Awesome-omni-skills linkedin-automation
LinkedIn Automation via Rube MCP workflow skill. Use this skill when the user needs Automate LinkedIn tasks via Rube MCP (Composio): create posts, manage profile, company info, comments, and image uploads. Always search tools first for current schemas and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
git clone https://github.com/diegosouzapw/awesome-omni-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/linkedin-automation" ~/.claude/skills/diegosouzapw-awesome-omni-skills-linkedin-automation && rm -rf "$T"
skills/linkedin-automation/SKILL.mdLinkedIn 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
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
| Situation | Start here | Why it matters |
|---|---|---|
| First-time use | | Confirms repository, branch, commit, and imported path before touching the copied workflow |
| Provenance review | | Gives reviewers a plain-language audit trail for the imported source |
| Workflow execution | | Starts with the smallest copied file that materially changes execution |
| Supporting context | | Adds the next most relevant copied source file without loading the entire package |
| Handoff decision | | Helps the operator switch to a stronger native skill when the task drifts |
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.
- Verify Rube MCP is available by confirming RUBESEARCHTOOLS responds
- Call RUBEMANAGECONNECTIONS with toolkit linkedin
- If connection is not ACTIVE, follow the returned auth link to complete LinkedIn OAuth
- Confirm connection status shows ACTIVE before running any workflows
- LINKEDINGETMY_INFO - Get authenticated user's profile info [Prerequisite]
- LINKEDINREGISTERIMAGE_UPLOAD - Register image upload if post includes an image [Optional]
- 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.
- Verify Rube MCP is available by confirming
respondsRUBE_SEARCH_TOOLS - Call
with toolkitRUBE_MANAGE_CONNECTIONSlinkedin - If connection is not ACTIVE, follow the returned auth link to complete LinkedIn OAuth
- 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:
- Get authenticated user's profile info [Prerequisite]LINKEDIN_GET_MY_INFO
- Register image upload if post includes an image [Optional]LINKEDIN_REGISTER_IMAGE_UPLOAD
- Publish the post [Required]LINKEDIN_CREATE_LINKED_IN_POST
Key parameters:
: Post content texttext
: 'PUBLIC' or 'CONNECTIONS'visibility
: Title for attached mediamedia_title
: Description for attached mediamedia_description
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:
- Get authenticated user's profile [Required]LINKEDIN_GET_MY_INFO
- Get company page details [Optional]LINKEDIN_GET_COMPANY_INFO
Key parameters:
- No parameters needed for GET_MY_INFO (uses authenticated user)
: Company/organization ID for GET_COMPANY_INFOorganization_id
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:
- Register an image upload with LinkedIn [Required]LINKEDIN_REGISTER_IMAGE_UPLOAD- Upload the image binary to the returned upload URL [Required]
- Verify uploaded image status [Optional]LINKEDIN_GET_IMAGES
- Create post with the image asset [Required]LINKEDIN_CREATE_LINKED_IN_POST
Key parameters:
: URN of the image owner (user or organization)owner
: ID of the uploaded image for GET_IMAGESimage_id
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:
- Add a comment to a post [Required]LINKEDIN_CREATE_COMMENT_ON_POST
Key parameters:
: The URN or ID of the post to comment onpost_id
: Comment contenttext
: URN of the commenter (user or organization)actor
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:
- Delete the specified post [Required]LINKEDIN_DELETE_LINKED_IN_POST
Key parameters:
: The URN or ID of the post to deletepost_id
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
with toolkitRUBE_MANAGE_CONNECTIONSlinkedin - Always call
first to get current tool schemasRUBE_SEARCH_TOOLS
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. Load only the files that materially change the answer, 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
- Use when the work is better handled by that native specialization after this imported skill establishes context.@linear-claude-skill
- Use when the work is better handled by that native specialization after this imported skill establishes context.@linkedin-cli
- Use when the work is better handled by that native specialization after this imported skill establishes context.@linkedin-profile-optimizer
- Use when the work is better handled by that native specialization after this imported skill establishes context.@lint-and-validate
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.
| Resource family | What it gives the reviewer | Example path |
|---|---|---|
| copied reference notes, guides, or background material from upstream | |
| worked examples or reusable prompts copied from upstream | |
| upstream helper scripts that change execution or validation | |
| routing or delegation notes that are genuinely part of the imported package | |
| supporting assets or schemas copied from the source package | |
Imported Reference Notes
Imported: Quick Reference
| Task | Tool Slug | Key Params |
|---|---|---|
| Get my profile | LINKEDIN_GET_MY_INFO | (none) |
| Create post | LINKEDIN_CREATE_LINKED_IN_POST | text, visibility |
| Get company info | LINKEDIN_GET_COMPANY_INFO | organization_id |
| Register image upload | LINKEDIN_REGISTER_IMAGE_UPLOAD | owner |
| Get uploaded images | LINKEDIN_GET_IMAGES | image_id |
| Delete post | LINKEDIN_DELETE_LINKED_IN_POST | post_id |
| Comment on post | LINKEDIN_CREATE_COMMENT_ON_POST | post_id, text, actor |
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.