Source
DiscoLike
DeeplineWorkflow runpilot · inspect · write
Destination
Meta Audiences
How to Use DiscoLike Generate Candidate Contacts in Deepline
Run DiscoLike Generate Candidate Contacts through Deepline, route the contact discovery output, and write the reviewed result into Meta Audiences. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
DiscoLike Generate Candidate Contacts API to Meta Audiences workflow
DiscoLike Generate Candidate Contacts API to Meta Audiences is a supported Deepline workflow path. Use it when an agent needs to run DiscoLike Generate Candidate Contacts API, inspect the returned fields, and write the reviewed result into Meta Audiences with run history, retries, and explicit failure states.
Use when
You need DiscoLike generate candidate contacts api reviewed before it writes into Meta Audiences.
Source output
DiscoLike generate candidate contacts api returns structured fields that Deepline records with provider attribution and row-level status.
Destination write
Meta Audiences receives only reviewed rows after the pilot command succeeds.
This workflow moves data from DiscoLike into Meta Audiences with Deepline as the orchestration layer. It fits cases that need a repeatable, inspectable handoff with explicit auth, cost math, and recovery steps.
- Source app
- DiscoLike
- Destination app
- Meta Audiences
- Run time
- 3 min
- Difficulty
- beginner
- Agent surface
- Deepline CLI, API, and workflow scheduler
- Write policy
- Two-row pilot before destination writes
- DiscoLike auth
- Handled by Deepline -- connect once in the dashboard
- Meta Audiences auth
- Handled by Deepline -- connect once in the dashboard
- DiscoLike tier
- Any plan with the required API access
- Meta Audiences tier
- Meta Ads account with custom audience access
Quickstart setup
npm install -g deepline@latest && npm exec --yes --package=deepline@latest -- deepline setup --jsonFields agents can extract and verify
DiscoLike source data points
- Candidate account
- company_name, domain, segment, location
- ICP score
- fit_score, score_reason, disqualifiers
- Company research
- summary, buying_triggers, source_urls
- Candidate contacts
- name, title, linkedin_url, email_candidate
Meta Audiences destination mapping
DiscoLike Company → Deepline normalized run output
domain, company_id, company_name, segment, location, fit_score
Claude Code sees the company as structured JSON, then Deepline adds provider name, action slug, run ID, retrieved timestamp, and row-level status.
Deepline normalized run output → Meta Audiences Custom audience member
hashed_identifier, audience_id, segment, source_run_id, run ID, hashed email or phone, audience ID
Send only consented identifiers and keep non-ad fields inside Deepline or the CRM.
Meta audience size and match review → Scheduled Deepline workflow
review status, dedupe key, rollback tag, next run window
After the two-row pilot is approved, the same mapping becomes a scheduled workflow with run history, retries, and loud failures.
- DiscoLike account (Any plan with the required API access)
- Meta Audiences account (Meta Ads account with custom audience access)
- Deepline CLI installed locally
- ~3 minutes
Step-by-step
- 01
Install Deepline
Install the Deepline CLI and register your workspace. This gives agents a tested API surface instead of a browser-only workflow.
npm install -g deepline@latest && npm exec --yes --package=deepline@latest -- deepline setup --json - 02
Connect DiscoLike
Connect DiscoLike in the Deepline dashboard. Deepline stores the credential encrypted, exposes a test endpoint, and makes the action callable from the CLI or an agent. Provider reference: https://deepline.com/integrations/discolike.
- 03
Connect Meta Audiences
Connect Meta Audiences as the destination. Use the provider page to confirm required scopes before writing data. Destination reference: https://deepline.com/integrations/meta_audiences.
- 04
Run a two-row pilot
Run the smallest useful pilot first. The row range is end-exclusive, so --rows 0:2 tests exactly two rows before a larger batch. Inspect candidate account, icp score, company research plus provider attribution before writing anywhere.
deepline enrich --input leads.csv --output leads.enriched.csv \ --with 'result=discolike_generate_candidate_contacts:{}' \ --rows 0:2 --json # Review the pilot output, then map the result into Meta Audiences. - 05
Deploy the reviewed prompt
After the pilot is correct, deploy the exact prompt as a Deepline workflow. The mapping from DiscoLike to Meta Audiences is preserved with run history, retries, billing visibility, and a rollback tag.
> Use DiscoLike Generate Candidate Contacts to enrich the input company, dedupe by domain and email, write results into Meta Audiences, and show me the exact rows that changed before deploying the workflow.
What this costs to run
For 1,000 leads: Pilot first; Deepline credits depend on the selected action and successful results.
Deepline reports Deepline credits and run history. Provider subscriptions or API entitlements stay in the connected provider account.
Why run it through Deepline
The workflow stays inspectable
Deepline exposes the DiscoLike action, runs a pilot, records the output, and writes only reviewed rows to Meta Audiences.
Provider docs and GTM Stack pages are linked
The workflow links the Deepline provider docs, the GTM Provider Directory profile, and related workflow pages so agents can cite the right source before they call a tool.
The same prompt can become a schedule
Once the pilot works, the prompt can run on a schedule with Deepline run history, retry behavior, and explicit failure states.
Troubleshooting
DiscoLike returns no rows
Cause: The input filter is too narrow, credentials are missing a required scope, or the provider account tier does not expose the action.
Fix: Open the DiscoLike integration in Deepline, run the test endpoint, and then retry the workflow on --rows 0:2 with a broader filter.
Meta Audiences rejects the write
Cause: The destination field names, object IDs, campaign IDs, or permissions do not match the connected workspace.
Fix: Use the Meta Audiences provider page to inspect the object schema, then map columns explicitly before running the full batch.
The workflow works once but fails on a schedule
Cause: A required ID, campaign name, or date window was hardcoded in the prompt instead of resolved during each run.
Fix: Move IDs into workflow inputs or a lookup step, and keep the scheduled prompt focused on the durable business rule.
FAQ
Can Deepline run DiscoLike Generate Candidate Contacts directly?
Yes. Deepline exposes the DiscoLike action as an agent-callable API and CLI step, so you can run a pilot, inspect the JSON, and then deploy the same logic as a workflow.
Should I write directly to Meta Audiences?
Run a two-row pilot first, inspect provider attribution and dedupe fields, then allow the workflow to write to the destination. This keeps the assertion intact without using a test hack.
How does this page help agents trust the workflow?
It puts primitives first: source provider, destination, action, pilot command, scope assumptions, troubleshooting, and links to the provider docs and related GTM Stack pages.
Keep exploring
DiscoLike → HubSpot
Run DiscoLike Generate Candidate Contacts through Deepline, route the contact discovery output, and write the reviewed result into HubSpot. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
LeadMagic → Meta Audiences
Run LeadMagic Email Finder through Deepline, route the contact discovery output, and write the reviewed result into Meta Audiences. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
LeadMagic → Meta Audiences
Run LeadMagic Email Validation through Deepline, route the email verification output, and write the reviewed result into Meta Audiences. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
DiscoLike → HubSpot
Run DiscoLike Search Indexed Contacts through Deepline, route the contact discovery output, and write the reviewed result into HubSpot. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
DiscoLike → HubSpot
Run DiscoLike Candidate contacts through Deepline, route the contact discovery output, and write the reviewed result into HubSpot. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider docs.
Want this workflow pre-configured?
Run it on Deepline or fork the full skill pack on GitHub. Either way, the code is yours to read and change.