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Agent skill

Chatexport Need Miner

by sickn33 in sickn33/agentic-awesome-skills

Mines offline Telegram Desktop chat exports (result.json) for unmet market needs and product opportunities using chunked streaming and verbatim quote grounding.

MITAuto-check passed

Install Chatexport Need Miner

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill chatexport-need-miner -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills chatexport-need-miner --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chatexport-need-miner .claude/skills/chatexport-need-miner && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
chatexport-need-miner
GitHub stars
47k
Used in
1 other repo
Token cost
~3.2k tokens
SKILL.md length
1,193 words
Files
1
Skills in repo
1,497
Repo updated
First seen
Licence
MIT

At a glance

Mines offline Telegram Desktop chat exports (result.json) for unmet market needs and product opportunities using chunked streaming and verbatim quote grounding.

  • Works in 5 steps: The 4MB Stream & Overlap Invariant… → Cross-Chat Multiplicity Law ($U \ge 3$… → Verbatim Quote Anchor &… → …
  • Phrases: mine chat export
  • SKILL.md covers When to Use This Skill, Core Mental Models &…, Named Sins & Anti-Patterns… and Concrete Archetypes / Presets, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Chatexport Need Miner is an agent skill from sickn33/agentic-awesome-skills. Mines offline Telegram Desktop chat exports (result.json) for unmet market needs and product opportunities using chunked streaming and verbatim quote grounding. Trigger phrases: mine chat export, telegram result.json, find unmet needs, analyze telegram chat.

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with Telegram. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Phrases: mine chat export
  • Telegram result.json
  • Find unmet needs
  • Analyze telegram chat

Example prompts

  • “Use the chatexport-need-miner skill to mine offline Telegram Desktop chat exports (result.json) for unmet market needs and product opportunities…”
  • “/chatexport-need-miner”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. The 4MB Stream & Overlap Invariant (Memory Ceiling <= 8MB)
  2. Cross-Chat Multiplicity Law ($U \ge 3$ Priority)
  3. Verbatim Quote Anchor & Anti-Hallucination Law
  4. Bi-Lingual Case-Insensitive Seed Lexicons
  5. Strict Air-Gap & Zero Exfiltration

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Chatexport Need Miner loads about 3.2k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 1,193 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~70
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its MIT licence (© sickn33). 1,193 words, ~3,224 tokens.

Download SKILL.mdSave it as .claude/skills/chatexport-need-miner/SKILL.md (or your agent's skills folder).
name
chatexport-need-miner
description
Mines offline Telegram Desktop chat exports (result.json) for unmet market needs and product opportunities using chunked streaming and verbatim quote grounding. Trigger phrases: mine chat export, telegram result.json, find unmet needs, analyze telegram chat.
category
development
risk
safe
source
community
source_repo
wwewtech/chatexport-need-miner
source_type
community
date_added
2026-09-22
author
wwewtech
tags
telegram, market-research, text-mining, offline-analytics, developer-tools
tools
claude, cursor, gemini, windsurf
license
MIT

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)

Anti-PatternManifestation in Code/WorkflowMandatory Production Counter-Rule
The OOM Slurpdata = json.load(open('result.json')) on 800MB file.Use incremental regex streaming or chunked buffered file reading with <= 8MB RAM footprint.
Chunk Boundary BlindnessChunking without overlap, truncating "looking for a tool" across 4096-byte splits.Maintain a 4KB sliding overlap tail across chunk transitions.
Double-Count Overlap TrapCounting hits found in both chunk $N$ and the overlap window of chunk $N+1$.Only increment match counter if match.end() > overlap_size.
The Echo-Chamber DistortionElevating a bug mentioned 80 times by 1 single user in 1 chat to the #1 product opportunity.Apply Cross-Chat Multiplicity Law ($U \times \sqrt{H}$) and count unique authors when available.
Hallucinated Quotations"User expressed desire for better sync" written in quotes as "I really need better sync".Exact substring slice from source buffer; if unquoted, label as synthetic analysis.
Service Message PollutionMining system notifications ("pinned a message", "joined group", bot spam) as human needs.Filter out messages where type == "service" or text begins with known bot commands (/start).
Premature Uniqueness ClaimStating "No tool currently exists for this problem" without validation.Run explicit coverage audit; if unverified, output strictly: I cannot confirm this.
Lossy Encoding CrashCrashing on multi-byte emoji surrogate pairs or non-UTF-8 characters in chat history.Decode with errors='replace' or raw byte-level UTF-8 traversal.
Monolithic Theme LumpingGrouping all complaints under "Users want better UI" or "Performance issues".Disaggregate into specific actionable workflows (e.g. "No zero-downtime database migration path").
API CreepPrompting the user for Telegram Bot tokens or phone numbers for MTProto login.Reject live requests; reiterate that input contract requires offline result.json exports only.
Show full SKILL.md (439 more words)Show less

