obsidian-second-brain turns an Obsidian vault into persistent, searchable memory for Claude Code and other command-line coding agents, storing knowledge as linked Markdown notes. It is for developers, founders, writers, and researchers who want agents to retain project context across sessions. Its catalogue entries provide commands, hooks, a plugin, a skill, and instructions for capturing, finding, and maintaining that memory.
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.
git clone --depth 1 https://github.com/eugeniughelbur/obsidian-second-brainWrote 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/commands/eugeniughelbur/obsidian-second-brain/x-pulse)<a href="https://agentmods.dev/commands/eugeniughelbur/obsidian-second-brain/x-pulse"><img src="https://agentmods.dev/badge/commands/eugeniughelbur/obsidian-second-brain/x-pulse/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/commands/eugeniughelbur/obsidian-second-brain/x-pulse"><img src="https://agentmods.dev/badge/commands/eugeniughelbur/obsidian-second-brain/x-pulse.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 | $0.00024 | $0.00787 |
| Opus 5 | $0.00012 | $0.00394 |
| Sonnet 5 | $0.00005 | $0.00157 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
x-pulse 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 9d ago.
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.
What it actually says
Use the obsidian-second-brain skill. Execute /x-pulse [topic]:
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Resolve the topic from the user's argument. Multi-word topics are fine ("AI automation", "vibe coding"). If no topic was given, ask: "What topic should I scan X for?"
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Run the script from the skill root (its absolute path was given at session start as Skill root; substitute it for
SKILL_ROOT):uv run --directory "SKILL_ROOT" -m scripts.research.x_pulse "<topic>" -
The script returns a structured pulse: WHAT'S HOT (themes with rep posts + voices), WHAT'S UNDEREXPLORED (gaps), HOOKS THAT ARE WORKING, VOICE & TONE WORKING, POST IDEAS FOR YOU TODAY. Show the full output to the user verbatim.
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Default save behavior: saves automatically. The script writes an AI-first note to
Research/X-pulse/YYYY-MM-DD - <slug>.mdwith the AI-first vault rule applied (preamble, frontmatter, recency markers, sources verbatim). It also appends a one-line entry tolog.md. -
After printing, mention to the user the file path that was saved (the script prints this on stderr, surface it cleanly).
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Plain English triggers that route to this command: "what's hot on X about [topic]", "X pulse on [topic]", "what should I post about [topic] today", "scan X for [topic]", "trends on X about [topic]".
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If the script reports "No active discourse found in last 72h on this topic", offer to either broaden the topic or try
/research [topic]instead (Perplexity for general web research). -
If the script fails with a clear error, surface it verbatim. Auto-retry on transient errors is handled inside the script.
AI-first rule: Every note created or updated by this command MUST follow references/ai-first-rules.md - ## For future agent preamble, rich frontmatter (type, date, tags, ai-first: true, plus type-specific fields), recency markers per external claim, mandatory [[wikilinks]] for every person/project/concept referenced, sources preserved verbatim with URLs inline, and confidence levels where applicable. If that path does not resolve from your working directory, search upward for it; if you still cannot read it, say so before writing rather than producing a note that silently skips the rule. The vault is for future agent retrieval - not human reading.
Anti-fabrication: Search exhaustively before claiming any note, person, or file is absent - false absence is the most common failure mode - and never invent facts, entities, or dates (mark unknowns as TBD). See the anti-fabrication and search-completeness hard rules in references/ai-first-rules.md.
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.
- 9d ago First seen · 36 lines · 24 tokens per session scan A 0f6d2e6f8a04
x-pulse is a command published in the GitHub repository eugeniughelbur/obsidian-second-brain (4,364 stars, last pushed 2d ago), licensed MIT. It adds 24 tokens to every session and 787 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
second-brain-mapping
Map your vault: extract structured metadata from every typed file, surface cross-doc insights, optionally build a knowledge graph.
cierre
A sales call just ended: turn its transcript into the full follow-up (CRM, tasks, email draft, reminder, coaching).
daily-journal
Daily journal interview and entry creator with emotional floor tagging.
deconstruct
First-principles analyst: surface hidden assumptions, find foundational truths, rebuild from scratch.
diagnose
Run a self-check on your AI Brain Starter install (CLAUDE.md, Meta folder, skills, hooks, MCPs).
evolve
Cluster hardened instincts into a proposed Command / Skill / Agent (Instinct Engine).