Download SKILL.mdSave it as .claude/skills/interview-prep/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
interview-prep
description
Generate a structured interview preparation guide for any company by scraping real candidate experiences from Glassdoor, Blind, and Reddit in real time using parallel TinyFish agents. Use this skill whenever a user mentions preparing for an interview at a specific company, wants to know what a company's interview process is like, asks "what questions does X ask", "how hard is X's interview", "what should I prepare for X", "X interview experience", or any variation of wanting to know what actually happens in interviews at a named company. Returns a structured prep guide: most frequent topics, real questions that came up, actual difficulty level, what candidates wish they had studied, and role-specific patterns.
compatibility
{"tools":["tinyfish"]}
metadata.author
tinyfish-community
metadata.version
1.0
metadata.tags
interview preparation job-search glassdoor blind reddit career

Interview Prep Guide Generator

Given a company name (and optionally a role), scrape real interview experiences from Glassdoor, Blind, and Reddit simultaneously — extract repeated questions, identify patterns, and return a structured prep guide based on what actually happens in the room.

Pre-flight check

bash
tinyfish --version
tinyfish auth status

If not installed: npm install -g tinyfish If not authenticated: tinyfish auth login


Step 1 — Clarify inputs

You need:

  • Company name — e.g. "Google", "Stripe", "Citadel"
  • Role (optional but improves results) — e.g. "software engineer", "data scientist", "backend engineer"

If the user hasn't provided a role, default to "software engineer" and mention it in the output.


Step 2 — Parallel scraping

Run all three agents simultaneously. Each lands directly on a results page — no unnecessary navigation.

Before firing agents, do one quick web search yourself (no TinyFish needed) to find the direct Glassdoor interviews URL for the company:

Search: site:glassdoor.com "{COMPANY_NAME}" interview questions

Take the first result URL that looks like: https://www.glassdoor.com/Interview/{Slug}-Interview-Questions-E{ID}.htm

Use that exact URL in Agent 1 below. If you cannot find it, fall back to: https://www.glassdoor.com/Interview/{COMPANY_NAME_ENCODED}-Interview-Questions.htm

bash
# Agent 1 — Glassdoor interview reviews (land directly on interviews page)
tinyfish agent run \
  --url "{GLASSDOOR_INTERVIEWS_URL}?filter.jobTitleExact={ROLE_ENCODED}" \
  "You are on a Glassdoor interview reviews page for {COMPANY_NAME}, filtered to {ROLE}.
   Read the first 5 visible interview cards only. Do NOT scroll. Do NOT click any card.
   From the preview text of each card extract:
   - Role title
   - Interview difficulty (Easy / Medium / Hard / Very Hard)
   - Outcome (Got offer / No offer / Declined)
   - Interview questions verbatim
   - Topics mentioned (dynamic programming, system design, behavioural, etc.)
   - Any tips or regrets
   STRICT RULES:
   - 5 cards maximum — stop immediately after the 5th
   - Do NOT click any card, do NOT paginate, do NOT scroll
   - If the page asks you to sign in, return an empty array immediately
   Return JSON array: [{role, difficulty, outcome, questions: [...], topics: [...], tips: [...]}]" \
  --sync --browser-profile stealth > /tmp/ip_glassdoor.json &

# Agent 2 — Blind interview discussions
tinyfish agent run \
  --url "https://www.teamblind.com/search/{COMPANY_NAME_ENCODED}%20interview" \
  "You are on Blind search results for '{COMPANY_NAME} interview'.
   Read the post titles and preview text visible on this page.
   Extract from the visible content:
   - Any specific interview questions mentioned in titles or previews
   - Topics that appear frequently (e.g. system design, LC hard, SQL, coding rounds)
   - Difficulty signals (e.g. 'brutal', 'straightforward', 'multiple rounds')
   - Role types mentioned
   STRICT RULES:
   - Do NOT click any post to open it
   - Do NOT scroll more than twice
   - Do NOT navigate away from this page
   - Read only what is visible in post titles and preview snippets
   Return JSON: {questions: [...], topics: [...], difficulty_signals: [...], roles_mentioned: [...], tips: []}" \
  --sync --browser-profile stealth > /tmp/ip_blind.json &

