Track platforms only through BeatBrowser and BeatAPI

.changeset/ai-platform-reports.md

@@ -0,0 +1,6 @@
+---
+"@workspace/web": patch
+"@workspace/lib": patch
+---
+
+Add separate Bing and Google AI report imports with comparable history and guide users through their first monitoring run.

.changeset/beatapi-monitoring-platforms.md

@@ -0,0 +1,8 @@
+---
+"@workspace/web": patch
+"@workspace/lib": patch
+"@workspace/config": patch
+"@workspace/worker": patch
+---
+
+Track platforms only through BeatBrowser or BeatAPI with a default model per platform, remove product analytics, and reorder the sidebar into SEO, GEO and Optimize.

AGENTS.md

@@ -50,7 +50,7 @@ Before handing work back or opening a PR, run `pnpm lint` and get it passing; CI
 
 ## Environment
 
-`.env` must exist at **both** the repo root and `apps/web/.env` (Vite reads its project root; the worker reads `apps/web/.env` via `--env-file`). Minimum for the local workspace: `DATABASE_URL`, `BETTER_AUTH_SECRET`, `BEAT_GEO_ENCRYPTION_KEY` (`openssl rand -base64 32`), `APP_URL`, `DISABLE_TELEMETRY=1`, and `SCRAPE_TARGETS` plus the keys of the providers it names. Local workspaces establish a private owner/session automatically and expose no registration, login, password, team or organization-switching UI. Local setup remains accessible without a research key; industry starter questions and browser monitoring need no research provider. AI-assisted onboarding and Opportunities require a research provider: `BEATAPI_API_KEY` plus `BEATAPI_RESEARCH_MODEL`, or one direct LLM key (`OPENAI_API_KEY`, `OPENROUTER_API_KEY`, `ANTHROPIC_API_KEY`, or `MISTRAL_API_KEY`) for onboarding and the Opportunities report. For UI-only work, `SCRAPE_TARGETS=stub:stub` and `ONBOARDING_LLM_TARGET=stub:stub` need no keys at all.
+`.env` must exist at **both** the repo root and `apps/web/.env` (Vite reads its project root; the worker reads `apps/web/.env` via `--env-file`). Minimum for the local workspace: `DATABASE_URL`, `BETTER_AUTH_SECRET`, `BEAT_GEO_ENCRYPTION_KEY` (`openssl rand -base64 32`), `APP_URL` and `SCRAPE_TARGETS` plus the keys of the providers it names. Local workspaces establish a private owner/session automatically and expose no registration, login, password, team or organization-switching UI. Local setup remains accessible without a research key; industry starter questions and browser monitoring need no research provider. AI-assisted onboarding and Opportunities require `BEATAPI_API_KEY` plus `BEATAPI_RESEARCH_MODEL`. Monitoring reaches platforms only through BeatBrowser (`beat-browser`) or BeatAPI (`beatapi`); see `docs/providers.md`. For UI-only work, `SCRAPE_TARGETS=stub:stub` and `ONBOARDING_LLM_TARGET=stub:stub` need no keys at all.
 
 ## Git workflow
 

apps/web/package.json

@@ -49,7 +49,6 @@
 		"lucide-react": "^1.51.0",
 		"pg": "^8.23.1",
 		"pg-boss": "^12.36.0",
-		"posthog-js": "^1.435.8",
 		"react": "^19.3.0",
 		"react-dom": "^19.3.0",
 		"react-icons": "^5.7.0",

apps/web/src/components/__tests__/response-markdown.test.tsx

@@ -1,92 +1,30 @@
 /**
- * Every provider stores its answers in a different shape, and each one reaches
- * the prompt detail page through `extractTextContent` before it is rendered.
- * A provider whose extraction hands back flattened text or glued-together
- * blocks looks identical to a broken renderer from the page's side, so the two
- * halves are checked together here rather than in isolation.
- *
- * The shapes mirror the fixtures in each provider's own tests in
- * `packages/lib/src/providers/registry`.
+ * Stored answers reach the prompt detail page through `extractTextContent`
+ * before they are rendered, so extraction and rendering are checked together:
+ * flattened text looks identical to a broken renderer from the page's side.
  */
 import { extractTextContent } from "@workspace/lib/text-extraction";
 import { renderToStaticMarkup } from "react-dom/server";
 import { describe, expect, it } from "vitest";
 import { ResponseMarkdown } from "@/components/response-markdown";
 
 const PROSE = "Here are the **top** trackers:";
-const TABLE = "| Tool | Price |\n| --- | --- |\n| Profound | $99 |";
+const TABLE = "| Tool | Price |\n| --- | --- |\n| Example Tracker | $99 |";
 const ANSWER = `${PROSE}\n\n${TABLE}`;
 
 const render = (rawOutput: unknown, provider: string) =>
 	renderToStaticMarkup(<ResponseMarkdown>{extractTextContent(rawOutput, provider)}</ResponseMarkdown>);
 
