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 KunanonJ/ai-skills-hub --skill aside-site-linkedingit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote 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/kunanonj/ai-skills-hub/aside-site-linkedin)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/aside-site-linkedin"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/aside-site-linkedin/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/kunanonj/ai-skills-hub/aside-site-linkedin"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/aside-site-linkedin.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 | $0.00015 | $0.03727 |
| Opus 5 | $0.00008 | $0.01863 |
| Sonnet 5 | $0.00003 | $0.00745 |
| Haiku 4.5 | $0.00002 | $0.00373 |
Grade A, and why
aside-site-linkedin scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 424 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use the linkedin global in the REPL tool. It allows you to control the LinkedIn website with API interface- no tab open needed.
Quick Reference
// Current viewer profile. Response shape is Voyager-native:
// { data: { plainId, '*miniProfile' }, included: [MiniProfile, ...] }
const me = await linkedin.getMe();
const miniProfile = me.included?.find((item) => item.$type === 'com.linkedin.voyager.identity.shared.MiniProfile');
console.log(miniProfile?.publicIdentifier, me.data?.plainId);
// Public profile lookup (public identifier or full profile URL)
const profile = await linkedin.getProfile('johndoe');
console.log(profile.fullName, profile.headline);
// Search people / companies
const people = await linkedin.searchPeople('software engineer at openai');
console.log(people.results.map((item) => item.title));
const companies = await linkedin.searchCompanies('openai');
console.log(companies.results.map((item) => item.title));
// Company / job / posts
const company = await linkedin.getCompany('microsoft');
const job = await linkedin.getJob('4242424242');
const posts = await linkedin.getUserPosts('johndoe');
// Messaging — inbox + conversation history (paginate by timestamp, not offset)
const inbox = await linkedin.getInbox();
const convo = await linkedin.getConversation(inbox.conversations[0].threadId);
// Reply to an existing thread
await linkedin.sendMessage({ threadId: inbox.conversations[0].threadId, text: 'Hey!' });
// Start a new thread (accepts public identifiers OR profile URNs)
await linkedin.sendMessage({ recipients: ['johndoe'], text: 'Hi, nice to meet you.' });
// Connection requests
await linkedin.sendInvitation({ identifier: 'johndoe', customMessage: 'Would love to connect.' });
const received = await linkedin.getReceivedInvitations();
if (received.invitations[0]) {
await linkedin.acceptInvitation(received.invitations[0]);
// or: linkedin.ignoreInvitation(received.invitations[0])
}
// Withdrawing a previously-sent invitation (URN captured from sendInvitation's response)
// await linkedin.withdrawInvitation(invitationUrn);
// If LinkedIn rotates the session cookies:
linkedin.invalidateCache();
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.
- 9d ago First seen · 424 lines · 15 tokens per session scan A 89035b54c156
aside-site-linkedin is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed 2d ago), licensed MIT. It adds 15 tokens to every session and 3,727 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 2026-09-03.
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Trigger: SDD research, external evidence, source-backed research. Produce auditable evidence for a selected research lane.
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