Copilot is an Obsidian plugin that brings AI agents into an Obsidian vault, where they can inspect notes, use tools, create files, and continue multi-step work. It supports research, writing, and knowledge-management workflows through opencode, Claude Code, or Codex. The catalogue entries define agents and other reusable Copilot configuration for working with vaults.
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/logancyang/obsidian-copilotWrote 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/rules/logancyang/obsidian-copilot/coding-rule)<a href="https://agentmods.dev/rules/logancyang/obsidian-copilot/coding-rule"><img src="https://agentmods.dev/badge/rules/logancyang/obsidian-copilot/coding-rule/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/rules/logancyang/obsidian-copilot/coding-rule"><img src="https://agentmods.dev/badge/rules/logancyang/obsidian-copilot/coding-rule.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 | $0.00020 | $0.00020 |
| Opus 5.5 | $0.00008 | $0.00008 |
| Sonnet 5.5 | $0.00004 | $0.00004 |
| Haiku 4.5 | $0.00002 | $0.00002 |
Grade A, and why
coding-rule 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 · 6 lines · 20 tokens per session scan A bbbd1add968b
coding-rule is a cursor rule published in the GitHub repository logancyang/obsidian-copilot (7,852 stars, last pushed yesterday), licensed AGPL-3.0. It adds 20 tokens to every session, about $0.0001 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 cursor rules, from other repositories
emergency-fund
Size an emergency fund from essential spend and real risk factors — not a one-size 'six months' — with the funding timeline and where the money should sit. Use when asked how big should my emergency fund be, do I have enough saved, emergency fund or invest, or how many months of expenses do I need. Produces the…
explorer-interface-brief
Use when asked to design the interface for an interactive 3D explorer, plan a UI for exploring a 3D model of a topic, or write an image-model prompt for a 3D learning app mock-up. Produces, from a topic, the UI design brief (audience, layout, panels, interactions, label style, colour palette, accessibility) and an…
ai-content-audit
Audit a content library, docs site, or blog for AI-generated filler that's eroding trust and search performance — and triage what to fix, rewrite, or delete. Use when asked to find slop in a content library, audit AI-written content quality, explain why content engagement or rankings dropped after scaling with AI, or…
respite-care-plan
Plan a genuine break from caregiving — arrange the coverage, hand off the essentials, and actually rest — because respite is what lets you keep going. Use when asked I need a break from caregiving, how do I arrange respite care, I can't leave them alone, or help me get time off from caring. Produces the coverage…
multi-source-signal-synthesiser
Synthesises user signals from multiple research sources into a unified, weighted insight brief. Use when you have data from interviews, support tickets, NPS verbatims, app reviews, or sales calls and need to reconcile contradictions, surface the underlying need behind requests, or answer 'what are users really telling…
bootstrap-alwayson
Minimal always-required LLM fixes.