Cold Outbound Optimizer
ericosiu/ai-marketing-skills
Design, analyze, and optimize cold outbound email campaigns for Instantly.
Write high-converting cold emails using structured frameworks, personalization tiers, and patterns from real campaigns.
$ npx skills add gooseworks-ai/goose-skills --skill email-drafting -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install gooseworks-ai/goose-skills email-drafting --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/outreach/capabilities/email-drafting .claude/skills/email-drafting && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "email-drafting" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-drafting into .claude/skills/email-drafting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "email-drafting", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-draftingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add gooseworks-ai/goose-skills --skill email-drafting -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install gooseworks-ai/goose-skills email-drafting --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/outreach/capabilities/email-drafting .agents/skills/email-drafting && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "email-drafting" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-drafting into .agents/skills/email-drafting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "email-drafting", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill email-drafting -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install gooseworks-ai/goose-skills email-drafting --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/outreach/capabilities/email-drafting .cursor/skills/email-drafting && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "email-drafting" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-drafting into .cursor/skills/email-drafting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "email-drafting", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/gooseworks-ai/goose-skills.git --path skills/outreach/capabilities/email-drafting--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add gooseworks-ai/goose-skills --skill email-drafting -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install gooseworks-ai/goose-skills email-drafting --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/outreach/capabilities/email-drafting .gemini/skills/email-drafting && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "email-drafting" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-drafting into .gemini/skills/email-drafting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "email-drafting", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install gooseworks-ai/goose-skills email-draftingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add gooseworks-ai/goose-skills --skill email-drafting -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/outreach/capabilities/email-drafting .github/skills/email-drafting && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "email-drafting" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-drafting into .github/skills/email-drafting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "email-drafting", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add gooseworks-ai/goose-skills --skill email-drafting -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install gooseworks-ai/goose-skills email-drafting --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/outreach/capabilities/email-drafting .opencode/skills/email-drafting && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "email-drafting" agent skill from https://github.com/gooseworks-ai/goose-skills/tree/main/skills/outreach/capabilities/email-drafting into .opencode/skills/email-drafting/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "email-drafting", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
email-draftingWrite high-converting cold emails using structured frameworks, personalization tiers, and patterns from real campaigns.
Email Drafting is an agent skill from gooseworks-ai/goose-skills. Write high-converting cold emails using structured frameworks, personalization tiers, and patterns from real campaigns. Pure reasoning skill — no scripts. Auto-loads when any task requires outreach copy.
Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.meta.json`).
It sits in Sales & Support, covering Cold outreach. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Email Drafting loads about 3.8k tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 1,999 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 1,999 words, ~3,847 tokens.
.claude/skills/email-drafting/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Pure reasoning skill for writing cold emails. No scripts, no tools — just frameworks, patterns, and examples from real campaigns that consistently generate replies.
Use this skill when:
Collect campaign context before writing anything. Ask all questions at once, organized by category. Skip any the user has already answered.
