Hackathon Finder logo

Hackathon Finder

OrganizationPopular
tinyfish-io
hackathon-finder

Find hackathons tailored to your tech profile and location by searching Devpost, Luma, Partiful, MLH, and Eventbrite. Use this skill when a user asks "find me a hackathon", "are there any hackathons near me", "what hackathons are coming up", "I want to compete in a hackathon", "find hackathons I could win", "upcoming hackathons in [city]", "online hackathons for [skill/tech]", or any request to discover hackathon opportunities.

Overview

Publishertinyfish-io
Repositorytinyfish-cookbook
Skill namehackathon-finder
Stars
2.2K
Forks
333
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by tinyfish-io on GitHub. Read the source before you install it.

Installation

Install the Hackathon Finder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/tinyfish-io/tinyfish-cookbook.git /tmp/tinyfish-cookbook
mkdir -p .claude/skills
cp -r /tmp/tinyfish-cookbook/skills/hackathon-finder .claude/skills/hackathon-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hackathon Finder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hackathon Finder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hackathon Finder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Hackathon Finder

Build a tech profile from everything known about you, then search Devpost, Luma, Partiful, MLH, and Eventbrite for upcoming hackathons — local or online — that match your stack and give you the best shot at winning.

Pre-flight Check (REQUIRED)

Before making any TinyFish call, always run BOTH checks:

1. CLI installed?

bash
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?

bash
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 — Build the user's tech profile

Before searching for anything, build a picture of who you're helping. Draw from everything available in the current conversation and session context:

  • Languages and frameworks mentioned or used (e.g. React, Python, Rust)
  • Projects described or worked on
  • Areas of interest expressed (e.g. AI/ML, Web3, hardware, design)
  • Skill level signals (beginner, experienced, specialist)
  • Any past hackathon experience mentioned

Summarize this as a brief internal profile:

Tech profile:
- Primary languages: {e.g. Python, TypeScript}
- Frameworks / tools: {e.g. React, FastAPI, LangChain}
- Interest areas: {e.g. AI, developer tools, consumer apps}
- Skill level: {beginner / intermediate / experienced}
- Past hackathons: {yes/no, any wins?}

If very little is known, ask one quick question:

"What do you usually build with? (e.g. languages, frameworks, or areas like AI, web, mobile)"


Step 2 — Ask for location and format preference

Ask the user two things before searching:

Two quick questions:

1. **Where are you based?** (city and country — e.g. "Singapore", "London, UK", "Austin, TX")
   Or if you prefer online-only hackathons, just say "online".

2. **What are you optimizing for?**
   - 🏆 Best chance of winning (match your stack to the theme)
   - 🌍 Biggest / most prestigious (large prize pools, well-known sponsors)
   - 🤝 Best for networking / meeting people
   - 🧪 Most interesting theme (something you'd genuinely enjoy building)

Wait for the user's response before proceeding.


Step 3 — Parallel hackathon search

Fire all agents simultaneously based on the user's location and tech profile.

bash
# Agent 1 — Devpost (largest hackathon aggregator)
tinyfish agent run \
  --url "https://devpost.com/hackathons?challenge_type=online&status=upcoming" \
  "You are on Devpost's upcoming hackathons page.
   Find hackathons relevant to these technologies: {TECH_KEYWORDS}.
   For each relevant hackathon extract:
   - name
   - theme or focus area
   - prize pool (total or top prize)
   - registration deadline
   - hackathon dates
   - online or in-person (and location if in-person)
   - direct URL
   - sponsor companies (if shown)
   STRICT RULES:
   - Do NOT click into any hackathon page
   - Read only what is visible in the listing cards
   - Only include hackathons with future dates
   - Maximum 10 listings then stop
   Return JSON array: [{name, theme, prize_pool, deadline, dates, format, location, url, sponsors: []}]" \
  --sync > /tmp/hf_devpost.json &

