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 commands/michael-ovo/obsidian-knowledge-agent/researchgit clone --depth 1 https://github.com/Michael-OvO/obsidian-knowledge-agentWrote 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/michael-ovo/obsidian-knowledge-agent/research)<a href="https://agentmods.dev/commands/michael-ovo/obsidian-knowledge-agent/research"><img src="https://agentmods.dev/badge/commands/michael-ovo/obsidian-knowledge-agent/research.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 | $0.00014 | $0.00298 |
| Opus 5 | $0.00007 | $0.00149 |
| Sonnet 5 | $0.00003 | $0.00060 |
| Haiku 4.5 | $0.00001 | $0.00030 |
Grade A, and why
research 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 5d 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
Research the topic in $ARGUMENTS and turn it into notes that teach.
- Recall + fit. Read
.agents/learned/conventions.mdif present and see how this vault is organized, so the result lands in the right place in the right shape. - Research. Search the web and fetch authoritative sources — papers, official docs, primary references. Prefer primary/real sources over second-hand summaries, keep the URLs for citation, and note where sources disagree or are uncertain.
- Pick the altitude. A focused question → one strong note plus a source note. A broad
topic → a small collection with an index, concept notes, and a concept-graph canvas if
there are 3+ units. (See "Choose the altitude" in
.agents/ingestion-workflow.md.) - Write to the standard in
.agents/style-guide.md: open from the real question; explain mechanism, assumptions, and limits; use the artifacts that genuinely teach (runnable code, an equation, a diagram); and cite sources in aSourcessection with links. - Wire & validate every wikilink, then reflect (journal entry + any durable lesson).
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.
- 5d ago First seen · 21 lines · 14 tokens per session scan A 0fc2d581776d
research is a command published in the GitHub repository Michael-OvO/obsidian-knowledge-agent (206 stars, last pushed 2mo ago), licensed MIT. It adds 14 tokens to every session and 298 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
daily-okr
Run a daily knowledge compound loop (7 KR). Invoke with /daily-okr or "start my daily review".
adopt
Adopt an existing directory as the SuperBrain vault (marks it, indexes existing notes).
install
Guided setup for a new Cowork workspace. Interviews you (about 5 minutes) and generates a full, pre-configured cowork-os workspace (folders, copy, project instructions, and recurring routines).
knowledge-transfer
Interview a person to capture their operating know-how (tacit knowledge) and write it into the workspace as the company brain: processes, rules with source, glossary, decisions and open questions. For onboarding, a key person leaving, or standardizing a process.
linkedin-editor
Run the 8-step LinkedIn editor on any source (an article, a case study, a draft, rough notes) and deliver ready-to-publish, founder-voice LinkedIn posts optimized for reach and leads, not likes.
upskill
Find the skill gaps that keep recurring across your applications and turn them into a learning plan.