ChatExport Need Miner: Offline Market Signal & Pain-Point Extractor

Transform offline Telegram Desktop chat exports (result.json) into quantified, quote-grounded rankings of unmet market needs with zero memory crashes and absolute source fidelity.

When to Use This Skill

Activate this skill when:

• The user provides an offline Telegram Desktop chat export (result.json or multi-file directory) and requests market research, customer problem analysis, or tool opportunity discovery.
• The user asks: "What are people in this chat struggling with?", "Find product ideas from this export", "What tools do users wish existed?", or "Mine complaints from this group".
• Analyzing multi-megabyte or gigabyte JSON dumps where standard in-memory deserialization (json.load()) risks out-of-memory (OOM) fatal crashes.
• Cross-referencing user complaints across multiple independent communities to eliminate echo-chamber noise.

Do NOT use this skill when:

• The user wants live channel scraping, continuous bot monitoring, or MTProto API automation (use dedicated online fetchers).
• Analyzing personal 1-on-1 romantic or private relationships.
• Processing generic SaaS helpdesk feeds (Zendesk, Intercom, Gong) with structured ticket schemas.

Core Mental Models & Non-Negotiable Rules

1. The 4MB Stream & Overlap Invariant (Memory Ceiling <= 8MB):

   • Telegram Desktop result.json files routinely exceed 500MB to 5GB.
   • NEVER load an entire export into memory with json.load() or fs.readFileSync().
   • Read the file in fixed 4MB chunks with a 4KB overlap tail.
   • Boundary Counting Law: A substring hit is recorded if and only if its terminus falls past the overlap boundary. This guarantees zero missed boundary-spanning phrases and strictly zero duplicate counts.

2. Cross-Chat Multiplicity Law ($U \ge 3$ Priority):

   • One user posting 50 complaints in a single chat is an anecdote; 5 distinct users posting the same complaint across 3 independent chats is a market signal.
   • Cluster rank score is calculated as: $$\text{Score} = U \times \sqrt{H}$$ where $U$ is the number of distinct chat exports containing the signal, and $H$ is the total verified keyword hits.
   • A pattern appearing in $U \ge 3$ chats always outranks a pattern confined to $U = 1$, regardless of raw hit volume.

3. Verbatim Quote Anchor & Anti-Hallucination Law:

   • Every identified need theme MUST be backed by 2 to 5 verbatim quotes with exact ISO timestamp (date) and chat identifier.
   • NEVER paraphrase a quote inside quotation marks. NEVER synthesize synthetic user statements.
   • If a hypothesized theme lacks verbatim quote support, it MUST be marked [UNCONFIRMED / NO VERBATIM EVIDENCE].

4. Bi-Lingual Case-Insensitive Seed Lexicons:

   • Russian Lexicon: не хватает, вот бы, бесит, надоело, задолбал, ищу инструмент, ищу бот, есть ли бот, есть ли сервис, посоветуйте тул, не работает, вручную, рутина, приходится руками.
   • English Lexicon: i wish, missing, annoying, frustrating, looking for a tool, is there an app, is there a bot, any alternative to, doesn't work, manually, repetitive, waste of time.
   • Custom terms may be added only when explicitly approved or provided by the user.

5. Strict Air-Gap & Zero Exfiltration:

   • The entire analysis executes locally and offline. No network requests, no external telemetry, no remote LLM proxying of raw message contents.

Named Sins & Anti-Patterns (Что категорически ЗАПРЕЩЕНО)

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