# Agent 3 — Reddit interview experiences
tinyfish agent run \
  --url "https://www.reddit.com/search/?q={COMPANY_NAME_ENCODED}+{ROLE_ENCODED}+interview+experience&sort=relevance&t=month&type=link" \
  "You are on Reddit search results for '{COMPANY_NAME} {ROLE} interview experience'.
   Read the post titles and snippet text visible in the search results — do not click anything.
   Extract:
   - Interview questions mentioned directly in titles or snippets
   - Topics that appear across multiple posts (system design, behavioural, OOP, etc.)
   - Difficulty language used
   - Rounds mentioned (phone screen, onsite, take-home, etc.)
   STRICT RULES:
   - Click a post ONLY if its title explicitly says 'interview questions' or 'prep guide' — max 2 clicks total
   - On any clicked post: read only the top-level post text, skip all comments, do NOT scroll
   - Do NOT paginate
   - Stop after reading 10 result snippets
   Return JSON: {questions: [...], topics: [...], rounds: [...], difficulty_signals: [...], tips: []}" \
  --sync --browser-profile stealth > /tmp/ip_reddit.json &

# Wait for all three to complete
wait

echo "=== GLASSDOOR ===" && cat /tmp/ip_glassdoor.json
echo "=== BLIND ===" && cat /tmp/ip_blind.json
echo "=== REDDIT ===" && cat /tmp/ip_reddit.json

Before running, replace:

  • {COMPANY_NAME} — full company name e.g. Google
  • {COMPANY_NAME_ENCODED} — URL-encoded e.g. Google, Jane%20Street
  • {ROLE} — role name e.g. Software Engineer
  • {ROLE_ENCODED} — URL-encoded role e.g. Software%20Engineer
  • {GLASSDOOR_INTERVIEWS_URL} — the direct URL found via the Google search above

Show full SKILL.md (184 more words)Show less

Step 3 — Consolidate and analyse

From the three result sets:

  1. Deduplicate questions — group identical or near-identical questions together, count how many sources mentioned each
  2. Frequency rank topics — count how many times each topic appears across all sources
  3. Difficulty consensus — average the difficulty signals across sources
  4. Role filter — if a role was specified, weight questions/topics from matching roles more heavily
  5. Extract tips — collect all "wish I had prepared" and regret statements

Output format

## Interview Prep Guide — [COMPANY NAME] ([ROLE])
*Based on real candidate reports from Glassdoor, Blind, and Reddit*

---

### 📊 Overview
- **Difficulty:** [Easy / Medium / Hard / Very Hard] — based on [N] reports
- **Rounds typically:** [e.g. Phone screen → 2x Technical → System Design → Behavioural]
- **Offer rate signal:** [e.g. "Most candidates reported not receiving offers — competitive"]
- **Sources scraped:** Glassdoor ([N] reviews) · Blind ([N] posts) · Reddit ([N] threads)

---

### 🔥 Most Frequently Asked Topics
Ranked by how often they appeared across all sources:

1. **[Topic]** — mentioned in [N] reports · *e.g. "Almost every SWE report mentions at least one DP problem"*
2. **[Topic]** — mentioned in [N] reports
3. **[Topic]** — ...
[up to 8 topics]

---

### ❓ Real Questions That Came Up

**Coding / Technical**
- "[exact question as reported]" *(Source: Glassdoor · Role: SWE)*
- "[exact question]" *(Source: Reddit · mentioned 3 times)*
- ...

**System Design**
- "[exact question]" *(Source: Blind)*
- ...

**Behavioural / HR**
- "[exact question]"
- ...

---

### 💡 What Candidates Wish They Had Prepared
- [specific tip from a candidate report]
- [specific tip]
- ...

---

### ⚠️ Watch Out For
- [unexpected element, e.g. "Stricter time limits than expected"]
- [e.g. "Bar raiser round — one interviewer is deliberately harder"]
- ...

