Generate LinkedIn posts from shared source material, written in each user's personal style.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionlinkedin-post-generatorExecute the skills CLI command in your project's root directory to begin installation:
Fetches linkedin-post-generator from casper-studios/casper-marketplace and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate linkedin-post-generator. Access via /linkedin-post-generator in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Generate LinkedIn posts from shared source material, written in each user's personal style.
~/.config/casper/linkedin-style.md (never committed)~/.config/casper/linkedin-sources.md (never committed)source-material/references/prompt-template.mdCheck if ~/.config/casper/linkedin-style.md exists.
If it does NOT exist, run the style setup flow:
https://linkedin.com/posts/...) or paste the text directly."python ${CLAUDE_PLUGIN_ROOT}/skills/apify-scrapers/scripts/scrape_linkedin_posts.py search "{url}" --max-posts 1
Extract the post text from the JSON output. If a URL fails to fetch, ask the user to paste that post's text instead.~/.config/casper/ directory if it doesn't exist~/.config/casper/linkedin-style.md using this format:# LinkedIn Style Profile
Generated: [date]
## Tone
[analysis]
## Structure Patterns
[paragraph length, line breaks, formatting habits]
## Hook Style
[how they open posts]
## CTA / Closing Style
[how they end posts — questions, challenges, etc.]
## Vocabulary & Phrases
[distinctive phrases, word choices, energy level]
## Sample Posts
[the 3 original posts, for reference]
/casper:generate-linkedin-post --setup"After style setup completes (or if style exists but source-material/ is empty), check for source material:
source-material/ contains any .md files besides README.md--setup-sources flow to configure Fireflies, Slack, or Google Drive auto-pulling--add-source flow to let the user paste a transcript, notes, or other contentIf style config exists and source material is available, proceed with generation:
~/.config/casper/linkedin-style.md${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/source-material/ (excluding README.md)${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/references/prompt-template.md| Flag | Behavior |
|---|---|
| (none) | Normal generation flow |
--setup |
Re-run style setup, overwrite existing config |
--setup-sources |
Configure which Fireflies, Slack, and Drive sources to pull from |
--refresh |
Pull fresh source material from configured integrations, then generate |
--view-style |
Read and display ~/.config/casper/linkedin-style.md |
--view-sources |
List and summarize all files in source-material/ |
--add-source |
Prompt user to paste new content, save as new .md file in source-material/ |
--setup-sourcesInteractive setup for automatic source pulling. Read references/source-integrations.md for full details.
user_email in the configFIREFLIES_API_KEY env var)SLACK_BOT_TOKEN env var)FIREFLIES_API_KEY in your environment. Get your API key from https://app.fireflies.ai/api"SLACK_BOT_TOKEN in your environment. Create a Slack app at https://api.slack.com/apps"~/.config/casper/linkedin-sources.md/casper:generate-linkedin-post --refresh to pull fresh content."--refreshPull fresh source material from all configured integrations before generating posts. Read references/source-integrations.md for the full integration workflow.
Summary of the flow:
~/.config/casper/linkedin-sources.md — if missing, run --setup-sources firstpython ${CLAUDE_PLUGIN_ROOT}/skills/transcript-search/scripts/fireflies_transcript_search.py "{term}" --days-back {N} --content --json
user_email (from source config) appears in the transcript's participants arraypython ${CLAUDE_PLUGIN_ROOT}/skills/slack-automation/scripts/slack_search.py read "{channel}" --days {N}python ${CLAUDE_PLUGIN_ROOT}/skills/google-workspace/scripts/gdrive_search.py files "{term}" --modified-days {N} --jsonsource-material/:
fireflies-{YYYY-MM-DD}-{title-slug}.mdslack-{channel}-{YYYY-MM-DD}.mdgdrive-{title-slug}-{YYYY-MM-DD}.md--view-styleRead ~/.config/casper/linkedin-style.md and display it. If it doesn't exist, say "No style profile found. Run /casper:generate-linkedin-post --setup to create one."
--view-sourcesList all .md files in ${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/source-material/ (excluding README.md). For each file, show the filename and a 1-line summary of its contents.
--add-sourceteam-standup-jan-2025)"${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/source-material/[name].md| File | When to Read |
|---|---|
references/prompt-template.md |
Every generation run — contains voice rules, few-shot examples, confidentiality rules |
references/source-integrations.md |
When running --refresh or --setup-sources — contains script paths, arguments, output conversion |
references/style-setup.md |
When running --setup — contains analysis framework for style profiling |
source-material/*.md |
Every generation run — raw content to extract post ideas from |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
linkedin-post-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added linkedin-post-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend linkedin-post-generator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in linkedin-post-generator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: linkedin-post-generator is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added linkedin-post-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
linkedin-post-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
linkedin-post-generator is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
linkedin-post-generator has been reliable in day-to-day use. Documentation quality is above average for community skills.
Registry listing for linkedin-post-generator matched our evaluation — installs cleanly and behaves as described in the markdown.
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