-/** One answer, one shape per provider surface. */
 const SURFACES: [name: string, provider: string, rawOutput: unknown][] = [
-	["openai-api", "openai-api", { output: [{ type: "message", content: [{ type: "output_text", text: ANSWER }] }] }],
-	["anthropic-api", "anthropic-api", { content: [{ type: "text", text: ANSWER }] }],
-	["mistral-api", "mistral-api", { outputs: [{ content: [{ type: "text", text: ANSWER }] }] }],
-	["openrouter", "openrouter", { choices: [{ message: { content: ANSWER } }] }],
-	["olostep", "olostep", { json_content: JSON.stringify({ result: { markdown_content: ANSWER } }) }],
-	["brightdata chatbot", "brightdata", [{ answer_text_markdown: ANSWER, answer_text: "flattened" }]],
-	["brightdata AI Overview", "brightdata", [{ ai_overview: { markdown: ANSWER } }]],
-	["oxylabs ChatGPT", "oxylabs", { results: [{ content: { markdown_text: ANSWER } }] }],
-	["oxylabs Perplexity", "oxylabs", { results: [{ content: { answer_results_md: ANSWER } }] }],
-	["cloro chatbot", "cloro", { markdown: ANSWER, text: "flattened" }],
-	["cloro AI Overview", "cloro", { aioverview: { markdown: ANSWER, text: "flattened" } }],
-	["dataforseo scraper", "dataforseo", { tasks: [{ result: [{ markdown: ANSWER, sources: [] }] }] }],
-	[
-		"dataforseo LLM Responses",
-		"dataforseo",
-		{ tasks: [{ result: [{ items: [{ type: "message", sections: [{ type: "text", text: ANSWER }] }] }] }] },
-	],
-	[
-		"dataforseo AI Overview",
-		"dataforseo",
-		{ tasks: [{ result: [{ items: [{ type: "ai_overview", markdown: ANSWER }] }] }] },
-	],
-	// Rows written before the provider column existed dispatch on the model.
-	[
-		"legacy row without a provider",
-		"chatgpt",
-		{ output: [{ type: "message", content: [{ type: "output_text", text: ANSWER }] }] },
-	],
+	["BeatBrowser observation", "beat-browser", { status: "completed", answer: ANSWER, citations: [] }],
+	["BeatAPI answer", "beatapi", { choices: [{ finish_reason: "stop", message: { content: ANSWER } }] }],
 ];
 
 describe("answer rendering across providers", () => {
-	it.each(SURFACES)("renders %s answers as markdown", (_name, provider, rawOutput) => {
+	it.each(SURFACES)("renders %s as markdown", (_name, provider, rawOutput) => {
 		const html = render(rawOutput, provider);
 		expect(html).toContain("<table>");
 		expect(html).toContain("<strong>top</strong>");
-		expect(html).not.toContain("flattened");
-	});
-
-	/**
-	 * These three surfaces arrive as a list of blocks rather than one string.
-	 * Joined with a single newline they render as one run-on paragraph, which
-	 * is what the extraction's blank-line join exists to prevent.
-	 */
-	it.each([
-		[
-			"brightdata AI Overview",
-			"brightdata",
-			[{ ai_overview: { texts: [{ snippet: "First." }, { snippet: "Second." }] } }],
-		],
-		[
-			"dataforseo scraper items",
-			"dataforseo",
-			{ tasks: [{ result: [{ sources: [], items: [{ markdown: "First." }, { markdown: "Second." }] }] }] },
-		],
-		[
-			"oxylabs AI Overview",
-			"oxylabs",
-			{
-				results: [
-					{ content: { ai_overviews: [{ answer_text: [{ fragments: [{ text: "First." }, { text: "Second." }] }] }] } },
-				],
-			},
-		],
-	])("keeps %s blocks as separate paragraphs", (_name, provider, rawOutput) => {
-		expect(render(rawOutput, provider).match(/<p>/g)).toHaveLength(2);
 	});
 
 	it("does not load relative or protocol-relative images", () => {