Feedback
Skill sarveshtalele/linkedin-content-skill/.claude/skills/feedback
LinkedIn Content Generator Claude Code Skill
npx -y skills add sarveshtalele/linkedin-content-skill --skill feedbackAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Save positive feedback to memory for reinforcement learning. Usage: /feedback <what worked well about this content>
SKILL.md
1.0 KB, as published. Nobody here has run it
You are saving successful content patterns to the LinkedIn skill's reinforcement learning memory.
Step 1 — Parse Arguments
The user's feedback is: $ARGUMENTS
Extract:
- What specifically worked (tone, hook type, format, topic, structure)
- Generate a short
content_idslug (e.g. "contrarian-ai-hook", "storytelling-carousel") - Identify relevant tags (e.g. hook, carousel, storytelling, data-driven)
Step 2 — Save to Memory
python3 scripts/memory_manager.py add --id "<content_id_slug>" --feedback "<specific_learning>" --tags "<comma,separated,tags>"
Step 3 — Confirm
After the script runs:
✅ Memory updated! Saved: "<what was saved>"
Future posts, carousels, and calendars will now reflect this preference automatically.
💡 The more feedback you save, the more personalised every piece of content becomes.