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 email-draftinggit 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/email-drafting)<a href="https://agentmods.dev/skills/gooseworks-ai/goose-skills/email-drafting"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-drafting/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/email-drafting"><img src="https://agentmods.dev/badge/skills/gooseworks-ai/goose-skills/email-drafting.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 | $0.00040 | $0.03751 |
| Opus 5 | $0.00020 | $0.01876 |
| Sonnet 5 | $0.00008 | $0.00750 |
| Haiku 4.5 | $0.00004 | $0.00375 |
Grade A, and why
email-drafting 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.
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Email Drafting
Pure reasoning skill for writing cold emails. No scripts, no tools — just frameworks, patterns, and examples from real campaigns that consistently generate replies.
When to Use
Use this skill when:
- User says "write a cold email", "draft outreach", "help me with email copy", "write a sequence"
- Any task requires cold email copy — subject lines, full sequences, or individual emails
Phase 0: Intake
Collect campaign context before writing anything. Ask all questions at once, organized by category. Skip any the user has already answered.
Campaign Context
- What product/service are you selling?
- What problem does it solve? Who feels this pain most acutely?
- What's the campaign angle? (hiring signal, competitor displacement, pain-based, event-triggered, etc.)
- Is there a specific signal or trigger? (job posting, G2 review, LinkedIn engagement, funding round, etc.)
Audience
- Who is the recipient? (title, seniority, department)
- What keeps them up at night? (daily frustrations relevant to your product)
- What objections will they have? (budget, switching cost, "we already have X", timing)
Proof & Credibility
- What social proof do you have? (customer logos, case studies, metrics)
- Name 2-3 peer companies the recipient would recognize as similar to them
- Any hard metrics? (cost savings, speed improvement, % lift)
Tone & Style
- What tone fits? (casual-direct, professional-sharp, provocative, empathetic)
- Who is the sender? (founder, AE, SDR — this affects voice)
- Any brand guidelines or words to avoid?
Sequence
- How many touches? (default: 3)
- What's the desired CTA? (call, demo, reply, resource download)
- Email-only or multi-channel? (email + LinkedIn, email + phone)
Phase 1: Draft Emails
Email Structure Formula
Every cold email follows this skeleton:
Hook (1 sentence) → Evidence (1-2 sentences) → Offer (1 sentence)
Word count targets:
- Cold intro (Touch 1): 50-90 words
- Follow-up (Touch 2-3): 30-50 words
- Breakup (final touch): 20-40 words
What ships with it
1 file 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 · 361 lines · 40 tokens per session scan A 38eb9fdca792
email-drafting is a skill published in the GitHub repository gooseworks-ai/goose-skills (1,201 stars, last pushed 10d ago), licensed MIT. It adds 40 tokens to every session and 3,751 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.
Other skills, from other repositories
sequence-architect
Design a 4-6 touch outreach cadence with channels, timing, tonal arc, and branching. Use when starting a new sequence from scratch given an ICP and offer.
icebreaker
Draft 3 distinct opening messages for a specific prospect, anchored on a why-now and a why-this-person. Use when sending a high-leverage first touch where personalization is worth the time.
sequence-doctor
Audit an outreach sequence and produce a ranked fix list. Use when reply rates are low, when you want a second opinion before sending, or when rewriting a sequence from scratch.
jargon-bingo
Score sales calls, emails, or posts on a 5x5 bingo card of cliches. Mostly for fun; quietly useful for spotting jargon-heavy patterns.
prospect-twin
Build a believable persona simulation of a prospect from their LinkedIn profile, then practice outreach against them. Use when preparing for a high-stakes outreach or call, when iterating on openers, or when testing whether a pitch lands.
cringe-translator
Translate sales-jargon-laden LinkedIn messages into what the sender actually means. Mostly for fun; occasionally educational about why a message tanked.