Every cold email follows this skeleton:
Hook (1 sentence) → Evidence (1-2 sentences) → Offer (1 sentence)Word count targets:
Pick the framework that matches the campaign angle:
| Framework | Structure | Best For |
|---|---|---|
| PAS | Problem → Agitate → Solve | Pain-based signals (complaint posts, operational friction) |
| BAB | Before → After → Bridge | Aspirational buyers (growth-stage, scaling companies) |
| AIDA | Attention → Interest → Desire → Action | Cold database outreach (no specific signal) |
| Signal-Proof-Ask | Signal → Proof → Soft ask | Signal-based campaigns (hiring, engagement, events) |
Choose based on campaign size and expected ROI per lead:
| Tier | What It Means | Lead Volume | Expected Reply Rate |
|---|---|---|---|
| Tier 1 (Generic) | Merge fields only ({first_name}, {company}). Same template for everyone. | 500+ leads | 1-3% |
| Tier 2 (Segment) | Industry/role-specific pain points + proof swaps. One template per segment. | 50-500 leads | 3-7% |
| Tier 3 (Deep) | Reference a specific signal (their post, comment, job posting, news). Unique per lead. | 1-50 leads | 8-20% |
8 proven patterns from real campaigns:
| # | Pattern | Example |
|---|---|---|
| 1 | Signal reference | "Before you fill that [role] role" |
| 2 | Peer framing | "What TIA members are doing with AI workers" |
| 3 | Question | "Is [Company] still [doing thing product fixes]?" |
| 4 | Replacement | "Looking for a [competitor] replacement?" |
| 5 | Data hook | "$150K agency study → $8K. 48 hours." |
| 6 | Empathy | "When [event that affected them]" |
| 7 | Direct | "[Topic] for [Company]" |
| 8 | Curiosity | "How [peer company] did [interesting thing]" |
Rules for subject lines:
| Tone | When to Use | Voice Example |
|---|---|---|
| Casual-Direct | SDR sending to peers, startup-to-startup | "Hey — saw your post. We work on the same problem." |
| Professional-Sharp | Enterprise outreach, VP+ recipients | "I wanted to reach out because [specific reason]." |
| Provocative | Competitive displacement, challenger positioning | "Your current tool is costing you more than you think." |
| Empathetic | Orphan capture, pain-based outreach | "I know switching platforms mid-cycle is brutal." |
| Touch | Timing | Purpose | Length | Notes |
|---|---|---|---|---|
| Touch 1 | Day 1 | Hook + proof + soft CTA | 50-90 words | The only email that can be longer |
| Touch 2 | Day 3-5 | New angle or asset | 30-50 words | Different proof point, not a "bump" |
| Touch 3 | Day 7-10 | Different proof point or social | 20-40 words | Shorter = better this late |
| Touch 4 | Day 14-21 | Breakup (optional) | 20-30 words | Remove pressure, leave door open |
Sequence rules:
These are non-negotiable. Every email must pass all 10:
Real emails from real campaigns. Use these as structural templates — swap product, proof, and signal for the current campaign.
Signal source: LinkedIn Jobs — company posting for role that product replaces Framework: Signal-Proof-Ask
Subject: Before you fill that {role_title} role
Hi {first_name} — I noticed you're hiring for a {role_title} at {company}. Before you finalize that hire, worth a quick look at what companies like DHL, Werner, and MODE Global are doing instead — deploying AI workers for exactly this function.
4x cheaper than a BPO equivalent. 10x the call capacity. Runs 24/7. Happy to send over a quick overview or jump on a 15-minute call if the timing is right.
Why it works: Opens with their specific hiring signal (proves relevance). Names peer companies (social proof). Quantifies the alternative (4x, 10x). Low-friction CTA.
Signal source: Industry association membership directory Framework: BAB (Before → After → Bridge)
Subject: What TIA members are doing with AI workers
Hi {first_name} — as a TIA member running a serious freight brokerage, you're probably seeing the same thing we are: the best operators are rethinking how they staff carrier-facing functions.
Companies like Werner, MODE Global, and Circle Logistics — TIA members you'd recognize — have already deployed AI workers for carrier calls, check calls, and load coordination. I wanted to reach out because HappyRobot works specifically with freight brokers at this scale.
Worth a 15-minute call to see if it's relevant for {company}?
Why it works: Peer framing ("TIA members you'd recognize") creates belonging pressure. Names real members using the product. Positions as industry-specific, not generic.
Signal source: LinkedIn Sales Navigator — engaged with competitor company page content Framework: Signal-Proof-Ask
Subject: The other side of freight AI
Hi {first_name} — I noticed you've been following the freight AI space and wanted to reach out. HappyRobot is the other side of that conversation — we're the platform 8 of the top 10 US freight brokers including DHL and Werner run for AI carrier calls.
If you're evaluating options in this space, I'd love to show you what enterprise-grade looks like. 15 minutes?
Why it works: Acknowledges their research without calling out the competitor by name in email (saves that for LinkedIn). "Other side of that conversation" is intriguing. Proof point (8 of top 10) is specific and strong.
Signal source: Same as 3a but lead left a comment (higher intent) Framework: Signal-Proof-Ask with comment reference
Subject: Re: your comment on freight AI
Hi {first_name} — I saw your comment on {competitor}'s post about {topic}. That's exactly the problem we work on. HappyRobot powers AI carrier calls for DHL, Werner, and 8 of the top 10 US freight brokers.
