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 samihalawa/linkedin-godmode-plugin --skill linkedin-operatorgit clone --depth 1 https://github.com/samihalawa/linkedin-godmode-pluginWrote 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/samihalawa/linkedin-godmode-plugin/linkedin-operator)<a href="https://agentmods.dev/skills/samihalawa/linkedin-godmode-plugin/linkedin-operator"><img src="https://agentmods.dev/badge/skills/samihalawa/linkedin-godmode-plugin/linkedin-operator.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 | $0.00049 | $0.00312 |
| Opus 5 | $0.00024 | $0.00156 |
| Sonnet 5 | $0.00010 | $0.00062 |
| Haiku 4.5 | $0.00005 | $0.00031 |
Grade A, and why
linkedin-operator 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 7d 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 operator
- Honor the user's explicitly selected authenticated controller. If the in-app Browser is named, do not open or treat another provider session as authoritative. For plugin-managed sessions, call
browser_sessionstatus/list before opening another session. - Prefer the dedicated local profile only when no controller was selected; use Anchor or Browserbase only when requested or configured.
- Read current state with
browser_capture. Use accessible role/label/text locators before CSS/XPath. - For UI work, call
browser_navigateandbrowser_actwith explicit caller-reviewed arguments. - For private web requests, follow the capture-first method in
references/operator-method.md; never guess a mutable endpoint. - Before an account-visible change, inspect the target, execute once, and verify at the same layer. Do not infer success from a click alone.
- Never add unrequested loops, scheduling, campaign scope, challenge bypass, or cookie import/export. A caller's authorized batch may iterate through matching targets; do not invent a gate or broaden the batch. The selected controller's mandatory action-time confirmation policy still applies.
Use browser_task only when the user explicitly requests a provider AI task. Deterministic tools never need it.
What ships with it
2 files 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.
- 7d ago First seen · 17 lines · 49 tokens per session scan A 696226ff62b0
linkedin-operator is a skill published in the GitHub repository samihalawa/linkedin-godmode-plugin (0 stars, last pushed 18d ago), licensed MIT. It adds 49 tokens to every session and 312 once invoked, about $0.0002 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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