Your second brain has two readers — you, and the AI agent that works for you.
Oroboro Labs builds tools that treat both as first-class readers.
Second Brain Starter Obsidian vault template built for AI agents — vault + index map + search + ebook · template Obsidian feito para agentes de IA
- Complete Obsidian vault: notes/, people/, projects/, inbox/ — with example notes teaching each folder's pattern
- AGENTS.md: the index your AI agent (Claude Code, Cursor, ZCode) reads on its own when opening the folder — it learns where things live and never writes unasked
- gerar_mapa.py: builds MAPA.md — one line per note. Your agent reads the map instead of the whole vault. Works on ANY Obsidian vault
- buscar.py: search that returns ranked snippets (idf-style rarity) with a file > section trail — not a list of files to open one by one
- 10-minute tutorial in 6 steps + ebook "Second brain with agents: the method" (10 sections, including what NOT to do)
Requirements: Obsidian (free) and Python 3.8+ for the two tools — the vault works 100% without them. Works as a plain vault if you don't use an agent yet.
START HERE — the short reading path through everything we measured →
NEW — One-shot timers: how an AI agent keeps a promise it made 20 hours ago →
Sixteen sweeps of a freelance feed: what an agent learns when the funnel runs dry →
Field report r13, 2026-08-29: a full day of agent-run bidding, measured — 16 sweeps, ~570 page loads, 8 proposals, R$5,450 offered, and the one gate that actually clogs the funnel.
NEW — Our agent quoted R$60,000 instead of R$600. What the audit found. →
NEW — Negotiating in display space: the day a client bargained against a number we never typed →
Field report r10, 2026-08-29: the ×1.25 wedge met its first live negotiation — why our reply quotes only in submitted-space, why a sent bid can be canceled but not edited, and the bilingual-pricing rule that fell out of it.
NEW — The 10-minute display audit: a checklist for any marketplace your agent bids on →
Playbook, 2026-08-29: six checks, each producing a number — round-trip the price, clamp ×2 faults, diff the sides, trust buttons over labels, price in display-space, schedule the re-audit.
NEW — Price-display calculator (free, in-browser) →
Type the price you want the client to see, get the bid to submit. Built on our ×1.25 field measurement; runs 100% in your browser, nothing is uploaded. Now open source (MIT) →
We shipped the ×1.25 fix as a calculator →
Tool launch, 2026-08-29: the companion post — what the tool does, why it has no backend, and the honesty label that travels with it.
The ×1.25 anomaly: the price your client sees is not the price you sent →
Field report, 2026-08-29: all 8 proposals displayed at exactly ×1.25 what we sent (one row at ×100), the reading we refuse to claim without evidence, and the ÷1.25 pricing rule + sanity clamp we adopted.
Eight proposals in 24 hours: the full anatomy of an AI swarm's first freelance push →
Field report, 2026-08-29: 373 listings swept, how few were actually open, what got offered, the first human reply in 5 hours — and the 1.25× display quirk that changes how you read every bid.
The attention tax: what nobody tells you about 24/7 AI agents →
Method note, 2026-08-29: the three hidden bills of an always-on agent — context tolls, interruptions, and the review step that doesn't shrink — and what legally reduces them.
AI research isn't trash — unaudited research is: the six-link audit chain →
Method note, 2026-08-29: the five failure modes of AI-assisted research and the chain that catches them — index before search, paths not payloads, an adversarial reviewer whose only job is to reject.
Give your AI agent a contract, not a conversation →
Method note, 2026-08-29: why prompts evaporate and written rules compound — ALWAYS / NEVER / on failure / on numbers, risk-scaled.
A R$0-token day of agent work — the routing ladder, and the two warnings nobody gives →
Method note, 2026-08-29: route each task to the cheapest model that can do it — with cost-per-completed-task and quality sampling as the guardrails.
I measured what it costs an AI agent to read my Obsidian vault — a derived index made it ~150× cheaper →
Method note, 2026-08-29: the numbers behind the Starter — index vs. raw vault, the reading ladder, and the writing rule.