Linkedin CLI V2

LinkedIn Skill

Overview

This public intake copy packages plugins/antigravity-awesome-skills/skills/linkedin-cli from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Authentication, Global Flags, Output Format, Important Behavior, Limitations.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Use this skill when you need to automate LinkedIn tasks such as profile fetching, connection management, or post creation via CLI, especially when integrated into automated workflows.

• LinkedIn Skill You have access to linkedin – a CLI tool for LinkedIn automation.

• Use it to fetch profiles, search people and companies, send messages, manage connections, create posts, react, comment, and more.
• Each command sends a request to Linked API, which runs a real cloud browser to perform the action on LinkedIn.
• Operations are not instant – expect 30 seconds to several minutes depending on complexity.
• If linkedin is not available, install it: bash npm install -g @linkedapi/linkedin-cli

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Authentication

If a command fails with exit code 2 (authentication error), ask the user to set up their account:

1. Go to app.linkedapi.io and sign up or log in
2. Connect their LinkedIn account
3. Copy the Linked API Token and Identification Token from the dashboard

Once the user provides the tokens, run:

linkedin setup --linked-api-token=TOKEN --identification-token=TOKEN

When to Use

Use this skill when you need to orchestrate LinkedIn actions from scripts or an AI agent instead of clicking through the web UI:

• Building outreach, research, or recruiting workflows that rely on LinkedIn data and messaging.
• Enriching leads or accounts by fetching people and company profiles in bulk.
• Coordinating multi-step Sales Navigator or workflow runs where JSON output and exit codes are required.

Always respect LinkedIn’s terms of service, local regulations, and your organisation’s compliance policies when using automation against real accounts.

Examples

Example 1: Ask for the upstream workflow directly

Use @linkedin-cli-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @linkedin-cli-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @linkedin-cli-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @linkedin-cli-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Commands

Fetch a Person Profile

linkedin person fetch <url> [flags] --json -q

Optional flags to include additional data:

• --experience – work history
• --education – education history
• --skills – skills list
• --languages – languages
• --posts – recent posts (with --posts-limit N, --posts-since TIMESTAMP)
• --comments – recent comments (with --comments-limit N, --comments-since TIMESTAMP)
• --reactions – recent reactions (with --reactions-limit N, --reactions-since TIMESTAMP)

Only request additional data when needed – each flag increases execution time.

# Basic profile
linkedin person fetch https://www.linkedin.com/in/username --json -q

# With experience and education
linkedin person fetch https://www.linkedin.com/in/username --experience --education --json -q

# With last 5 posts
linkedin person fetch https://www.linkedin.com/in/username --posts --posts-limit 5 --json -q

Search People

linkedin person search [flags] --json -q

linkedin person search --term "product manager" --locations "San Francisco" --json -q
linkedin person search --current-companies "Google" --position "Engineer" --limit 20 --json -q

Fetch a Company

linkedin company fetch <url> [flags] --json -q

Optional flags:

• --employees – include employees
• --dms – include decision makers
• --posts – include company posts

Employee filters (require --employees):

# Basic company info
linkedin company fetch https://www.linkedin.com/company/name --json -q

# With employees filtered by position
linkedin company fetch https://www.linkedin.com/company/name --employees --employees-position "Engineer" --json -q

# With decision makers and posts
linkedin company fetch https://www.linkedin.com/company/name --dms --posts --posts-limit 10 --json -q

Search Companies

linkedin company search [flags] --json -q

linkedin company search --term "fintech" --sizes "11-50,51-200" --json -q

Send a Message

linkedin message send <person-url> '<text>' --json -q

Text up to 1900 characters. Wrap the message in single quotes to avoid shell interpretation issues.

linkedin message send https://www.linkedin.com/in/username 'Hey, loved your latest post!' --json -q

Get Conversation

linkedin message get <person-url> [--since TIMESTAMP] --json -q

The first call for a conversation triggers a background sync and may take longer. Subsequent calls are faster.

linkedin message get https://www.linkedin.com/in/username --json -q
linkedin message get https://www.linkedin.com/in/username --since 2024-01-15T10:30:00Z --json -q

Connection Management

Check connection status

linkedin connection status <url> --json -q

Send connection request

linkedin connection send <url> [--note 'text'] [--email user@example.com] --json -q

List connections

linkedin connection list [flags] --json -q

linkedin connection list --limit 50 --json -q
linkedin connection list --current-companies "Google" --position "Engineer" --json -q
linkedin connection list --since 2024-01-01T00:00:00Z --json -q

List pending outgoing requests

linkedin connection pending --json -q

Withdraw a pending request

linkedin connection withdraw <url> [--no-unfollow] --json -q

By default, withdrawing also unfollows the person. Use --no-unfollow to keep following.