# Agent 2 — Devpost (in-person / local, if user specified a city)
tinyfish agent run \
  --url "https://devpost.com/hackathons?challenge_type=in-person&status=upcoming&search={LOCATION_ENCODED}" \
  "You are on Devpost's upcoming in-person hackathons page filtered to {LOCATION}.
   Find hackathons in or near {LOCATION}.
   For each extract:
   - name
   - theme or focus area
   - prize pool
   - registration deadline
   - hackathon dates
   - exact location (city, venue if shown)
   - direct URL
   - sponsor companies
   STRICT RULES:
   - Do NOT click into any hackathon page
   - Maximum 8 listings then stop
   - Only include hackathons with future dates
   Return JSON array: [{name, theme, prize_pool, deadline, dates, location, url, sponsors: []}]" \
  --sync > /tmp/hf_devpost_local.json &

# Agent 3 — MLH (Major League Hacking)
tinyfish agent run \
  --url "https://mlh.io/seasons/2026/events" \
  "You are on the MLH (Major League Hacking) events page for the current season.
   Find upcoming hackathons, especially any in or near {LOCATION} or online.
   For each event extract:
   - name
   - date
   - location (city or online)
   - direct URL
   - any theme or focus if shown
   STRICT RULES:
   - Do NOT click any event
   - Read only the visible event cards
   - Maximum 10 events then stop
   - Only future events
   Return JSON array: [{name, date, location, url, theme}]" \
  --sync > /tmp/hf_mlh.json &

# Agent 4 — Luma
tinyfish agent run \
  --url "https://lu.ma/discover?q=hackathon+{LOCATION_ENCODED}" \
  "You are on Luma event discovery searching for hackathons near {LOCATION}.
   Find upcoming hackathon events.
   For each event extract:
   - name
   - date and time
   - location (in-person address or online)
   - host / organizer
   - short description or theme
   - direct URL
   STRICT RULES:
   - Do NOT click any event
   - Read only what is visible in the event cards
   - Maximum 8 events then stop
   - Only future events
   - If no hackathons found, return {found: false}
   Return JSON array: [{name, date, location, host, description, url}]" \
  --sync > /tmp/hf_luma.json &

# Agent 5 — Devpost tech-specific search
tinyfish agent run \
  --url "https://devpost.com/hackathons?search={TECH_KEYWORD_ENCODED}&status=upcoming" \
  "You are on Devpost searching for hackathons related to {PRIMARY_TECH}.
   Find hackathons that specifically feature {PRIMARY_TECH} as a theme, sponsor, or required technology.
   For each extract:
   - name
   - theme
   - prize pool
   - deadline
   - dates
   - format (online/in-person)
   - direct URL
   - why it's relevant to {PRIMARY_TECH}
   STRICT RULES:
   - Do NOT click into any hackathon
   - Maximum 8 listings then stop
   - Only future hackathons
   Return JSON array: [{name, theme, prize_pool, deadline, dates, format, url, relevance}]" \
  --sync > /tmp/hf_devpost_tech.json &

# Agent 6 — Eventbrite
tinyfish agent run \
  --url "https://www.eventbrite.com/d/{LOCATION_SLUG}/hackathon/" \
  "You are on Eventbrite searching for hackathon events in {LOCATION}.
   Find upcoming hackathon events.
   For each event extract:
   - name
   - date
   - location (venue or online)
   - price / ticket cost (free or paid)
   - organizer
   - short description
   - direct URL
   STRICT RULES:
   - Do NOT click any event
   - Read only what is visible in the event cards
   - Maximum 8 events then stop
   - Only future events
   Return JSON array: [{name, date, location, price, organizer, description, url}]" \
  --sync > /tmp/hf_eventbrite.json &

wait

echo "=== DEVPOST ONLINE ===" && cat /tmp/hf_devpost.json
echo "=== DEVPOST LOCAL ===" && cat /tmp/hf_devpost_local.json
echo "=== MLH ===" && cat /tmp/hf_mlh.json
echo "=== LUMA ===" && cat /tmp/hf_luma.json
echo "=== DEVPOST TECH ===" && cat /tmp/hf_devpost_tech.json
echo "=== EVENTBRITE ===" && cat /tmp/hf_eventbrite.json

