linkedin-distribution-module

name	linkedin-distribution-module
description	Specialized skill for mastering LinkedIn distribution. Encapsulates LinkedIn's algorithmic rules, manages Groups, and ensures optimal Comment Cascade execution.
triggers	["post to linkedin","linkedin distribution","linkedin campaign"]

LinkedIn Distribution Module

Purpose

This skill specializes in LinkedIn content distribution. It encapsulates the "invisible" algorithmic rules of the platform to maximize organic reach and prevent spam or penalties.

Output Format

Always start your response with:

━━━ Brand Amplification: LinkedIn Distribution Module ━━━

Comment Hijack Gates (MANDATORY for hijack-style comments)

A "hijack" = posting a substantive comment on an influencer post to drive traffic to your hub. Two gates fire before any hijack comment is posted.

Gate A — Target scoring (run first, before writing the comment)

python3 "$(ls -v ~/.claude/plugins/cache/xos/brand-amplification/*/skills/social-distribution-engine/detect.py 2>/dev/null | tail -1)" '{
  "platform": "linkedin",
  "author_followers": <int or omit if unknown>,
  "post_age_hours": <float>,
  "post_likes": <int>,
  "post_comments": <int>,
  "post_reposts": <int>,
  "topic_relevance": <0-3: 3=direct AI/work/agents match, 2=adjacent, 1=tangential, 0=unrelated>,
  "has_prior_engagement": <true if author has engaged with your content>,
  "post_velocity": "fast|normal|slow"
}'

Exit 0 = HIJACK or MONITOR (proceed to write the comment). Exit 1 = SKIP (don't write — surface the score and reason to the user).

Gate B — Comment quality + dedup (run before posting)

python3 "$(ls -v ~/.claude/plugins/cache/xos/brand-amplification/*/rules/comment-hijack-gate/HOW.py 2>/dev/null | tail -1)" '{
  "platform": "linkedin",
  "target_post_url": "<URL>",
  "target_post_age_hours": <float>,
  "comment_text": "<full comment including hub URL>",
  "hub_url": "<hub post URL>",
  "previously_commented_urls": ["<URL>", ...]
}'

Exit 0 = PASS (post the comment). Exit 1 = BLOCK (do not post — surface remediation).

Gate B checks: hub_url present in comment, freshness (≤72h for LinkedIn), dedup, and LLM standalone_value judge.

Playbook: $(ls -v ~/.claude/plugins/cache/xos/brand-amplification/*/skills/social-distribution-engine/hijack-playbook.md 2>/dev/null | tail -1)

Capabilities

1. Execute Algorithmic Posting

When distributing to LinkedIn:

• No Link Penalties: Never place links in the main text of the post. Always place the link to the hub (e.g., Substack) in the first comment.
• Hub vs. Spoke: If LinkedIn is a spoke, apply the "Comment Cascade" protocol. Ensure the first comment links back to the canonical Hub Post.
• Gap Timing: Enforce a minimum 15-minute gap between LinkedIn spokes to avoid cross-post penalties.
• Asset Attachment: Use correct visual assets based on the campaign specs (e.g., 1200x627 for short posts, no images for comment cascades).

2. Group Management & Posting

For full LinkedIn Groups discovery + distribution, use the linkedin-groups-distribution-module skill.

Summary of groups rules enforced by that skill:

• Check brain.read("brand-amplification/campaigns/social-channel-directory.md") for approved LinkedIn Groups.
• 7-day cooldown per group (enforced by linkedin-groups-dedup gate).
• Max 3 groups per campaign. Max 150 words per group post. Open with question — not declaration.
• Dedup gate fires before every group post:

python3 "$(ls -v ~/.claude/plugins/cache/xos/brand-amplification/*/rules/linkedin-groups-dedup/HOW.py 2>/dev/null | tail -1)" \
  '{"group_url": "<URL>"}'

Exit 0 = PASS. Exit 1 = BLOCK (with next available date).

• Rule: If a group historically yields 0 engagement, do NOT post. Escalate to the Analytics Engine for pruning.

3. Record Execution

After posting, immediately update the campaign tracker (e.g., [campaign-name]-distribution-stats.md) with the exact time, URL, and status.

Lessons Repository

Update WIP/career-os-product/linkedin-algo-lessons.md if any new algorithmic insight is discovered during distribution.