Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tonydzi/second-brain-starter-kit --skill mine-channelgit clone --depth 1 https://github.com/tonydzi/second-brain-starter-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tonydzi/second-brain-starter-kit/mine-channel)<a href="https://agentmods.dev/skills/tonydzi/second-brain-starter-kit/mine-channel"><img src="https://agentmods.dev/badge/skills/tonydzi/second-brain-starter-kit/mine-channel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tonydzi/second-brain-starter-kit/mine-channel"><img src="https://agentmods.dev/badge/skills/tonydzi/second-brain-starter-kit/mine-channel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.01122 |
| Opus 5 | $0.00036 | $0.00561 |
| Sonnet 5 | $0.00014 | $0.00224 |
| Haiku 4.5 | $0.00007 | $0.00112 |
Grade A, and why
mine-channel scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/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).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 55 lines · 72 tokens per session scan A 089651371dd6
mine-channel is a skill published in the GitHub repository tonydzi/second-brain-starter-kit (6 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 1,122 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-09.
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