OpenHive is a runtime for groups of specialized AI agents that collaborate on long-running business processes. A persistent lead agent, called the Queen, creates and coordinates worker agents while the system manages state, recovery, observability, costs, and human oversight. The catalogue entries provide agent skills, instructions, and integrations for working with this harness.
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 aden-hive/hive --skill linkedin-automationgit clone --depth 1 https://github.com/aden-hive/hiveWrote 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/aden-hive/hive/linkedin-automation)<a href="https://agentmods.dev/skills/aden-hive/hive/linkedin-automation"><img src="https://agentmods.dev/badge/skills/aden-hive/hive/linkedin-automation/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/aden-hive/hive/linkedin-automation"><img src="https://agentmods.dev/badge/skills/aden-hive/hive/linkedin-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00099 | $0.05147 |
| Opus 5.5 | $0.00040 | $0.02059 |
| Sonnet 5.5 | $0.00020 | $0.01029 |
| Haiku 4.5 | $0.00010 | $0.00515 |
Grade A, and why
hive.linkedin-automation 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 1mo 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 — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Automation
LinkedIn is the hardest mainstream site to automate because it combines shadow DOM (#interop-outlet for messaging), strict Trusted Types CSP (silently drops innerHTML), heavy React reconciliation (injected nodes get stripped on re-render), native beforeunload draft dialogs (hang the bridge), and aggressive spam filters. Every one of those has bit us at least once. This skill documents what actually works.
Always activate browser-automation first. This skill assumes you already know about CSS-px coordinates, browser_type/browser_type_focused, and browser_shadow_query. The guidance below is LinkedIn-specific; general browser rules are there.
Rule #0: screenshot + coordinates, not selectors
LinkedIn changes class names aggressively and hides composers inside shadow roots AND iframes. Selectors break constantly. Your default strategy on every LinkedIn page should be:
browser_screenshot()— see the page visually- Pick the target's position from the image
browser_coords(image_x, image_y)→ get CSS pixelsbrowser_click_coordinate(css_x, css_y)— reaches shadow DOM, iframes, and React elements indifferentlybrowser_type(use_insert_text=True, text=...)— types into whatever is focused, including Lexical composers
If browser_evaluate(...querySelectorAll...) returns [] even once, do not try a different selector. Stop, screenshot, and click. The "what if I try .artdeco-list__item next" instinct has burned ~50 tool calls in real sessions before the agent pivoted. Don't fall into that loop.
The selectors in the table below are only for when you already know the target is in the light DOM and you want a faster path than screenshot+coord. When in doubt, default to coordinates.
Invitation manager — inline message button path is BROKEN
If the user asks to message a connection request from the invitation manager page without accepting first, the inline "Message" button opens a composer inside a nested iframe overlay (not a shadow root). The iframe's contentDocument is either cross-origin-blocked or not hydrated at access time. This path is not reliably automatable today.
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.
- 1mo ago First seen · 398 lines · 99 tokens per session scan A 0fe897aaaf17
hive.linkedin-automation is a skill published in the GitHub repository aden-hive/hive (11,122 stars, last pushed today), licensed Apache-2.0. It adds 99 tokens to every session and 5,147 once invoked, about $0.0004 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 2026-08-30.
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