Linkedin Automation

LinkedIn Automation via Rube MCP

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/linkedin-automation 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.

LinkedIn Automation via Rube MCP Automate LinkedIn operations through Composio's LinkedIn toolkit via Rube MCP.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Prerequisites, Common Patterns, Known Pitfalls, 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.

• This skill is applicable to execute the workflow or actions described in the overview.
• Use when the request clearly matches the imported source intent: Automate LinkedIn tasks via Rube MCP (Composio): create posts, manage profile, company info, comments, and image uploads. Always search tools first for current schemas.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.
• Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

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. Verify Rube MCP is available by confirming RUBESEARCHTOOLS responds
2. Call RUBEMANAGECONNECTIONS with toolkit linkedin
3. If connection is not ACTIVE, follow the returned auth link to complete LinkedIn OAuth
4. Confirm connection status shows ACTIVE before running any workflows
5. LINKEDINGETMY_INFO - Get authenticated user's profile info [Prerequisite]
6. LINKEDINREGISTERIMAGE_UPLOAD - Register image upload if post includes an image [Optional]
7. LINKEDINCREATELINKEDINPOST - Publish the post [Required]

Imported Workflow Notes

Imported: Setup

Get Rube MCP: Add https://rube.app/mcp as an MCP server in your client configuration. No API keys needed — just add the endpoint and it works.

1. Verify Rube MCP is available by confirming RUBE_SEARCH_TOOLS responds
2. Call RUBE_MANAGE_CONNECTIONS with toolkit linkedin
3. If connection is not ACTIVE, follow the returned auth link to complete LinkedIn OAuth
4. Confirm connection status shows ACTIVE before running any workflows

Imported: Core Workflows

1. Create a LinkedIn Post

When to use: User wants to publish a text post on LinkedIn

Tool sequence:

1. LINKEDIN_GET_MY_INFO - Get authenticated user's profile info [Prerequisite]
2. LINKEDIN_REGISTER_IMAGE_UPLOAD - Register image upload if post includes an image [Optional]
3. LINKEDIN_CREATE_LINKED_IN_POST - Publish the post [Required]

Key parameters:

• text: Post content text
• visibility: 'PUBLIC' or 'CONNECTIONS'
• media_title: Title for attached media
• media_description: Description for attached media

Pitfalls:

• Must retrieve user profile URN via GET_MY_INFO before creating a post
• Image uploads require a two-step process: register upload first, then include the asset in the post
• Post text has character limits enforced by LinkedIn API
• Visibility defaults may vary; always specify explicitly

2. Get Profile Information

When to use: User wants to retrieve their LinkedIn profile or company details

Tool sequence:

1. LINKEDIN_GET_MY_INFO - Get authenticated user's profile [Required]
2. LINKEDIN_GET_COMPANY_INFO - Get company page details [Optional]

Key parameters:

• No parameters needed for GET_MY_INFO (uses authenticated user)
• organization_id: Company/organization ID for GET_COMPANY_INFO

Pitfalls:

• GET_MY_INFO returns the authenticated user only; cannot look up other users
• Company info requires the numeric organization ID, not the company name or vanity URL
• Some profile fields may be restricted based on OAuth scopes granted

3. Manage Post Images

When to use: User wants to upload and attach images to LinkedIn posts

Tool sequence:

1. LINKEDIN_REGISTER_IMAGE_UPLOAD - Register an image upload with LinkedIn [Required]
2. Upload the image binary to the returned upload URL [Required]
3. LINKEDIN_GET_IMAGES - Verify uploaded image status [Optional]
4. LINKEDIN_CREATE_LINKED_IN_POST - Create post with the image asset [Required]

Key parameters:

• owner: URN of the image owner (user or organization)
• image_id: ID of the uploaded image for GET_IMAGES

Pitfalls:

• The upload is a two-phase process: register then upload binary
• Image asset URN from registration must be used when creating the post
• Supported formats typically include JPG, PNG, and GIF
• Large images may take time to process before they are available

4. Comment on Posts

When to use: User wants to comment on an existing LinkedIn post

Tool sequence:

1. LINKEDIN_CREATE_COMMENT_ON_POST - Add a comment to a post [Required]

Key parameters:

• post_id: The URN or ID of the post to comment on
• text: Comment content
• actor: URN of the commenter (user or organization)

Pitfalls:

• Post ID must be a valid LinkedIn URN format
• The actor URN must match the authenticated user or a managed organization
• Rate limits apply to comment creation; avoid rapid-fire comments

5. Delete a Post

When to use: User wants to remove a previously published LinkedIn post

Tool sequence:

1. LINKEDIN_DELETE_LINKED_IN_POST - Delete the specified post [Required]

Key parameters:

• post_id: The URN or ID of the post to delete

Pitfalls:

• Deletion is permanent and cannot be undone
• Only the post author or organization admin can delete a post
• The post_id must be the exact URN returned when the post was created

Imported: Prerequisites

• Rube MCP must be connected (RUBE_SEARCH_TOOLS available)
• Active LinkedIn connection via RUBE_MANAGE_CONNECTIONS with toolkit linkedin
• Always call RUBE_SEARCH_TOOLS first to get current tool schemas

Examples

Example 1: Ask for the upstream workflow directly

Use @linkedin-automation 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-automation 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-automation 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-automation 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.

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-claude/skills/linkedin-automation, 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

• @00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @10-andruia-skill-smith-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: Quick Reference

Imported: Common Patterns

ID Resolution

User URN from profile:

1. Call LINKEDIN_GET_MY_INFO
2. Extract user URN (e.g., 'urn:li:person:XXXXXXXXXX')
3. Use URN as actor/owner in subsequent calls

Organization ID from company:

1. Call LINKEDIN_GET_COMPANY_INFO with organization_id
2. Extract organization URN for posting as a company page

Image Upload Flow

• Call REGISTER_IMAGE_UPLOAD to get upload URL and asset URN
• Upload the binary image to the provided URL
• Use the asset URN when creating a post with media
• Verify with GET_IMAGES if upload status is uncertain

Imported: Known Pitfalls

Authentication:

• LinkedIn OAuth tokens have limited scopes; ensure required permissions are granted
• Tokens expire; re-authenticate if API calls return 401 errors

URN Formats:

• LinkedIn uses URN identifiers (e.g., 'urn:li:person:ABC123')
• Always use the full URN format, not just the alphanumeric ID portion
• Organization URNs differ from person URNs

Rate Limits:

• LinkedIn API has strict daily rate limits on post creation and comments
• Implement backoff strategies for bulk operations
• Monitor 429 responses and respect Retry-After headers

Content Restrictions:

• Posts have character limits enforced by the API
• Some content types (polls, documents) may require additional API features
• HTML markup in post text is not supported

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.