| name | import-linkedin-history |
| description | Parse a LinkedIn data export ZIP — positions, connections, messages, profile — and land structured markdown/CSV in <WORKING_FOLDER>/linkedin/. Surfaces follow-up candidates (recent connections + recent message threads) for the user to consider routing to outreach. |
| disable-model-invocation | false |
| allowed-tools | Read, Write, Bash(unzip *), Bash(mkdir *), Bash(test *), Bash(ls *), Bash(file *), Bash(head *), Bash(wc *) |
Import LinkedIn History
Accept a LinkedIn data export ZIP, parse it, land structured outputs. Optionally cross-reference connections against the user's target lists.
Inputs
$ARGUMENTS:
- Required:
<zip-path> — path to the LinkedIn export ZIP (the "Get a copy of your data" download).
- Optional:
--cross-ref=<domain-slug> — flag connections at companies in this domain note.
- Optional:
--surface-followups — surface recent connections / message threads as outreach candidates.
Examples
/career:ecosystem linkedin-import ~/Downloads/Basic_LinkedInDataExport_2026-04-28.zip
/career:ecosystem linkedin-import ~/Downloads/li-export.zip --cross-ref=ai-eval-startups --surface-followups
Procedure
1. Validate + extract
Check ZIP exists. Extract to ${WORKING_FOLDER}/linkedin/raw/ (overwrite on re-run with confirmation).
LinkedIn exports typically contain: Profile.csv, Positions.csv, Education.csv, Connections.csv, messages.csv, Endorsement_Received_Info.csv, Skills.csv, Recommendations_Received.csv (exact filenames vary by export tier).
Inventory the files present and the row counts.
2. Parse + structure
Land parsed outputs:
${WORKING_FOLDER}/linkedin/profile.md — single document with profile + positions + education + skills + endorsements summary.${WORKING_FOLDER}/linkedin/connections.csv — normalized columns: name, headline, company, role, connected_on, profile_url.${WORKING_FOLDER}/linkedin/messages/<thread-id>.md — one file per thread (or one consolidated messages.md for sparse exports).
3. Cross-reference (if --cross-ref)
For each connection, check whether their company matches a company in domain-notes/${cross-ref}.md. Tag matches in ${WORKING_FOLDER}/linkedin/cross-ref-${cross-ref}.md:
# LinkedIn × {{domain}} overlap
| connection | role | company (matched) | connected_on | last_message_at | suggested action |
4. Surface follow-ups (if --surface-followups)
- Recent connections (last 90 days) with no follow-up message → list as
## Cold connections — never followed up.
- Active message threads with the user as last sender > 14 days ago → list as
## Stalled threads — your move.
- Active threads with the counterparty as last sender → list as
## Threads waiting on you.
Write to ${WORKING_FOLDER}/linkedin/follow-ups.md. Don't auto-route to outreach.
5. Print summary
linkedin imported: linkedin/
profile + positions + connections + messages: parsed
connections: <n>
messages: <n> threads
cross-ref overlaps: <n> (if --cross-ref)
follow-up candidates: <n> (if --surface-followups)
next:
cross-ref → /career:outreach find <company> (already-connected? skip Hunter)
follow-ups → review linkedin/follow-ups.md, route to /career:outreach draft for the strongest 2–3
Guardrails
- Don't write back to LinkedIn. This skill parses an export — it doesn't post, message, or connect.
- Connections data is private. Files land in
${WORKING_FOLDER}/linkedin/ which the workspace .gitignore should already cover via linkedin/ (add it if not).
- When suggesting follow-ups, don't draft messages — that belongs to
draft-outreach. This skill surfaces candidates only.
Failure modes
- ZIP doesn't look like a LinkedIn export → bail with a list of files found vs. expected filenames.
- Some columns missing (LinkedIn export tier varies) → continue with the columns present; mark missing fields explicitly.
- No connections file in export → write profile-only output and warn.
