القائمة
Fetch a URL and produce a structured summary with title, key points, and an action-oriented takeaway. Use when the user shares a link and asks for a summary, TL;DR, or "what's this about?".
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Evaluate multiple choices side-by-side based on relevant criteria, then present a comparison the user can act on. Use when the user asks to compare options, choose between alternatives, or weigh up X vs Y.
Day-of-week rotating proactive sweep — Mon=connections / Tue=routines / Wed=skills / Thu=memories / Fri=findings / Sat=cross-cutting / Sun=weekly summary. Forces outward scan instead of inward thrash. Routine-only; load this skill into a daily routine that fires AssistantAgent. Adapted from goanna's caretaker.
Use when an agent has had N consecutive quiet runs with nothing to do. Pivots to bounded inward consolidation (promote findings, refresh memory, audit asks) anchored in own data — NOT generic news summarisation. Adapted from goanna's reverie cycle. Routine-only; loaded by the routine that detects the quiet condition.
Use to track open questions you owe the user (asks) and time-bounded commitments you owe yourself (tasks). Write OPEN entries when you commit; promote to CLOSED when answered/done. Survives session compaction. Adapted from goanna's asks.md/tasks.md pattern.
Reviewer criteria for AI-generated code via with_review. Checks for security issues (injection, auth bypass, secret leakage), correctness, and project conventions. Use as criteria.skill when generating code that touches data, auth, or external systems.
Reviewer criteria for outbound email drafts via with_review. Checks tone-recipient match, professionalism, no AI tells, no placeholder leakage. Use as criteria.skill argument when reviewing email drafts before send.
| name | summarise-url |
| description | Fetch a URL and produce a structured summary with title, key points, and an action-oriented takeaway. Use when the user shares a link and asks for a summary, TL;DR, or "what's this about?". |
The user has shared a URL and wants a quick understanding without reading the whole thing.
Fetch — use browser_markdown to get the page as clean text.
Extract structure — produce a summary with:
Length-aware — if the page is very long (>3000 words):
Use UI elements where helpful:
show_alert for important caveats (paywall, opinion piece, sponsored content)offer_choices at the end: "Read in full", "Find related articles", "Save to memory"browser_markdown returns partial content, say so.