Track all identified/contacted people across strategies. CSV-backed contact database with dedup by LinkedIn URL or email. Prevents duplicate outreach when running strategies on a recurring cadence.
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Track all identified/contacted people across strategies. CSV-backed contact database with dedup by LinkedIn URL or email. Prevents duplicate outreach when running strategies on a recurring cadence.
# Check if contacts are already cached
python3 skills/contact-cache/scripts/cache.py check --linkedin-urls "https://linkedin.com/in/person1,https://linkedin.com/in/person2"
python3 skills/contact-cache/scripts/cache.py check --emails "john@example.com,jane@example.com"
# Add a single contact
python3 skills/contact-cache/scripts/cache.py add --name "John Smith" --linkedin-url "https://linkedin.com/in/johnsmith" --email "john@example.com" --company "Acme Corp" --title "VP Finance" --strategy "2A-hiring-signal"
# Bulk import from CSV
python3 skills/contact-cache/scripts/cache.py add --csv /path/to/leads.csv --strategy "2A-hiring-signal"
# Update a contact's status
python3 skills/contact-cache/scripts/cache.py update --linkedin-url "https://linkedin.com/in/johnsmith" --status contacted --notes "Sent intro email 2026-02-24"
# Export the full cache
python3 skills/contact-cache/scripts/cache.py export --format csv
python3 skills/contact-cache/scripts/cache.py export --format json
python3 skills/contact-cache/scripts/cache.py export --status contacted
python3 skills/contact-cache/scripts/cache.py export --strategy "2A-hiring-signal"
# Print summary statistics
python3 skills/contact-cache/scripts/cache.py stats
Contacts are stored in skills/contact-cache/data/contacts.csv. The file is auto-created on first use.
Dedup is by LinkedIn URL (preferred) or email. Both are normalized and hashed (SHA256, first 16 chars) to produce a stable contact_id.
new, qualified, contacted, replied, meeting_booked, converted, not_interested
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概要と使いどころ
Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.
日本語の概要は準備中です。原文の説明を表示しています。
For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.
日本語の概要は準備中です。原文の説明を表示しています。
The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.
日本語の概要は準備中です。原文の説明を表示しています。
Turn a brand's facts, a campaign brief and the product into a one-minute Meta ad strategy with its reasoning — goal, audience, objective and placements, budget split, how many ads and how different they must be (generate 3x so the user can choose), the test frame, the success metric, and safety rules for the user to accept. Decides what launch-meta-ad-campaign then executes, and re-reads the strategy after a deep check to show which assumption changed. Use it after intake and before any creative is generated or any campaign is built.
日本語の概要は準備中です。原文の説明を表示しています。