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.
Borrowing it
Nothing to install: this file belongs to breferrari/obsidian-mind. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/breferrari/obsidian-mind/main/.claude/commands/om-review-brief.mdgit 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/commands/breferrari/obsidian-mind/om-review-brief)<a href="https://agentmods.dev/commands/breferrari/obsidian-mind/om-review-brief"><img src="https://agentmods.dev/badge/commands/breferrari/obsidian-mind/om-review-brief/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/breferrari/obsidian-mind/om-review-brief"><img src="https://agentmods.dev/badge/commands/breferrari/obsidian-mind/om-review-brief.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 | $0.00000 | $0.00629 |
| Opus 5 | $0.00000 | $0.00315 |
| Sonnet 5 | $0.00000 | $0.00126 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
om-review-brief 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 11d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate Review Brief
Generate a performance review context transfer document from vault data. Supports manager version (PO-friendly) and peer version (project-focused).
Usage
/om-review-brief <audience> [period]
Examples:
/om-review-brief manager "Q3 2024 + Q4 2024"/om-review-brief peers "Q3 2024 + Q4 2024"
Subagent
review-prep— aggregates all evidence (brag doc, decisions, incidents, competencies, 1:1 feedback, PR scans) for the period
Launch the subagent first to gather raw material, then use its output to write the brief.
Workflow
1. Gather Data
Read these vault sources:
perf/<cycle>/Review Brief.md(or current private brief) — full contextperf/Brag Doc.md— quarterly highlightsperf/brag/Q*.md— quarterly detail notes for the periodperf/evidence/Your PRs - *.md— PR datawork/*.md— project notes for the periodperf/competencies/*.md— competency definitions- Previous review notes for baseline comparison
2. Generate Content
For manager audience:
- Frame for a non-technical audience — outcome language, not technical jargon
- Include: The Arc (narrative), Impact at a Glance (table), Impact Details (per project), Competency Highlights (with baselines), Documentation Trail
- Simplify technical terms for your audience's background
- No wikilinks — use plain text or markdown links to external resources
- Include all documentation, task tracker, repository, error tracking, and communication references
For peer audience:
- Can be more technical but still accessible (peers write reviews that go to manager)
- Organize by project (a common review tool structure)
- Include "Other things worth mentioning" for non-project work
- Casual tone — "jog your memory", "no pressure to cover everything"
- No competency section — that's for the manager
3. Create Files
- Markdown version in
perf/ - HTML version with professional styling (blue theme, tables, responsive)
- PDF via Chrome headless:
--headless --no-pdf-header-footer --print-to-pdf
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.
- 11d ago First seen · 70 lines · 0 tokens per session scan A b751b029e46b
om-review-brief is a command published in the GitHub repository breferrari/obsidian-mind (4,620 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 629 tokens. 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
kb-ingest
Ingest external material into Sources/ inside the bound project KB, then update registry, index, and daily note as needed.
kb-promote
Promote durable content from Daily or source notes into canonical Knowledge, Experiments, Results, Results/Reports, or Writing notes.
status
Show memex statistics and status including projects, memos, and pending items.
curate
A command for maintaining a file-based knowledge wiki. It can review pages, shorten overlong material, manage page lifecycles, find possible contradictions, and rebuild weak connections between notes.
ingest
A command for adding information to a file-based knowledge wiki from web pages, files, or text notes. It classifies the material, updates or creates wiki pages, and adds links between related pages.
onboard
An interview-based setup command for an LLM Wiki, a notes system designed for use with language models. It asks about your wiki, files, working mode, and personal context, then fills in the setup details.