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-voyager-sdui-methodologygit 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-voyager-sdui-methodology)<a href="https://agentmods.dev/skills/samihalawa/linkedin-godmode-plugin/linkedin-voyager-sdui-methodology"><img src="https://agentmods.dev/badge/skills/samihalawa/linkedin-godmode-plugin/linkedin-voyager-sdui-methodology/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/samihalawa/linkedin-godmode-plugin/linkedin-voyager-sdui-methodology"><img src="https://agentmods.dev/badge/skills/samihalawa/linkedin-godmode-plugin/linkedin-voyager-sdui-methodology.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 | $0.00049 | $0.00186 |
| Opus 5 | $0.00024 | $0.00093 |
| Sonnet 5 | $0.00010 | $0.00037 |
| Haiku 4.5 | $0.00005 | $0.00019 |
Grade A, and why
linkedin-voyager-sdui-methodology 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 11d 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
Voyager and SDUI methodology
Treat Voyager and SDUI as observed private web protocols, not stable APIs.
- Capture the exact current UI flow.
- Group calls by causal order and identify the smallest request that performs or verifies the operation.
- Preserve opaque IDs exactly as captured for that session; never promote them into tool names or source constants.
- Replay reads before writes when possible.
- For SDUI, preserve prerequisite state/component calls if the final submit depends on them.
- Verify writes with a fresh independent read or UI state.
Read references/protocol-notes.md before interpreting opaque IDs or nested form state.
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.
- 11d ago First seen · 18 lines · 49 tokens per session scan A d4be07ea8c96
linkedin-voyager-sdui-methodology is a skill published in the GitHub repository samihalawa/linkedin-godmode-plugin (0 stars, last pushed 23d ago), licensed MIT. It adds 49 tokens to every session and 186 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.
Other skills, from other repositories
mk:agent-browser
Browser automation CLI for AI agents using agent-browser. Use for navigating websites, clicking/filling pages, screenshots, data extraction, web app testing, exploratory QA, dogfooding, Electron apps, Slack automation, Vercel Sandbox browser runs, AWS AgentCore cloud browsers, auth-heavy flows, and long autonomous…
browser-use
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work.
opencli-autofix
Automatically fix broken OpenCLI adapters when commands fail. Load this skill when an opencli command fails — it guides you through collecting a trace artifact, patching the adapter, retrying, and filing an upstream GitHub issue after a verified fix. Works with any AI agent.
opencli-sitemap-author
Use when creating or maintaining OpenCLI site sitemaps: agent-facing navigation, page-state, action, workflow, API-reference, pitfall, and fallback knowledge for a website. Use after browser exploration discovers durable site context, when a sitemap is stale, or when promoting local site knowledge into the repo.
opencli-browser-sitemap
Use when driving a website with opencli browser and sitemap context is available, requested, or needed to avoid blind navigation. Guides agents to consume site sitemap files lazily, choose adapter/browser fallback paths, resume from state signatures, and mark stale sitemap entries without trusting them over live…
pinchtab
Use this skill when a task needs browser automation through PinchTab: open a website, inspect interactive elements, click through flows, fill out forms, scrape page text, reuse a dedicated automation profile with user approval, export screenshots or PDFs, manage multiple browser instances, or fall back to the HTTP API…