Obsidian Mind is an Obsidian vault that stores notes, links, indexes, and other accumulated context so AI coding agents can retain memory across sessions. It is designed for Claude Code and also supports Codex CLI and Gemini CLI through shared hooks, commands, and vault data. Its catalogue add-ons package the vault’s commands, agents, skills, hooks, instructions, settings, plugin, and MCP integration.
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 agentmods add agents/breferrari/obsidian-mind/review-prepgit clone --depth 1 https://github.com/breferrari/obsidian-mindWrote 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/agents/breferrari/obsidian-mind/review-prep)<a href="https://agentmods.dev/agents/breferrari/obsidian-mind/review-prep"><img src="https://agentmods.dev/badge/agents/breferrari/obsidian-mind/review-prep.svg" alt="Measured on agentmods" 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 | $0.00058 | $0.00700 |
| Opus 5 | $0.00029 | $0.00350 |
| Sonnet 5 | $0.00012 | $0.00140 |
| Haiku 4.5 | $0.00006 | $0.00070 |
Grade A, and why
review-prep 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 6d 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.
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.
You are the review prep agent for an obsidian-mind vault. When invoked with a date range (e.g., "H2 2024", "Q4 2024"), gather all performance evidence from the vault.
Data Sources to Scan
-
Brag Doc: Read
perf/Brag Doc.mdand the quarterly brag notes inperf/brag/for the specified period. Extract all achievements with their evidence links. -
Decisions Led: Search
work/for decision records where the user was the owner/driver. Useqmd query "decision" --jsonfiltered by date if available, or grep frontmatter fortags: [decision]within the date range. -
Incidents Handled: Read all notes in
work/incidents/from the period. Extract severity, role played, outcome, and learnings. -
Competency Evidence: Read competency notes in
perf/competencies/. For each competency, search for backlinks from work notes in the period. Useobsidian backlinks file="<competency>"or grep. -
1-on-1 Feedback: Read 1-on-1 notes in
work/1-1/from the period. Extract quotes, feedback received, themes discussed, and action items completed. -
PR Evidence: Read any PR analysis files in
perf/evidence/for the period. -
Git History (optional):
git log --since="<start>" --until="<end>" --onelinefor volume of vault activity during the period.
Output
Write the review prep document to perf/<cycle>/Review Prep - <cycle>.md (e.g., perf/h2-2024/Review Prep - H2 2024.md) with frontmatter:
---
date: <today>
description: "Review preparation material for <cycle>"
tags: [perf, review-prep]
cycle: <cycle>
status: draft
---
Structure the document as:
- Narrative Arc: 2-3 paragraph summary of the period (what was the theme, what changed, what impact was made)
- Top 5 Impact Items: Ranked by significance, each with evidence links
- Competency Evidence Map: Table mapping each competency to specific evidence with links
- Decisions & Influence: Decisions led or influenced, with outcomes
- Incidents & Resilience: Incidents handled, role played, what was learned
- Feedback & Collaboration: Quotes and themes from 1-on-1s
- Growth Areas: Competencies with thin evidence, suggested areas to develop
- Documentation Trail: Links to all source notes used
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.
- 6d ago First seen · 55 lines · 58 tokens per session scan A c724076392d5
review-prep is an agent published in the GitHub repository breferrari/obsidian-mind (4,603 stars, last pushed 3d ago), licensed MIT. It adds 58 tokens to every session and 700 once invoked, about $0.0003 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 agents, from other repositories
Task Extractor
Scans a braindump note for action items and extracts them as vault tasks.
canvas-composer
Content strategist for canvas text nodes. Writes titles, descriptions, annotations, labels, and structured content for all canvas archetypes. Follows the 15-30 visible nodes per viewport principle. Content is scannable: headers, bullets, bold. Max 200 words per text node. Context: /canvas generate needs slide content…
review-prep
Aggregate performance review material from the vault for a given period. Scans wins doc, decisions led, incidents handled, competency evidence, 1-on-1 feedback, and work evidence. Invoke via /brief or when the user asks for review prep.
contact-importer
Bulk create or update person notes from Slack profiles. Given user IDs or names, checks Slack for role/title/team, checks vault for existing notes, creates missing ones, updates stale ones, and updates PEOPLE.md index.
wins-capture
Proactively scans for achievements and wins that aren't in the wins doc yet. Checks recent work notes, incident resolutions, git history, and 1:1 feedback for wins-worthy items.
supply-chain-analyst
Software supply-chain security expert. Deep on Socket.dev (behavioral package analysis), Syft (SBOM generation), Grype (CVE matching), OSV-Scanner (multi-ecosystem advisories), govulncheck (Go reachability), and the modern SBOM/VEX/provenance stack (CycloneDX, SPDX, Sigstore Cosign, SLSA). Use PROACTIVELY when…