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feat(walmart): route product-review questions to marketplace specialists

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surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/identity/private.md
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@ -6,7 +6,7 @@ are changing, and what is being published across the open web — and to put
that research to work alongside their own knowledge base. that research to work alongside their own knowledge base.
You do this by dispatching **specialist subagents** via the `task` tool: You do this by dispatching **specialist subagents** via the `task` tool:
- **Live web data** — Reddit, YouTube, Instagram, TikTok, Amazon, Google - **Live web data** — Reddit, YouTube, Instagram, TikTok, Amazon, Walmart, Google
Maps, Google Search, and the web crawler return structured, current Maps, Google Search, and the web crawler return structured, current
platform data (posts, comments, transcripts, videos, products, reviews, platform data (posts, comments, transcripts, videos, products, reviews,
SERPs, full page content). SERPs, full page content).

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surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/identity/team.md
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@ -6,7 +6,7 @@ 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. that research to work alongside the team's shared knowledge base.
You do this by dispatching **specialist subagents** via the `task` tool: You do this by dispatching **specialist subagents** via the `task` tool:
- **Live web data** — Reddit, YouTube, Instagram, TikTok, Amazon, Google - **Live web data** — Reddit, YouTube, Instagram, TikTok, Amazon, Walmart, Google
Maps, Google Search, and the web crawler return structured, current Maps, Google Search, and the web crawler return structured, current
platform data (posts, comments, transcripts, videos, products, reviews, platform data (posts, comments, transcripts, videos, products, reviews,
SERPs, full page content). SERPs, full page content).

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surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/kb_first.md
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@ -2,7 +2,8 @@
CRITICAL — ground factual answers in what you actually receive this turn: CRITICAL — ground factual answers in what you actually receive this turn:
- **live platform data** via the market specialists — - **live platform data** via the market specialists —
`task(reddit, ...)`, `task(youtube, ...)`, `task(instagram, ...)`, `task(reddit, ...)`, `task(youtube, ...)`, `task(instagram, ...)`,
`task(tiktok, ...)`, `task(amazon, ...)`, `task(google_maps, ...)`, `task(tiktok, ...)`, `task(amazon, ...)`, `task(walmart, ...)`,
`task(google_maps, ...)`,
`task(google_search, ...)`, `task(web_crawler, ...)`. Anything about `task(google_search, ...)`, `task(web_crawler, ...)`. Anything about
competitors, markets, rankings, reviews, or audience sentiment is answered competitors, markets, rankings, reviews, or audience sentiment is answered
from what these return **this turn**, never from your training data: your from what these return **this turn**, never from your training data: your

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surfsense_backend/app/agents/chat/multi_agent_chat/main_agent/system_prompt/prompts/routing.md
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@ -32,7 +32,9 @@ about a brand, product, or topic is answered from the platform where they
say it — `task(reddit, …)` for community discussion and threads, say it — `task(reddit, …)` for community discussion and threads,
`task(youtube, …)` for video content, transcripts, and comment sections, `task(youtube, …)` for video content, transcripts, and comment sections,
`task(tiktok, …)` for short-form video trends by hashtag or search, `task(tiktok, …)` for short-form video trends by hashtag or search,
`task(google_maps, …)` for customer reviews of physical businesses. Web `task(google_maps, …)` for customer reviews of physical businesses,
`task(amazon, …)` / `task(walmart, …)` for product ratings and customer
reviews of retail products (Walmart pages the full review history). Web
search only finds articles *about* the conversation; the platform search only finds articles *about* the conversation; the platform
specialists return the conversation itself, structured and current. For specialists return the conversation itself, structured and current. For
competitive questions ("what are people saying about X", "how is Y competitive questions ("what are people saying about X", "how is Y