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 XyrusCode/ai-sync --skill automategit clone --depth 1 https://github.com/XyrusCode/ai-syncWrote 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/xyruscode/ai-sync/automate)<a href="https://agentmods.dev/skills/xyruscode/ai-sync/automate"><img src="https://agentmods.dev/badge/skills/xyruscode/ai-sync/automate/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/xyruscode/ai-sync/automate"><img src="https://agentmods.dev/badge/skills/xyruscode/ai-sync/automate.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 | $0.00012 | $0.08125 |
| Opus 5.5 | $0.00005 | $0.03250 |
| Sonnet 5.5 | $0.00002 | $0.01625 |
| Haiku 4.5 | $0.00001 | $0.00813 |
Grade A, and why
automate 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.
This is a copy
95% identical to automate — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 378 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Automation (Interactive)
Use this skill when the user explicitly wants to make, build, set up, or create a new Cursor Automation — for example "create a Cursor automation", "open the Automations editor with this draft", or "set up a scheduled Cursor agent".
Disambiguation. "Automation" in a user workspace can mean many things (.github/workflows, CI pipelines, scheduled jobs, scripts, dbt, browser automation, shell scripts, workflow engines). Do not assume generic phrases like "automate this", "help me automate my deploys", or "make an automation" mean Cursor Automation. Route to the named surface when the user mentions one, use normal repo/product exploration when the context points elsewhere, or ask a short clarifying question when the target surface is ambiguous. Start this spine only when the user explicitly asks for Cursor Automations or confirms that Cursor Automations is the intended surface.
Execution spine (every run)
- Finish-path check. First, check whether the in-app Automations editor handoff is available (see Finish availability below). If neither the Automations editor tool nor the resource opener is available, immediately say "Please use this skill in the Agents Window." and stop.
- Capture intent + proactive integration discovery. After the finish-path check passes, if the prompt is missing 2+ of {what kicks it off, what should happen, what outcome}, send one short plain-chat message asking for a 1–2 sentence description and wait. Skip when the prompt already names trigger + action + outcome. Proactively run discovery for any integration the user named or implied —
gh repo viewon cwd; Slack MCP channels; PagerDuty MCP services; Linear/Sentry MCP teams/projects. Use the results to skip questions later. - Completeness gates. Work through the trigger, tool, prompt, naming, and PCD checks below. Do not jump to a summary while required picker-backed fields are still unknown unless the user explicitly deferred them to the Automations editor.
- One consolidated question. Ask inline for whatever integration discovery couldn't resolve — trigger details, repo / channel / service when ambiguous, tools when not obvious. Default to plain-chat inline. Only escalate to
AskQuestionfor (a) the tools multi-select and (b) integration discovery candidate lists with 3+ matches. - Draft table → approval → finish handoff. Show a compact Markdown table (plain language, no YAML) recapping name / description, trigger, tools, instructions, resolved settings, and "to finish in editor". User approves, then ask whether they are ready for you to open the Automations editor so they can finish any deferred values there. When they say yes, use the finish path from the availability check.
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 · 378 lines · 12 tokens per session scan A 0a0aadc25417
automate is a skill published in the GitHub repository XyrusCode/ai-sync (2 stars, last pushed 18d ago), licensed MIT. It adds 12 tokens to every session and 8,125 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to automate, differing in 12 lines, and is treated as a copy.
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