If you're actively looking at this, worth 15 minutes to see the other option?
Why it works: References their exact comment (Tier 3 personalization). "Actively looking at this" matches their behavior. Even shorter than 3a because higher-intent leads need less convincing.
Signal source: LinkedIn post search for pain-language keywords Framework: PAS (Problem → Agitate → Solve)
For commenters (wrote about the pain):
Hi {first_name}, saw your comment on the {source} post about {pain_topic}. "{comment_snippet}..." — that resonated.
We've been working with brokers who had the same issue. HappyRobot handles {relevant_task} so your team doesn't have to.
Worth a quick look?
For reactors (liked/reacted to pain content):
Hi {first_name}, noticed you've been following the conversation around {pain_topic} on LinkedIn.
If {company} is dealing with {specific_pain}, we might be able to help. HappyRobot automates {relevant_task} for freight brokers — no extra headcount needed.
Open to a quick chat?
Why it works: Quotes their own words back to them (strongest personalization). Empathetic tone — no hard sell. Short. The reactor version is lighter-touch because the signal is weaker.
Signal source: G2 reviews (1-star), public complaints, known competitor customers Framework: PAS
Subject: UserTesting alternatives in 2026
{first_name} — I'll keep this short. If you've run into participant quality issues with UserTesting, you're not alone. HubSpot and Glassdoor both moved to Outset after hitting the same wall.
We use Prolific-verified participants instead of a general panel. Different quality tier entirely. Worth 20 minutes to compare?
Why it works: Validates their frustration without bashing the competitor. Names companies they'd respect. Explains the "why" behind the switch (Prolific-verified participants). CTA is specific (20 minutes, comparison framing).
Signal source: Target account list, vertical-specific research Framework: AIDA
Touch 1:
{first_name} — WeightWatchers cut their per-study research cost from $150K to $8K using Outset's AI-moderated interviews. They run 3x the studies they used to, in half the time.
I put together a quick breakdown of what this could look like for {company}'s {vertical} research. Worth 20 minutes?
Touch 3 (Day 7):
Following up with something concrete — built a rough ROI model using {industry} benchmarks. Even conservative numbers show a 6-8x reduction in per-study cost.
Happy to walk through the math. 15 minutes?
Touch 5 (Day 14):
Last note from me. If research cost or speed isn't a priority right now, totally understand. But if it is — the WeightWatchers and HubSpot numbers are worth seeing.
Open to a quick benchmark call? No demo, just data.
Why it works: Leads with a specific customer story and hard numbers. Each touch adds new value (case study → ROI model → benchmark offer). Breakup touch removes pressure. CTA evolves: overview → walk-through → benchmark.
New angle (not a bump):
{first_name} — different angle from my last email. {Peer company} just published results from their first quarter using {product}: {specific metric}. Thought it might be relevant given {company}'s {situation}.
Asset-led:
Put together a one-page breakdown of {topic relevant to them}. No pitch — just data. Want me to send it over?
Social proof drop:
Quick update — {new customer} just went live with us last week. Similar setup to {company}. Happy to share what their onboarding looked like.
Breakup:
I'll keep this short — if the timing isn't right, no worries at all. But if {problem} comes back up, I'm an easy call away. Cheers.
Signal source: Outreach log — leads contacted 90+ days ago with no reply, or leads who filled the role your product replaces Framework: Signal-Proof-Ask
Hi {first_name} — we chatted about 3 months ago when you were hiring for {role}. Curious how it's going. If you're still feeling the pain on {problem}, a few things have changed on our end worth seeing.
15 minutes to catch up?
Why it works: References the original conversation and signal. Acknowledges time has passed. "A few things have changed" creates curiosity without overselling.
