Goose Skills is a library of workflows and data APIs that lets coding agents handle growth and go-to-market work such as advertising, social media, content, SEO, lead generation, and customer research. It is intended for teams using Claude Code, Cursor, Codex, and similar agents. The catalogue entries are its reusable skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add gooseworks-ai/goose-skills --skill contact-cachegit clone --depth 1 https://github.com/gooseworks-ai/goose-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gooseworks-ai/goose-skills/contact-cache)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/contact-cache"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/contact-cache/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/contact-cache"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/contact-cache.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00038 | $0.00475 |
| Opus 5 | $0.00019 | $0.00237 |
| Sonnet 5 | $0.00008 | $0.00095 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
contact-cache scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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
# 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 "[email protected],[email protected]"
# Add a single contact
python3 skills/contact-cache/scripts/cache.py add --name "John Smith" --linkedin-url "https://linkedin.com/in/johnsmith" --email "[email protected]" --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
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 49 lines · 38 tokens per session scan A 2ac0798d1316
contact-cache is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,202 stars, last pushed 10d ago), licensed MIT. It adds 38 tokens to every session and 475 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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