contact-cache
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.
Best use case
contact-cache is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using contact-cache should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/contact-cache/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How contact-cache Compares
| Feature / Agent | contact-cache | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Contact Cache 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. ## Usage ```bash # 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 ``` ## Data 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`. ## Valid Statuses `new`, `qualified`, `contacted`, `replied`, `meeting_booked`, `converted`, `not_interested`
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