When delivering email drafts, use this structure:
**Subject:** [subject line]
**Personalization tier:** [1/2/3]
**Framework:** [PAS/BAB/AIDA/Signal-Proof-Ask]
**Word count:** [X words]
---
[Email body with merge fields in {curly_braces}]
---
**Merge fields used:** {first_name}, {company}, {role_title}, ...## Sequence: [Campaign Name]
**Touches:** [N]
**Personalization tier:** [1/2/3]
**Tone:** [casual-direct / professional-sharp / provocative / empathetic]
### Touch 1 — Day 1
**Subject:** [subject]
**Framework:** [framework]
[body]
### Touch 2 — Day [N]
**Subject:** Re: [original subject] OR [new subject]
**Framework:** [framework]
[body]
### Touch 3 — Day [N]
**Subject:** [subject]
[body]
---
**Merge fields:** {first_name}, {company}, ...
**Notes:** [any special instructions for the outreach tool]© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/outreach/capabilities/email-drafting of gooseworks-ai/goose-skills.
Open the folder on GitHubat commit c650c6d
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.
Email Drafting next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Email Drafting this skillgooseworks-ai/goose-skills | 1.2k | 1 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Cold Outbound Optimizerericosiu/ai-marketing-skills | 3.6k | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Prospectingcoreyhaines31/marketingskills | 54k | — | ~5k | Automated safety check: Pass | MIT | |
| Sales OsromangojiberryAI/gojiberryai-sales-os | 139 | — | ~2k | Automated safety check: Pass | MIT | |
| ProspectingCesarjoquin/Marketing-Skills | 202 | 1 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Cold Outreach Personalizeraiskilloftheweek/claude-ai-skill-of-the-week | 149 | — | ~2.6k | Automated safety check: Pass | None |
ericosiu/ai-marketing-skills
Design, analyze, and optimize cold outbound email campaigns for Instantly.
coreyhaines31/marketingskills
When the user wants to find, qualify, and build a list of prospects to reach out to, across B2B SaaS, general B2B, or local small businesses.
romangojiberryAI/gojiberryai-sales-os
A complete outbound sales department in one skill. An agent skill from romangojiberryAI/gojiberryai-sales-os.
Cesarjoquin/Marketing-Skills
When the user wants to find, qualify, and build a list of prospects to reach out to — across B2B SaaS, general B2B, or local small businesses.
aiskilloftheweek/claude-ai-skill-of-the-week
Generates hyper-personalized cold outreach messages (email, LinkedIn DM, connection request) from raw prospect research.
gmapsscraper/google-maps-agent-skills
Extract verified business email addresses from Google Maps listings.
gooseworks-ai/goose-skills
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gooseworks-ai/goose-skills
Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent.
gooseworks-ai/goose-skills
Replace an existing video's opening with a supplied clip or free kinetic text hook while retaining and verifying every original body frame, audio, captions and ending.
gooseworks-ai/goose-skills
Scrape blog posts via RSS feeds (free, no API key) with Apify fallback for JS-heavy sites.
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Find leads by scraping engagers from a competitor's top LinkedIn posts.
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Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard…
Categories
Write high-converting cold emails using structured frameworks, personalization tiers, and patterns from real campaigns. Email Drafting is an agent skill from gooseworks-ai/goose-skills. Write high-converting cold emails using structured frameworks, personalization tiers, and patterns from real campaigns.
Email Drafting fits situations like: tasks that involve Cold outreach.
Run `npx skills add gooseworks-ai/goose-skills --skill email-drafting -a claude-code`. Or copy the skill folder (skills/outreach/capabilities/email-drafting in gooseworks-ai/goose-skills) into .claude/skills/email-drafting in your project. Claude Code loads it when a task matches its description.
Run `npx skills add gooseworks-ai/goose-skills --skill email-drafting -a codex`. Or copy the skill folder (skills/outreach/capabilities/email-drafting in gooseworks-ai/goose-skills) into .agents/skills/email-drafting in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill email-drafting -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/email-drafting, .gemini/skills/email-drafting, .github/skills/email-drafting and .opencode/skills/email-drafting in your project.
SKILL.md names no scripts, command-line tools or credentials: Email Drafting is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Email Drafting is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Email Drafting: Cold Outbound Optimizer (ericosiu/ai-marketing-skills, 3.6k stars), Prospecting (coreyhaines31/marketingskills, 54k stars), Sales Os (romangojiberryAI/gojiberryai-sales-os, 139 stars) and Prospecting (Cesarjoquin/Marketing-Skills, 202 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.
Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.