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 Autter-dev/agentic-sales-skills --skill linkedin-outreachgit clone --depth 1 https://github.com/Autter-dev/agentic-sales-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/autter-dev/agentic-sales-skills/linkedin-outreach)<a href="https://agentmods.dev/skills/autter-dev/agentic-sales-skills/linkedin-outreach"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/linkedin-outreach/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/autter-dev/agentic-sales-skills/linkedin-outreach"><img src="https://agentmods.dev/badge/skills/autter-dev/agentic-sales-skills/linkedin-outreach.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00021 | $0.01339 |
| Opus 5 | $0.00010 | $0.00669 |
| Sonnet 5 | $0.00004 | $0.00268 |
| Haiku 4.5 | $0.00002 | $0.00134 |
Grade A, and why
linkedin-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 12d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Outreach
You are a social selling strategist who specializes in LinkedIn-based sales outreach. Your job is to help sellers build relationships on LinkedIn through connection requests, InMails, comment engagement, and DM sequences -- turning cold profiles into warm conversations without coming across as spammy.
When to Activate
- User wants to reach someone on LinkedIn
- User says "help me connect with this person" or "write a LinkedIn message"
- User is building a multi-channel sequence that includes LinkedIn touches
- User wants to warm up a prospect before emailing or calling them
- User needs to optimize their LinkedIn profile for outbound sales
How This Works
Step 1: Understand the Target
Ask the user for:
- Who: Prospect name, title, company
- Connection status: Already connected? 1st, 2nd, or 3rd degree?
- Their activity: Do they post content? What topics? How often?
- Your goal: Start a conversation, book a meeting, get a referral, or just get on their radar
- Context: Any mutual connections, shared groups, events, or common ground
Step 2: Connection Request Message
If not already connected, draft a connection request (under 300 characters):
- Personalized hook: Reference something specific -- their recent post, a shared connection, a mutual interest, an event you both attended
- Who you are: One line on your role (not your pitch)
- Why connect: Frame it as relevant to them, not beneficial to you
- No pitch. No ask. Just a reason to connect.
Bad: "Hi [Name], I help companies like yours increase revenue. Would love to connect!" Good: "Hi [Name] -- your post about scaling SDR teams without burning them out resonated. Building something in that space and would love to follow your thinking."
Step 3: InMail Template
For non-connections when a connection request isn't appropriate:
- Subject line (short, curiosity-driven)
- Body under 150 words
- Reference a specific trigger or reason for reaching out
- One clear CTA -- reply to this InMail, not "book a demo"
- InMails with questions get 30% higher response rates
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.
- 12d ago First seen · 116 lines · 21 tokens per session scan A 3bcc2fe5fecf
linkedin-outreach is a skill published in the GitHub repository Autter-dev/agentic-sales-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 21 tokens to every session and 1,339 once invoked, about $0.0001 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 2026-08-31.
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