Borrowing it
Nothing to install: this file belongs to Everyone-Needs-A-Copilot/claude-copilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Everyone-Needs-A-Copilot/claude-copilot/main/.claude/skills/sales/draft-outreach/SKILL.mdgit clone --depth 1 https://github.com/Everyone-Needs-A-Copilot/claude-copilotWrote 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/everyone-needs-a-copilot/claude-copilot/draft-outreach)<a href="https://agentmods.dev/skills/everyone-needs-a-copilot/claude-copilot/draft-outreach"><img src="https://agentmods.dev/badge/skills/everyone-needs-a-copilot/claude-copilot/draft-outreach.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00052 | $0.02333 |
| Opus 5 | $0.00026 | $0.01167 |
| Sonnet 5 | $0.00010 | $0.00467 |
| Haiku 4.5 | $0.00005 | $0.00233 |
Grade A, and why
draft-outreach 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 2d 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.
This is a copy
100% identical to draft-outreach — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 441 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Draft Outreach
Research first, then draft. This skill never sends generic outreach - it always researches the prospect first to personalize the message. Works standalone with web search, supercharged when you connect your tools.
Connectors (Optional)
| Connector | What It Adds |
|---|---|
| Enrichment | Verified email, phone, background details |
| CRM | Prior relationship context, existing contacts |
| Create draft directly in your inbox |
No connectors? Web research works great. I'll output the email text for you to copy.
How It Works
+------------------------------------------------------------------+
| DRAFT OUTREACH |
| |
| Step 1: RESEARCH (always happens first) |
| - Web search (default) |
| - + Enrichment (if enrichment tools connected) |
| - + CRM (if CRM connected) |
| |
| Step 2: DRAFT (based on research) |
| - Personalized opening (from research) |
| - Relevant hook (their priorities) |
| - Clear CTA |
| |
| Step 3: DELIVER (based on connectors) |
| - Email draft (if email connected) |
| - Copy for LinkedIn (always) |
| - Output to user (always) |
+------------------------------------------------------------------+
Output Format
# Outreach Draft: [Person] @ [Company]
**Generated:** [Date] | **Research Sources:** [Web, Enrichment, CRM]
---
## Research Summary
**Target:** [Name], [Title] at [Company]
**Hook:** [Why reaching out now - the personalized angle]
**Goal:** [What you want from this outreach]
---
## Email Draft
**To:** [email if known, or "find email" note]
**Subject:** [Personalized subject line]
---
[Email body]
---
**Subject Line Alternatives:**
1. [Option 2]
2. [Option 3]
---
## LinkedIn Message (if no email)
**Connection Request (< 300 chars):**
[Short, no-pitch connection request]
**Follow-up Message (after connected):**
[Value-first message]
---
## Why This Approach
| Element | Based On |
|---------|----------|
| Opening | [Research finding that makes it personal] |
| Hook | [Their priority/pain point] |
| Proof | [Relevant customer story] |
| CTA | [Low-friction ask] |
---
## Email Draft Status
[Draft created - check ~~email]
[Email not connected - copy email above]
[No email found - use LinkedIn approach]
---
## Follow-up Sequence (Optional)
**Day 3 - Follow-up 1:**
[Short, new angle]
**Day 7 - Follow-up 2:**
[Different value prop]
**Day 14 - Break-up:**
[Final attempt]
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.
- 2d ago First seen · 441 lines · 52 tokens per session scan A eeca7158539a
draft-outreach is a skill published in the GitHub repository Everyone-Needs-A-Copilot/claude-copilot (13 stars, last pushed 2d ago), licensed MIT. It adds 52 tokens to every session and 2,333 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to draft-outreach, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
security-review
Perform a focused security review of pending git changes to identify high-confidence security vulnerabilities with real exploitation potential. Use this skill when the user asks for a security review, security audit, vulnerability scan, or wants to check pending changes on a branch for security issues before merging.…
huggingface-llm-trainer
Train or fine-tune language models with TRL or Unsloth on Hugging Face Jobs, including SFT, DPO, GRPO, reward models, and GGUF conversion. Use for cloud LLM training; use huggingface-vision-trainer for vision tasks.
memstack-development-refactor-planner
Use this skill when the user says 'refactor', 'refactoring plan', 'code cleanup', 'reduce duplication', 'simplify code', 'tech debt', 'god class', 'tight coupling', or needs to systematically improve existing code. Identifies targets, assesses risk, and builds incremental execution plans. Do NOT use for writing new…
feature-dev
Guide a feature implementation through a structured seven-phase workflow with deep codebase understanding, clarifying questions, parallel architecture design, and quality review. Use this skill when the user asks to build a new feature, add functionality, or wants a methodical approach to implementation rather than…
memstack-deployment-domain-ssl
Use this skill when the user says 'setup domain', 'configure DNS', 'SSL certificate', 'domain-ssl', 'custom domain', 'HTTPS setup', or needs to configure DNS records, SSL certificates, and custom domains for any hosting provider. Do NOT use for full deployment workflows.
memstack-product-feedback-analyzer
Use this skill when the user says 'analyze feedback', 'feedback analysis', 'what are customers asking for', or has support tickets, reviews, or survey data to categorize, score, and prioritize into actionable reports. Do NOT use for competitor analysis or market research.