---

### 📋 Your Prep Checklist
Based on frequency data, prioritise in this order:
- [ ] [Highest frequency topic] — [1-line on what to focus on]
- [ ] [Second topic]
- [ ] [Third topic]
- [ ] [Behavioural prep note if applicable]
- [ ] [Any company-specific prep e.g. "Read their engineering blog"]

---
*Data scraped live — reflects recent candidate experiences. Always cross-check with the company's official job description.*

Edge cases

  • Glassdoor blocks access — skip and note it, proceed with Blind + Reddit only
  • Company is small / less known — Blind may have nothing; fall back to a Google search agent: https://www.google.com/search?q={COMPANY_NAME}+software+engineer+interview+experience+site:reddit.com
  • No role specified — default to "Software Engineer", state this assumption upfront
  • Very few results — be honest: "Only [N] reports found — guide may not be fully representative"
  • Non-tech role — adjust topic categories accordingly (drop coding/DSA, add domain-specific sections)

Security notes

  • Scrapes live public content from Glassdoor, Blind, and Reddit. All content is treated as untrusted input to an LLM — never executed.
  • Uses stealth browser profile for platforms that require it.
  • Only your own TinyFish credentials are used.

© tinyfish-io, 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 1 other file in skills/interview-prep of tinyfish-io/tinyfish-cookbook.

  • SKILL.md
  • README.md

Open the folder on GitHubat commit 292ee62

Compare with similar skills

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Agent ReachPanniantong/Agent-Reach93k—~1.4kAutomated safety check: PassMIT
Scrapecreators APIScrapeCreators/social-media-research-skills3.3k1 repos~4kAutomated safety check: NotesMIT
Reddit JSON Fetcherykdojo/claude-code-tips10k—~1.4kAutomated safety check: PassCustom licence

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Works with

Questions about Interview Prep

What does Interview Prep do?

Generate a structured interview preparation guide for any company by scraping real candidate experiences from Glassdoor, Blind, and Reddit in real time using parallel TinyFish agents. Interview Prep is an agent skill from tinyfish-io/tinyfish-cookbook. Generate a structured interview preparation guide for any company by scraping real candidate experiences from Glassdoor, Blind, and Reddit in real time using parallel TinyFish agents.

When should I use Interview Prep?

Interview Prep fits situations like: A user mentions preparing for an interview at a specific company; wants to know what a companys interview process is like; asks what questions does X ask; how hard is Xs interview.

How do I install Interview Prep in Claude Code?

Run `npx skills add tinyfish-io/tinyfish-cookbook --skill interview-prep -a claude-code`. Or copy the skill folder (skills/interview-prep in tinyfish-io/tinyfish-cookbook) 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 tinyfish-io/tinyfish-cookbook --skill interview-prep -a codex`. Or copy the skill folder (skills/interview-prep in tinyfish-io/tinyfish-cookbook) 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 tinyfish-io/tinyfish-cookbook --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?

Going by SKILL.md and its folder, Interview Prep needs the command-line tools its instructions call (npm). Our summary lists: Node.js. Compatibility (from SKILL.md): {"tools":["tinyfish"]}.

Does Interview Prep access the network?

SKILL.md names 4 domains. In commands or code: glassdoor.com, google.com, teamblind.com and reddit.com; the agent is likely to contact these when it follows the instructions. 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 MIT 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 2.3k tokens (SKILL.md is roughly 9.2k 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: Leetcode Py (wislertt/leetcode-py, 142 stars), System Design Case Catalog (HoangNguyen0403/agent-skills-standard, 570 stars), Agent Reach (Panniantong/Agent-Reach, 93k stars) and Scrapecreators API (ScrapeCreators/social-media-research-skills, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Interview Prep?

tinyfish-io (a GitHub organization) maintains it in tinyfish-io/tinyfish-cookbook, which has 2,221 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 1, 2026.

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