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 styfinity/linkedin-engine --skill linkedin-connection-notegit clone --depth 1 https://github.com/styfinity/linkedin-engineWrote 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/styfinity/linkedin-engine/linkedin-connection-note)<a href="https://agentmods.dev/skills/styfinity/linkedin-engine/linkedin-connection-note"><img src="https://agentmods.dev/badge/skills/styfinity/linkedin-engine/linkedin-connection-note/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/styfinity/linkedin-engine/linkedin-connection-note"><img src="https://agentmods.dev/badge/skills/styfinity/linkedin-engine/linkedin-connection-note.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 | $0.00042 | $0.00465 |
| Opus 5.5 | $0.00017 | $0.00186 |
| Sonnet 5.5 | $0.00008 | $0.00093 |
| Haiku 4.5 | $0.00004 | $0.00047 |
Grade A, and why
linkedin-connection-note 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 2mo 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
LinkedIn Connection Note
A connection note is not a pitch. It earns the accept by referencing one real, specific detail. This skill writes two short variants so the operator can pick.
Inputs
- The target profile (name, role, company) and how you found them, plus the one real hook (a post they wrote, a comment, a mutual, a signal): $ARGUMENTS
- The brief (persona tone, pains, voice) loads automatically.
Do this
- Pull the single most specific real hook from the input. If there is no real hook, say so and ask for one. Do not invent it.
- Write Variant A: a connection note that opens on that exact detail. Under 200 characters. No pitch.
- Write Variant B: a different angle on the same hook, or a second real detail. Under 200 characters. No pitch.
- Count the characters in each. If either is over 200, cut it down and recount.
Output
Variant A and Variant B, each on its own line, with the exact character count in brackets after it (for example: [184 chars]). One line below: each is draft only, pick one, then approve before it goes out.
Rules
- Under 200 characters, counted and shown. No exceptions.
- No pitch, no ask, no offer. The note buys the accept, nothing more.
- No "I came across your profile", no "hope you're well", no exclamation marks.
- No em-dashes. Use a comma, a period, or " - ".
- Reads like one peer messaging another about a real thing they noticed.
- Draft only. Claude drafts, the operator approves and sends.
- Sending happens only through the connected opt-in CLI/MCP layer wired to your own LinkedIn session or provider key, and is hard-capped at 20 actions per day on new accounts. This skill never sends.
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.
- 2mo ago First seen · 32 lines · 42 tokens per session scan A 8d3c535fc3ed
linkedin-connection-note is a skill published in the GitHub repository styfinity/linkedin-engine (9 stars, last pushed 4mo ago), licensed MIT. It adds 42 tokens to every session and 465 once invoked, about $0.0002 per session on Opus 5.5. 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.
linkedin-connection-note compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| linkedin-connection-notestyfinity/linkedin-engine | Skill | 9 | 4mo ago | MIT | A | 42 | Claude Code |
| LinkedIn Automationclaude-office-skills/skills | Skill | 567 | 9mo ago | MIT | A | 19 | Claude Code, Codex |
| linkedin-carouselsericrisco/rsc-harness | Skill | 529 | 4d ago | MIT | A | 91 | Claude Code, Codex |
| deepline-ads-audiencesgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 133 | Claude Code, Codex |
| deepline-analyticsgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 115 | Claude Code |
| deepline-enginegetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 43 | Claude Code, Codex |
| deepline-gtmgetaero-io/gtm-eng-skills | Skill | 73 | yesterday | MIT | A | 332 | Claude Code, Codex |