Before running, replace:

  • {LOCATION} — e.g. Singapore, London
  • {LOCATION_ENCODED} — URL-encoded e.g. Singapore
  • {LOCATION_SLUG} — Eventbrite format e.g. singapore--sg
  • {TECH_KEYWORDS} — comma-separated e.g. AI, React, Python
  • {TECH_KEYWORD_ENCODED} — primary tech URL-encoded e.g. artificial-intelligence
  • {PRIMARY_TECH} — single best-match technology e.g. AI/ML

Step 4 — Score and rank by fit

For each hackathon found, score it against the user's tech profile and stated goal:

Fit score (0-10):

  • Theme matches user's primary tech area: +4
  • Sponsor uses tech the user knows: +2
  • Prize pool / prestige matches stated goal: +2
  • Location matches preference: +2

Present hackathons ranked by fit score, with the win-probability assessment front and center.


Output format

## Hackathons for You — {LOCATION} · {date}

*Based on your profile: {PRIMARY_LANGUAGES} · {INTEREST_AREAS}*
*Searched: Devpost · MLH · Luma · Eventbrite*

---

### 🏆 Best Matches (Highest Win Potential)

#### {Hackathon Name}
**📅** {dates} · **📍** {location or online}
**💰** Prize: {prize_pool} · **⏰** Register by: {deadline}
**🎯 Why you'd win:** {1-2 sentences on why this fits the user's stack and the theme}
**Sponsors:** {sponsors}
🔗 {url}

---

#### {Hackathon Name}
[same structure]

---

### 🌍 Also Worth Considering

[remaining hackathons, shorter format]

- **{name}** — {date} · {location} · {prize} · {url}

---

### 📊 Summary

| Hackathon | Format | Date | Prize | Fit |
|---|---|---|---|---|
| {name} | Online/Local | {date} | {prize} | ⭐⭐⭐⭐⭐ |

---

### 💡 Strategy Tips
{1-3 targeted tips based on the user's profile and the hackathons found}
- e.g. "The {hackathon} has an AI track with no strong competition in the LLM tooling space — right in your wheelhouse"
- e.g. "For MLH events, solo Python projects with clean demos tend to score well with judges"

Edge Cases

  • User is online-only — skip Devpost local, Luma local, and Eventbrite local agents; focus on Devpost online and MLH
  • No hackathons found in the city — broaden to country, then to online, and note the broadening
  • User has no clear tech profile — skip the fit scoring, present all hackathons by date and let the user choose
  • User has won hackathons before — note this and suggest larger or more competitive events; skip beginner-friendly ones
  • User is a beginner — prioritize beginner-friendly or first-timer hackathons; flag events that explicitly welcome new participants
  • No upcoming hackathons found — suggest checking back closer to major seasons (September-November and January-March tend to be peak hackathon periods)

Frequently asked questions

What does the Hackathon Finder AI skill do?

Find hackathons tailored to your tech profile and location by searching Devpost, Luma, Partiful, MLH, and Eventbrite. Use this skill when a user asks "find me a hackathon", "are there any hackathons near me", "what hackathons are coming up", "I want to compete in a hackathon", "find hackathons I could win", "upcoming hackathons in [city]", "online hackathons for [skill/tech]", or any request to discover hackathon opportunities.

Why use Hackathon Finder on TypingMind?

Because you install it once and use it with any model. Hackathon Finder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hackathon Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tinyfish-io/tinyfish-cookbook/tree/main/skills/hackathon-finder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hackathon Finder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hackathon Finder?

As many as you like. As long as a model supports skills, you can use Hackathon Finder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hackathon Finder AI skill free?

Yes. It is published on GitHub by tinyfish-io under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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