Runnable scripts for common GTM workflows on the DiscoLike API, written against the Python SDK. Each one is stdlib plus discolike, takes its inputs on the command line, and reads your key from DISCOLIKE_API_KEY.
pip install "discolike[cli]"
export DISCOLIKE_API_KEY="dl_..." # create one at https://app.discolike.com/account/management/keys| Script | What it does | How to run |
|---|---|---|
tam_from_seed_domains.py |
Counts companies in a country and employee bucket, then discovers lookalikes of three seed domains and writes them to CSV | python examples/tam_from_seed_domains.py stripe.com adyen.com checkout.com US 51,200 --max-records 100 --output tam.csv |
icp_prompt_search.py |
Turns a plain-English ICP into a company list with similarity scores | python examples/icp_prompt_search.py "Series A fintechs in Europe selling to SMBs" --country EU |
phrase_match_count.py |
Counts sites whose text contains an exact phrase, then lists them | python examples/phrase_match_count.py "SOC 2" --country US |
enrich_crm_export.py |
Adds firmographics (size, revenue, location, industry, business model) to every domain in a CSV | python examples/enrich_crm_export.py accounts.csv --domain-column website --output enriched.csv |
contacts_at_results.py |
Discovers companies for an ICP, then finds contacts at the top N filtered by seniority, department, or title | python examples/contacts_at_results.py "B2B SaaS selling to sales teams" --top 10 --seniority executive --has-email |
agent_signup_to_first_search.py |
Opens a DiscoLike account for a person from an agent, relays next_step, and runs a first search once DISCOLIKE_API_KEY is set |
python examples/agent_signup_to_first_search.py --email jane@acme.com --first-name Jane --last-name Doe |
discover_and_enrich.py |
Discovers companies for an ICP, then runs a DiscoGen research prompt over them (needs a BYOK LLM provider) | python examples/discover_and_enrich.py --icp "Cybersecurity for SMBs" --country US --query "What is their pricing model?" |
find_emails_from_csv.py |
Finds verified work emails for a CSV of first name, last name, domain in batches of 500; only status found bills |
python examples/find_emails_from_csv.py people.csv --output emails.csv |
match_crm_contacts.py |
Matches a messy CRM contact export to DiscoLike persona IDs with resumable checkpointing | python examples/match_crm_contacts.py contacts.csv --output matched.csv |
cli_recipes.sh |
The same searches as discolike discover, discolike count, discolike contacts search, and discolike signup one-liners, plus a discolike bulk volume pull |
bash examples/cli_recipes.sh |
Every script prints --help. Employee ranges are min,max strings such as 51,200; countries are ISO-2 codes or region aliases like EU, DACH, APAC.