Concrete Archetypes / Presets

Archetype 1: Streaming Regex Need Scanner (Python 3.10+)
python
import re
import os
from typing import Generator, Dict, List, Tuple

CHUNK_SIZE = 4 * 1024 * 1024  # 4 MB
OVERLAP = 4096                 # 4 KB

RU_LEXICON = re.compile(
    r"(?i)\b(не\s+хватает|вот\s+бы|бесит|надоело|задолбал|ищу\s+(?:инструмент|бот|софт)|"
    r"есть\s+ли\s+(?:бот|сервис|тул)|посоветуйте|вручную|рутина|приходится\s+руками)\b"
)
EN_LEXICON = re.compile(
    r"(?i)\b(i\s+wish|missing|annoying|frustrating|looking\s+for\s+a\s+(?:tool|bot|app)|"
    r"is\s+there\s+(?:an?\s+app|a\s+bot|a\s+tool)|any\s+alternative\s+to|manually|waste\s+of\s+time)\b"
)

def stream_chat_chunks(filepath: str) -> Generator[Tuple[str, int], None, None]:
    overlap_tail = ""
    with open(filepath, "r", encoding="utf-8", errors="replace") as f:
        while True:
            chunk = f.read(CHUNK_SIZE)
            if not chunk:
                break
            combined = overlap_tail + chunk
            yield combined, len(overlap_tail)
            overlap_tail = combined[-OVERLAP:] if len(combined) >= OVERLAP else combined

def mine_need_signals(filepath: str, regex: re.Pattern, max_samples: int = 5) -> Dict:
    hits = 0
    samples: List[str] = []
    for text_block, overlap_len in stream_chat_chunks(filepath):
        for m in regex.finditer(text_block):
            if m.end() > overlap_len:
                hits += 1
                if len(samples) < max_samples:
                    start = max(0, m.start() - 60)
                    end = min(len(text_block), m.end() + 140)
                    snippet = " ".join(text_block[start:end].split())
                    samples.append(snippet)
    return {"total_hits": hits, "samples": samples}
Archetype 2: Need Cluster & Prioritization Schema
json
{
  "theme_id": "NEED-001",
  "theme_name": "Zero-Downtime SQLite Replication for Edge Daemons",
  "aggregate_score": 14.14,
  "distinct_chats": 4,
  "total_hits": 50,
  "chats_observed": ["devops_talk_ru", "sqlite_users", "homelab_ops", "backend_craft"],
  "evidence": [
    {
      "date": "2026-08-14T11:22:04",
      "chat": "devops_talk_ru",
      "verbatim_quote": "бесит что нет нормальной репликации для sqlite на edge серверах без поднятия тяжелого postgres"
    },
    {
      "date": "2026-09-02T19:40:12",
      "chat": "sqlite_users",
      "verbatim_quote": "is there a tool that actually handles multi-master sqlite sync without crashing on high concurrency?"
    }
  ],
  "existing_coverage": [
    {"tool": "LiteFS", "gap": "Requires Consul / Fly.io infrastructure; complex on bare-metal edge."},
    {"tool": "rqlite", "gap": "Raft layer alters SQLite interface semantics."}
  ],
  "verdict": "Real commercial gap for turnkey lightweight edge replication."
}
Archetype 3: Multi-File Directory Batch Orchestrator
python
def process_export_directory(dir_path: str, pattern: re.Pattern) -> List[Dict]:
    results = []
    for root, _, files in os.walk(dir_path):
        for file in files:
            if file == "result.json" or file.endswith(".json"):
                full_path = os.path.join(root, file)
                chat_name = os.path.basename(root) if file == "result.json" else file
                data = mine_need_signals(full_path, pattern)
                if data["total_hits"] > 0:
                    results.append({"chat": chat_name, **data})
    return results

The Pre-Emit Quality Gate Checklist

Before emitting any market research summary or opportunity report, verify:

  • Memory Protection: Confirmed that raw JSON was parsed via chunked stream or filtered iterator, never loaded as a monolithic object.
  • Boundary Integrity: Overlap boundary logic was applied so split phrases across chunk cuts were not lost or double-counted.
  • Verbatim Quote Integrity: Every listed quote exists word-for-word in the input file with exact date and source. Zero paraphrasing.
  • Cross-Chat Breadth: Verified how many independent chat files the signal appeared in ($U \ge 3$ emphasized).
  • Service Message Stripping: Confirmed system and bot notifications were not tabulated as customer pain points.
  • Honesty and Verification Clause: If a gap or existing competitor cannot be verified, explicitly output: "I cannot confirm this".
  • Actionable Granularity: Themes are tied to specific engineering or operational workflows, not generic platitudes.

