mine-channel
Skill6 starsChanged 2 months agoMITView on GitHub
Mine any Telegram channel or chat for signal in one command: incremental zero-token scrape, deterministic detector shortlist, LLM judge for what is genuinely valuable to this owner, then linked vault notes, a database row, a map-of-content entry and reindex. Triggers: "/mine-channel <@channel|id>", "alpha from <channel>".
- Reads credentials
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The file
Files
/mine-channel — pull in a channel and squeeze out the alpha in one command
🧒 Finish the reply to a non-technical operator with a simple "In plain words" recap (memory
eli5-always).
This generalizes a pattern that was repeated by hand 5+ times across different channels. Cost ladder [[vault-data-architecture]]: a deterministic detector (0 tokens) → an LLM judge over the shortlist only → the vault.
Steps
0. RECALL (do not duplicate). Has this channel been mined already? Check $IMPORTS_ROOT/alpha/<slug>\ and memory (*-mine, *-community-import). If yes, this is a TOP-UP: same slug, incremental.
1. Resolve the channel. A username (@some_channel / some_channel) or a numeric id (<YOUR_CHAT_ID>). If you do not know the id — mcp__telegram__search_dialogs or /chat <name>. Pick a short Latin slug (e.g. silmeshok).
2. Scrape + detector (0 tokens, 0 GPU):
set PYTHONIOENCODING=utf-8
python $IMPORTS_ROOT/alpha/mine_channel.py --channel <name|id> --slug <slug> [--limit N] [--top 40] [--since YYYY-MM-DD --until YYYY-MM-DD]→ _imports\alpha\<slug>\<slug>.jsonl + <slug>.db + the shortlist _imports\alpha\candidates\<slug>-report.md.
(The scrape goes through the subscription Telethon session <TELEGRAM_MCP_DIR>/.env, account work_acct_a — NOT a paid API [[prefer-included-limits-before-paid-api]]. Re-running without --channel plus --detect-only = re-detect without re-scraping.)
3. The judge (LLM, shortlist only). Run the shortlist through a cheap grunt model (grunt work → the small model [[model-routing-sonnet-grunt]]; a subagent with model:'sonnet', or the alpha-judge skill): keep only REAL alpha FOR THE OWNER (a tool/model/deal · a technique or workflow · a mental model · a proof point or benchmark · a build pattern), and drop promos, banter, and anything we already do better. Verdicts: ✅ alpha · 🟡 watch · 🗑 noise.
4. Into the vault (obsidian-ingest). Backup first [[vault-backup-rule]]. ✅ alpha → atomic notes + concept links ([[no-orphan-notes-rule]]) + a MOC _<Slug>-MOC; a sensitive channel → #private. The original jsonl stays in _imports\alpha\<slug>\ (that IS the _originals copy for the channel). Reindex [[reindex-routine]] (or let the nightly job pick it up).
5. Make it a routine? ([[evaluate-recurring-into-routine]]) A valuable channel → propose a weekly top-up (night window [[routines-run-at-night]]).
Boundaries
The detector is generic (AI / tool / deal / startup keywords); per-channel keyword and promo filters are tuned inside mine_channel.py. Sensitivity: closed / adult / personal channels → #private, never surfaced outside. Read the channel only, never post into it.
<!--kit-footer-->Like this skill? It is one of 100 in second-brain-starter-kit: the second brain we built for ourselves and run every day at Palo Alto AI Research Lab. Install the whole set with npx skills add tonydzi/second-brain-starter-kit. Everything is open source and free, so take what you need.
Flagships worth a look on their own: secondop-panel (a second opinion from a panel of external models), claude-memory-tidy (stop your agent's memory from rotting), telegram-mcp-kit (your own Telegram over MCP in about 15 minutes).
Author: Anton Dziatkovskii, Palo Alto AI Research Lab. Telegram @tonydzi - WhatsApp +1 341 222 9178 - X @Tony_Stef_
Engineers: want to test-drive this setup? Message me. I hand out free starter seeds to engineers who test and report back, and custom skill requests are welcome.
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