export-csv

name	export-csv
description	Convert any or all sourcing pipeline JSON files to CSV. Handles flattening of nested objects and arrays. Saves CSV files alongside the JSON files. Triggers on: "export csv", "convert to csv", "export data", "download csv", "export all", "get csv", "export companies", "export founders", "export results".

Export CSV

Convert sourcing pipeline JSON files to CSV. Each file gets its own CSV saved in the same folder.

Available exports

File	CSV output	Contents
data/raw/yc_companies.json	data/raw/yc_companies.csv	One row per company (raw YC data)
data/normalized/enriched_founders.json	data/normalized/enriched_founders.csv	One row per founder with enriched contact details
data/raw/website_content.json	data/raw/website_content.csv	One row per company with website signals
data/normalized/company_news.json	data/normalized/company_news.csv	One row per company with top news article flattened
data/normalized/company_fundraises.json	data/normalized/company_fundraises.csv	One row per company with latest round details
data/normalized/sourced_companies.json	data/normalized/sourced_companies.csv	Full merged output — one row per company

What to ask

If the VC does not specify which file(s) to export, ask:

Which files would you like to export to CSV?

  1. All available files
  2. yc_companies — raw YC company data
  3. enriched_founders — founders with emails and LinkedIn
  4. website_content — scraped website signals
  5. company_news — latest news and momentum
  6. company_fundraises — latest funding rounds
  7. sourced_companies — full merged output (recommended)

Reply with a number, a comma-separated list (e.g. "3,6"), or "all".

Only export files that exist. Skip and note any that are missing.

CSV column definitions

yc_companies.csv

company_id, company_name, yc_profile_url, short_description, batch,
industry, subindustry, stage, status, tags,
company_location, year_founded, team_size,
website, company_linkedin, company_x, company_crunchbase, company_github,
is_hiring, number_of_open_jobs

• tags: join array with |
• Flatten founders[] into separate columns: founder_1_name, founder_1_email, founder_1_linkedin, etc. (up to 3 founders)

enriched_founders.csv

company_id, company_name, founder_id, name, title, bio, bio_source,
email, email_status, email_tier, email_source,
linkedin, linkedin_source, x

website_content.csv

company_id, company_name, website, scrape_status,
headline, product_description, target_customer,
value_proposition, pricing_signals, tech_signals,
content_mismatch

company_news.csv

Flatten top article (most recent) into columns:

company_id, company_name, news_momentum,
product_hunt_featured, hacker_news_featured,
top_article_title, top_article_url, top_article_source,
top_article_date, top_article_signal_type, top_article_summary,
total_articles_found

company_fundraises.csv

company_id, company_name, fundraising_status,
total_raised_usd, has_post_yc_funding, likely_raising_soon,
last_round_type, last_round_amount_usd, last_round_date,
last_round_lead_investors, last_round_all_investors,
last_round_source_url, notes

• Arrays: join with |

sourced_companies.csv (full merged output)

company_id, company_name, batch, industry, stage, status,
company_location, year_founded, team_size, website,
short_description, long_description,
company_linkedin, company_x, company_crunchbase,
is_hiring, number_of_open_jobs,
founder_1_name, founder_1_email, founder_1_email_tier, founder_1_linkedin,
founder_2_name, founder_2_email, founder_2_email_tier, founder_2_linkedin,
founder_3_name, founder_3_email, founder_3_email_tier, founder_3_linkedin,
website_headline, website_product_description, website_target_customer,
website_value_proposition, website_pricing_signals,
news_momentum, top_article_title, top_article_source, top_article_date,
fundraising_status, total_raised_usd, has_post_yc_funding,
last_round_type, last_round_amount_usd, last_round_date, last_round_lead_investors,
likely_raising_soon

How to write the CSV

Always write the Python conversion script to a .py file first, then execute it. Never use a bash heredoc (<<'EOF') to run Python inline — it triggers a false-positive safety warning due to curly braces in dict comprehensions.

Correct pattern:

1. Write the script to scripts/export_csv.py using the file-write tool
2. Run it: python3 scripts/export_csv.py
3. Delete the script after it runs (optional)

Wrong pattern (do not use):

python3 - <<'EOF'
...script with {curly braces}...
EOF

CSV formatting rules

• Always include a header row
• Wrap any field containing commas, newlines, or double quotes in double quotes
• Escape internal double quotes as ""
• Use UTF-8 encoding
• Null values → empty cell (not the string "null")

After export

List each file written with its row count:

Exported:
  ✓ data/normalized/sourced_companies.csv — 47 rows
  ✓ data/normalized/enriched_founders.csv — 89 rows
  ✓ data/normalized/company_fundraises.csv — 47 rows

Skipped (file not found):
  - data/raw/website_content.json