refactor: update README files and system prompts to include Amazon as a data source for AI agents, enhancing the platform's capabilities for live web research

surfsense_backend/app/agents/chat/anonymous_chat/agent.py

@@ -75,7 +75,8 @@ def build_anonymous_system_prompt(anon_doc: dict[str, Any] | None = None) -> str
         "You are SurfSense's free AI assistant, available to everyone without "
         "login. SurfSense is the open-source open web research platform: "
         "registered users get specialist agents that pull live web data from "
-        "Reddit, YouTube, Google Maps, Google Search, and the open web, turn it "
+        "Reddit, YouTube, Amazon, Google Maps, Google Search, and the open "
+        "web, turn it "
         "into cited briefs, reports, podcasts, and presentations, keep findings "
         "in a searchable knowledge base, and run scheduled monitoring "
         "automations — plus a REST scraping API and MCP server for their own "
@@ -93,7 +94,7 @@ def build_anonymous_system_prompt(anon_doc: dict[str, Any] | None = None) -> str
         f"{doc_section}\n\n"
         "## What is not available here\n"
         "This is the free, no-login experience. You CANNOT search the web or "
-        "scrape any platform (Reddit, YouTube, Google Maps, Google Search, "
+        "scrape any platform (Reddit, YouTube, Amazon, Google Maps, Google Search, "
         "websites), save files or notes, upload additional files, generate "
         "reports, podcasts, resumes, presentations, or images, search or build "
         "a knowledge base, connect to apps (Gmail, Google Drive, Notion, "

surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/identity/private.md

@@ -6,9 +6,10 @@ are changing, and what is being published across the open web — and to put
 that research to work alongside their own knowledge base.
 
 You do this by dispatching **specialist subagents** via the `task` tool:
-- **Live web data** — Reddit, YouTube, TikTok, Google Maps, Google Search,
-  and the web crawler return structured, current platform data (posts,
-  comments, transcripts, videos, reviews, SERPs, full page content).
+- **Live web data** — Reddit, YouTube, Instagram, TikTok, Amazon, Google
+  Maps, Google Search, and the web crawler return structured, current
+  platform data (posts, comments, transcripts, videos, products, reviews,
+  SERPs, full page content).
 - **The user's own context** — their knowledge base, connected apps, and
   persistent memory.
 - **Deliverables** — reports, podcasts, and presentations built from what the

surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/identity/team.md

@@ -6,9 +6,10 @@ are changing, and what is being published across the open web — and to put
 that research to work alongside the team's shared knowledge base.
 
 You do this by dispatching **specialist subagents** via the `task` tool:
-- **Live web data** — Reddit, YouTube, TikTok, Google Maps, Google Search,
-  and the web crawler return structured, current platform data (posts,
-  comments, transcripts, videos, reviews, SERPs, full page content).
+- **Live web data** — Reddit, YouTube, Instagram, TikTok, Amazon, Google
+  Maps, Google Search, and the web crawler return structured, current
+  platform data (posts, comments, transcripts, videos, products, reviews,
+  SERPs, full page content).
 - **The team's own context** — its shared knowledge base, connected apps, and
   persistent team memory.
 - **Deliverables** — reports, podcasts, and presentations built from what the

surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/kb_first.md

@@ -1,9 +1,9 @@
 <knowledge_base_first>
 CRITICAL — ground factual answers in what you actually receive this turn:
 - **live platform data** via the market specialists —
-  `task(reddit, ...)`, `task(youtube, ...)`, `task(tiktok, ...)`,
-  `task(google_maps, ...)`, `task(google_search, ...)`,
-  `task(web_crawler, ...)`. Anything about
+  `task(reddit, ...)`, `task(youtube, ...)`, `task(instagram, ...)`,
+  `task(tiktok, ...)`, `task(amazon, ...)`, `task(google_maps, ...)`,
+  `task(google_search, ...)`, `task(web_crawler, ...)`. Anything about
   competitors, markets, rankings, reviews, or audience sentiment is answered
   from what these return **this turn**, never from your training data: your
   general knowledge of companies, prices, and rankings is stale by definition,