Y Combinator Reader (Read-Only)

Fetches Y Combinator company data from the yc-oss/api, an unofficial open-source API that indexes all publicly launched YC companies. The data is sourced from YC's Algolia search index and updated daily via GitHub Actions.

This is a read-only data source. It provides company profiles, batch listings, industry/tag breakdowns, hiring status, and diversity data. No write operations exist — the API serves static JSON files.

No authentication required. The API is public and free. Just use curl to fetch JSON endpoints.

Step 1: Verify Prerequisites

This skill only needs curl (to fetch data) and jq (to parse/filter JSON). Both are pre-installed on most systems.

!`(command -v curl > /dev/null && echo "CURL_OK" || echo "CURL_MISSING") && (command -v jq > /dev/null && echo "JQ_OK" || echo "JQ_MISSING")`

If JQ_MISSING, install it:

bash
# macOS
brew install jq

# Linux (Debian/Ubuntu)
sudo apt-get install jq

If jq is unavailable, you can still fetch raw JSON with curl and parse it inline with Python or other tools — but jq makes filtering much easier.

Step 2: Identify What the User Needs

Match the user's request to the appropriate endpoint. See references/api_reference.md for full details.

| User Request | Endpoint | Notes | |---|---|---| | Overall YC stats | meta.json | Company count, batch list, industry/tag lists | | All companies | companies/all.json | Full dataset (~5,700 companies) — large response | | Top companies | companies/top.json | ~91 top-performing YC companies | | Companies hiring | companies/hiring.json | ~1,400 currently hiring | | Non-profit companies | companies/nonprofit.json | YC-backed non-profits | | Diversity data | companies/black-founded.json, hispanic-latino-founded.json, women-founded.json | Founder diversity | | Specific batch | batches/{batch-name}.json | e.g., winter-2026.json, spring-2026.json, fall-2025.json | | Single company profile | batches/{batch-name}/{slug}.json | e.g., batches/summer-2009/stripe.json, batches/winter-2009/airbnb.json | | By industry | industries/{industry}.json | e.g., fintech.json, healthcare.json | | By tag | tags/{tag}.json | e.g., ai.json, developer-tools.json |

Batch name format

Batches use {season}-{year} format: winter-2026, spring-2026, summer-2026, fall-2025. Older batches follow the same pattern back to summer-2005. The short form (w09, s21) also works for the per-company endpoint.

Industry and tag name format

Use lowercase with hyphens for multi-word names: real-estate, developer-tools, machine-learning.

Step 3: Execute the Request

Base URL

https://yc-oss.github.io/api/

General pattern

bash
# Fetch and pretty-print
curl -s https://yc-oss.github.io/api/companies/top.json | jq .

# Count companies in a result
curl -s https://yc-oss.github.io/api/batches/winter-2025.json | jq length

# Filter by field (e.g., hiring companies in a batch)
curl -s https://yc-oss.github.io/api/batches/winter-2025.json | jq '[.[] | select(.isHiring == true)]'

# Extract specific fields
curl -s https://yc-oss.github.io/api/companies/top.json | jq '.[] | {name, one_liner, batch, team_size, website}'

# Search by name (case-insensitive)
curl -s https://yc-oss.github.io/api/companies/all.json | jq '[.[] | select(.name | test("stripe"; "i"))]'

Key rules

1. Use -s flag with curl to suppress progress output
2. Pipe through jq for readable output and filtering
3. Avoid fetching companies/all.json unless necessary — it's a large response (~5,700 companies). Prefer more specific endpoints (batches, industries, tags) when possible
4. Use jq select/filter to narrow results client-side when the API doesn't have a specific endpoint for what the user wants
5. Batch names are lowercase with hyphens — winter-2025 not Winter 2025 or W25
6. Tag and industry names are lowercase with hyphens — developer-tools not Developer Tools

Common jq filters

| Filter | Purpose | |---|---| | jq length | Count results | | jq '.[0]' | First company | | jq '.[:10]' | First 10 companies | | jq '[.[] \| select(.isHiring == true)]' | Only hiring companies | | jq '[.[] \| select(.status == "Active")]' | Only active companies | | jq '[.[] \| select(.team_size > 100)]' | Companies with 100+ employees | | jq '.[] \| {name, one_liner, batch, website}' | Select specific fields | | jq '[.[] \| select(.name \| test("query"; "i"))]' | Search by name | | jq 'sort_by(-.team_size) \| .[:10]' | Top 10 by team size |

Step 4: Present the Results

After fetching data, present it clearly for startup/venture research:

1. Summarize key data — company name, one-liner, batch, team size, status, and website
2. Highlight hiring status — note which companies are actively hiring (growth signal)
3. Include website URLs when the user might want to visit the company
4. For batch listings, summarize the batch size and notable companies
5. For industry/tag queries, highlight trends (how many companies, which are top/hiring)
6. For research queries, provide aggregate stats (count, common industries, team size distribution)
7. Note the data freshness — the API updates daily, so data is near-real-time

Step 5: Diagnostics

If a request fails:

| Error | Cause | Fix | |-------|-------|-----| | 404 Not Found | Invalid batch, industry, or tag name | Check meta.json for valid names | | Empty array [] | No companies match the query | Broaden the search or check spelling | | curl: Could not resolve host | No internet connection | Check network connectivity | | Large/slow response | Fetching companies/all.json (5,700+ entries) | Use a more specific endpoint or add jq filters |

To discover valid batch, industry, and tag names:

bash
# List all batches
curl -s https://yc-oss.github.io/api/meta.json | jq '.batches[].name'

# List all industries
curl -s https://yc-oss.github.io/api/meta.json | jq '.industries[].name'

# List all tags (there are 333+)
curl -s https://yc-oss.github.io/api/meta.json | jq '.tags[].name'

Reference Files

• references/api_reference.md — Complete endpoint reference with company schema, all endpoint URLs, and research workflow examples

Read the reference file when you need the exact company field schema, valid batch/industry/tag names, or detailed research workflow patterns.