Self-Correction & Verification Loop

Bad (Vibe-Coded AI Slop Output):

"I reviewed the chats and users are looking for better dev tools. Many people complain about speed and say they wish things worked better. There is a huge opportunity to build an AI bot for developers." Problems: Zero verbatim quotes, zero date citations, zero chat distribution count, ungrounded speculation, generic meaningless advice.

Good (Production ChatExport Need Miner Output):
1. Schema Migration Rollbacks for Flyway in CI/CD — 38 hits across 4 chats ($U=4, H=38, \text{Score}=24.66$)
  • Chat Distribution: k8s_ru (14 hits), devops_community (12 hits), backend_pro (8 hits), java_chat (4 hits).
  • Evidence 1: "бесит когда flyway падает на миграции в CI и приходится вручную чистить schema_version таблицу на стейдже" (2026-07-19T09:12:44, devops_community).
  • Evidence 2: "is there a tool to safely dry-run flyway down migrations before merging to master?" (2026-08-04T16:21:09, k8s_ru).
  • Coverage Check: Flyway Pro provides undo migrations; however, community tier users lack automated sandbox validation without custom Docker scripts.
  • Verdict: Confirmed gap for a lightweight CLI pre-flight validator for open-source Flyway migrations.

Limitations

  • Use only exports you are authorized to analyze. Chat exports can contain personal or sensitive information; minimize copied excerpts, redact identifiers in reports, and follow applicable retention and privacy requirements.
  • Keep raw exports local and offline as described above. Do not upload messages, quotes, or identifiers to external services or include them in public reports without explicit authorization.
  • Keyword counts and clustered themes are exploratory signals, not representative market research. Validate conclusions with independent evidence and do not infer intent from isolated messages.
  • Chunked text scanning is not a complete Telegram JSON parser; malformed exports, escaped content, nested schemas, or encoding issues can affect counts. Verify any quoted excerpt against the original export.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/chatexport-need-miner of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Process Inboxtelegramdesktop/tdesktop33k1 repos~5.4kAutomated safety check: PassGPL-3.0

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Works with

Questions about Chatexport Need Miner

What does Chatexport Need Miner do?

Mines offline Telegram Desktop chat exports (result.json) for unmet market needs and product opportunities using chunked streaming and verbatim quote grounding. Chatexport Need Miner is an agent skill from sickn33/agentic-awesome-skills.json) for unmet market needs and product opportunities using chunked streaming and verbatim quote grounding.

When should I use Chatexport Need Miner?

Chatexport Need Miner fits situations like: phrases: mine chat export; telegram result.json; find unmet needs; analyze telegram chat.

How do I install Chatexport Need Miner in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill chatexport-need-miner -a claude-code`. Or copy the skill folder (skills/chatexport-need-miner in sickn33/agentic-awesome-skills) into .claude/skills/chatexport-need-miner in your project. Claude Code loads it when a task matches its description.

How do I install Chatexport Need Miner in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill chatexport-need-miner -a codex`. Or copy the skill folder (skills/chatexport-need-miner in sickn33/agentic-awesome-skills) into .agents/skills/chatexport-need-miner in your project. Codex loads it when a task matches its description.

Can I use Chatexport Need Miner in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill chatexport-need-miner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chatexport-need-miner, .gemini/skills/chatexport-need-miner, .github/skills/chatexport-need-miner and .opencode/skills/chatexport-need-miner in your project.

What does Chatexport Need Miner need to run?

SKILL.md names no scripts, command-line tools or credentials: Chatexport Need Miner is instructions for the agent only. Our summary lists: Python 3.

Does Chatexport Need Miner access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Chatexport Need Miner safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Chatexport Need Miner use?

Chatexport Need Miner is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chatexport Need Miner use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Chatexport Need Miner?

Skills that share tags, products or a category with Chatexport Need Miner: Dependency Watch (telegramdesktop/tdesktop, 33k stars), Perform Task (telegramdesktop/tdesktop, 33k stars), Custom Mode Creator for claude-mem (thedotmack/claude-mem, 99k stars) and Continue (telegramdesktop/tdesktop, 33k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chatexport Need Miner?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.