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/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/log)<a href="https://agentmods.dev/commands/michael-ovo/obsidian-knowledge-agent/log"><img src="https://agentmods.dev/badge/commands/michael-ovo/obsidian-knowledge-agent/log/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/michael-ovo/obsidian-knowledge-agent/log"><img src="https://agentmods.dev/badge/commands/michael-ovo/obsidian-knowledge-agent/log.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 | $0.00010 | $0.00206 |
| Opus 5.5 | $0.00004 | $0.00082 |
| Sonnet 5.5 | $0.00002 | $0.00041 |
| Haiku 4.5 | $0.00001 | $0.00021 |
Grade A, and why
log 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 1mo 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
Append $ARGUMENTS as a timestamped entry to today's daily log. Keep it instant — no ceremony.
- Find today's log. If the vault already uses daily notes, follow that location and
naming. Otherwise use
Daily/{YYYY-MM-DD}.md— createDaily/and the file if needed, with minimal frontmatter (tags: [daily],created). - Append a line under a
## Logsection:- HH:MM — {entry}. Never rewrite earlier entries. - If the entry clearly refers to a note or project, add a wikilink to it. Don't expand a
log line into a full note — that's
/obsidian-knowledge:capture. - Confirm in one line where it went.
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.
- 1mo ago First seen · 16 lines · 10 tokens per session scan A 6553c2750dec
log is a command published in the GitHub repository Michael-OvO/obsidian-knowledge-agent (206 stars, last pushed 4mo ago), licensed MIT. It adds 10 tokens to every session and 206 once invoked, about $0.0000 per session on Opus 5.5. 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
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).
process-inbox
Process the inbox. Read everything the user dropped in (notes, links, a deck, a messy folder) and route each fact to the most specific workspace file, separating facts from assumptions and open questions, without inventing anything.
plan
Create a phased implementation plan before writing any code.
megacave
Activate megacave mode (caveman in Classical Chinese).
help
Quick reference for all Attune commands.
fire-todos
Capture, list, and manage todos during work sessions.