Remove a connection

linkedin connection remove <url> --json -q

Posts

Fetch a post

linkedin post fetch <url> [flags] --json -q

linkedin post fetch https://www.linkedin.com/posts/username_activity-123 --json -q

# With comments sorted by most recent, including replies
linkedin post fetch https://www.linkedin.com/posts/username_activity-123 \
  --comments --comments-sort mostRecent --comments-replies --json -q

Create a post

linkedin post create '<text>' [flags] --json -q

Attachment limits: up to 9 images, or 1 video, or 1 document. Cannot mix types.

linkedin post create 'Excited to share our latest update!' --json -q

# With a document
linkedin post create 'Our Q4 report' \
  --attachments "https://example.com/report.pdf:document:Q4 Report" --json -q

# Post as a company
linkedin post create 'Company announcement' \
  --company-url https://www.linkedin.com/company/name --json -q

React to a post

linkedin post react <url> --type <reaction> [--company-url <url>] --json -q

Reaction types: like, love, support, celebrate, insightful, funny.

linkedin post react https://www.linkedin.com/posts/username_activity-123 --type like --json -q

# React on behalf of a company
linkedin post react https://www.linkedin.com/posts/username_activity-123 --type celebrate \
  --company-url https://www.linkedin.com/company/name --json -q

Comment on a post

linkedin post comment <url> '<text>' [--company-url <url>] --json -q

Text up to 1000 characters.

linkedin post comment https://www.linkedin.com/posts/username_activity-123 'Great insights!' --json -q

# Comment on behalf of a company
linkedin post comment https://www.linkedin.com/posts/username_activity-123 'Well said!' \
  --company-url https://www.linkedin.com/company/name --json -q

Statistics

# Social Selling Index
linkedin stats ssi --json -q

# Performance analytics (profile views, post impressions, search appearances)
linkedin stats performance --json -q

# API usage for a date range
linkedin stats usage --start 2024-01-01T00:00:00Z --end 2024-01-31T00:00:00Z --json -q

Sales Navigator

Requires a LinkedIn Sales Navigator subscription. Uses hashed URLs for person/company lookups.

Fetch person

linkedin navigator person fetch <hashed-url> --json -q

Search people

linkedin navigator person search [flags] --json -q

linkedin navigator person search --term "VP Marketing" --locations "United States" --json -q
linkedin navigator person search --years-of-experience "moreThanTen" --position "CEO" --json -q

Fetch company

linkedin navigator company fetch <hashed-url> [flags] --json -q

Optional flags:

• --employees – include employees
• --dms – include decision makers

Employee filters (require --employees):

linkedin navigator company fetch https://www.linkedin.com/sales/company/97ural --employees --dms --json -q
linkedin navigator company fetch https://www.linkedin.com/sales/company/97ural \
  --employees --employees-positions "Engineer,Designer" --employees-locations "Europe" --json -q

Search companies

linkedin navigator company search [flags] --json -q

linkedin navigator company search --term "fintech" --sizes "11-50,51-200" --json -q
linkedin navigator company search --revenue-min 10 --revenue-max 100 --locations "United States" --json -q

Send InMail

linkedin navigator message send <person-url> '<text>' --subject '<subject>' --json -q

Text up to 1900 characters. Subject up to 80 characters.

linkedin navigator message send https://www.linkedin.com/in/username \
  'Would love to chat about API integrations' --subject 'Partnership Opportunity' --json -q

Get Sales Navigator conversation

linkedin navigator message get <person-url> [--since TIMESTAMP] --json -q

Custom Workflows

Execute a custom workflow definition from a file, stdin, or inline:

# From file
linkedin workflow run --file workflow.json --json -q

# From stdin
cat workflow.json | linkedin workflow run --json -q

# Inline
echo '{"actions":[...]}' | linkedin workflow run --json -q

Check workflow status or wait for completion:

linkedin workflow status <id> --json -q
linkedin workflow status <id> --wait --json -q

See Building Workflows for the workflow JSON schema.

Account Management

linkedin account list                            # List accounts (* = active)
linkedin account switch "Name"                   # Switch active account
linkedin account rename "Name" --name "New Name" # Rename account
linkedin reset                                   # Remove active account
linkedin reset --all                             # Remove all accounts

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/linkedin-cli, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @cred-omega-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @customs-trade-compliance-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @docker-expert-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ejentum-reasoning-harness-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Global Flags

Always use --json and -q for machine-readable output:

linkedin <command> --json -q

Imported: Output Format

Success:

{ "success": true, "data": { "name": "John Doe", "headline": "Engineer" } }

Error:

{
  "success": false,
  "error": { "type": "personNotFound", "message": "Person not found" }
}

Exit code 0 means the API call succeeded – always check the success field for the action outcome. Non-zero exit codes indicate infrastructure errors:

Imported: Important Behavior

• Sequential execution. All operations for an account run one at a time. Multiple requests queue up.
• Not instant. A real browser navigates LinkedIn – expect 30 seconds to several minutes per operation.
• Timestamps in UTC. All dates and times are in UTC.
• Single quotes for text arguments. Use single quotes around message text, post text, and comments to avoid shell interpretation issues with special characters.
• Action limits. Per-account limits are configurable on the platform. A limitExceeded error means the limit was reached.
• URL normalization. All LinkedIn URLs in responses are normalized to https://www.linkedin.com/... format without trailing slashes.
• Null fields. Fields that are unavailable are returned as null or [], not omitted.

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.