LinkedIn Post Generator

Generate LinkedIn posts from shared source material, written in each user's personal style.

How It Works

• Personal style profile — stored locally at ~/.config/casper/linkedin-style.md (never committed)

• Source config — stored locally at ~/.config/casper/linkedin-sources.md (never committed)

• Shared source material — meeting transcripts, Slack dumps, docs in source-material/

• Prompt template — extraction rules, voice guidelines, few-shot examples in references/prompt-template.md

First Run: Style Setup

Check if ~/.config/casper/linkedin-style.md exists.

If it does NOT exist, run the style setup flow:

• Say: "Welcome to the LinkedIn Post Generator! Before we start, I need to understand your writing style."

• Say: "Share 3 LinkedIn posts that match the style you want. You can either paste the post links (e.g. https://linkedin.com/posts/... ) or paste the text directly."

• Wait for the user to provide 3 posts

• If the user provides LinkedIn URLs, fetch the post content using the apify-scrapers skill: 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.

• Analyze the posts for: tone, sentence length, vocabulary, formatting habits, hook style, CTA style, use of questions, paragraph length, overall energy

• Create ~/.config/casper/ directory if it doesn't exist

• Save the analysis to ~/.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]

• Confirm: "Got it! Your style profile is saved. You can update it anytime with /casper:generate-linkedin-post --setup "

First Run: Source Material Check

After style setup completes (or if style exists but source-material/ is empty), check for source material:

• Check if source-material/ contains any .md files besides README.md

• If empty, guide the user:

• Say: "You don't have any source material yet. I need content to generate posts from — meeting transcripts, notes, Slack conversations, etc."

• Present options:

• "Connect integrations" — run the --setup-sources flow to configure Fireflies, Slack, or Google Drive auto-pulling

• "Paste something manually" — run the --add-source flow to let the user paste a transcript, notes, or other content

• Wait for user choice and proceed with the selected flow

• If source material exists, proceed with generation

Normal Run: Post Generation

If style config exists and source material is available, proceed with generation:

• Read ~/.config/casper/linkedin-style.md

• Read ALL files in ${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/source-material/ (excluding README.md)

• Read ${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/references/prompt-template.md

• Apply the confidentiality rules from the prompt template (no financials, no client names, no pipeline, no team member names)

• Generate 2-4 post options based on the source material, written in the user's personal style

• Present them in a clean, copy-paste-ready format

Flags

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/

Flag Details

--setup-sources

Interactive setup for automatic source pulling. Read references/source-integrations.md for full details.

• Ask: "What's your work email address? This is used to filter transcripts to only meetings you attended."

• Save as user_email in the config

• Ask: "Which sources do you want to connect?" Present options:

• Fireflies.ai — pulls meeting transcripts (needs FIREFLIES_API_KEY env var)

• Slack — pulls messages from channels (needs SLACK_BOT_TOKEN env var)

• Google Drive — pulls docs and transcripts (needs OAuth setup via google-workspace skill)

• For each selected source, check if the required env var / credentials exist. If missing, provide setup instructions:

• Fireflies: "Set FIREFLIES_API_KEY in your environment. Get your API key from https://app.fireflies.ai/api"

• Slack: "Set SLACK_BOT_TOKEN in your environment. Create a Slack app at https://api.slack.com/apps"

• Google Drive: "Run the google-workspace skill setup to configure OAuth."

• For each enabled source, gather configuration:

• Fireflies: search terms (or leave empty for all recent) and days_back

• Slack: which channels to pull from — list available channels if possible, otherwise ask the user

• Google Drive: search terms, days_back

• Save to ~/.config/casper/linkedin-sources.md

• Confirm: "Source config saved. Run /casper:generate-linkedin-post --refresh to pull fresh content."

--refresh

Pull fresh source material from all configured integrations before generating posts. Read references/source-integrations.md for the full integration workflow.

Summary of the flow:

• Read ~/.config/casper/linkedin-sources.md — if missing, run --setup-sources first

• For each enabled source, call the existing Casper skill scripts:

• Fireflies: python ${CLAUDE_PLUGIN_ROOT}/skills/transcript-search/scripts/fireflies_transcript_search.py "{term}" --days-back {N} --content --json

• After fetching, filter results to only transcripts where user_email (from source config) appears in the transcript's participants array

• Slack: python ${CLAUDE_PLUGIN_ROOT}/skills/slack-automation/scripts/slack_search.py read "{channel}" --days {N}

• Google Drive: python ${CLAUDE_PLUGIN_ROOT}/skills/google-workspace/scripts/gdrive_search.py files "{term}" --modified-days {N} --json

• Convert JSON output to clean markdown and save to source-material/ :

• Fireflies: fireflies-{YYYY-MM-DD}-{title-slug}.md

• Slack: slack-{channel}-{YYYY-MM-DD}.md

• Google Drive: gdrive-{title-slug}-{YYYY-MM-DD}.md

• Proceed with normal generation

--view-style

Read ~/.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-sources

List 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-source

• Ask: "Paste the content you want to add as source material (meeting transcript, Slack dump, notes, etc.)"

• Ask: "What should I name this source file? (e.g., team-standup-jan-2025 )"

• Save as ${CLAUDE_PLUGIN_ROOT}/skills/linkedin-post-generator/source-material/[name].md

• Confirm: "Source material saved. It will be included in future post generation."

Reference Files

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