Can I vibecode Profound?

Build me a local AI answer engine visibility tracker for one brand. Requirements:

- Node 22, TypeScript, SQLite via better-sqlite3, a CLI, and a plain server-rendered
  dashboard. Local only, no accounts, no telemetry.
- brand.json holds my brand name, aliases, domain, and competitor names. prompts.json
  holds up to 40 buyer questions.
- `track run` sends every prompt through OpenAI, Anthropic, Gemini, and Perplexity with
  each provider's web search or grounding tool enabled. Keys live in .env.
- Store one immutable row per run, prompt, and provider: raw answer, cited URLs, model
  id, latency, and error text. Never overwrite an existing run.
- Cap concurrency at 3 per provider, retry twice on 429 and 5xx with backoff, and keep
  failed cells visible in the report instead of dropping them.
- Detect brand and competitor mentions case-insensitively using the alias list, and
  record the first-mention character offset as a crude prominence proxy.
- Score the sentiment of each brand mention in one cheap structured pass over stored
  answers, after the run, never inline.
- Normalize citations to hostname plus canonical path, strip tracking parameters, then
  compute owned-domain citation share and a top 25 sources table.
- `track serve` renders visibility per provider over time, share of voice against each
  competitor, the sources table, and the prompts where competitors appear and I do not.
- `track crawlers --log access.log` parses server logs for GPTBot, OAI-SearchBot,
  ClaudeBot, PerplexityBot, Google-Extended and friends, plus referral hits from
  chatgpt.com and perplexity.ai, and reports which URLs they touched.
- Keep the bot user agent list in an editable JSON file. Log lines matching nothing get
  counted as unknown agents, not silently discarded.
- `track export` writes runs, mentions, and citations to CSV.
- Fixture tests for mention detection, URL normalization, and log parsing.
- Out of scope: real consumer surface answers, prompt volume estimates, content
  generation agents, teams, and hosted scheduling. Do not scrape the consumer web UIs.
- README: setup, per-run cost estimate, a cron line for daily runs, and a plain note
  that API answers only approximate what users actually see.