obsidian-medical-knowledge

obsidian-medical-knowledge is a skill for Claude Code, Codex from 2023Anita/clinical-ai-agent-skills. It costs 33 tokens per session (221 once invoked), scanned A, original, MIT.

A workflow for organizing clinical research notes, medical concepts, references, tags, and knowledge graphs in Obsidian, a note-taking application. It keeps source facts, interpretations, and review questions separate.

In plain words
What is it for?
Use it to structure medical research notes, add suitable metadata, connect related concepts, and preserve visible sources while protecting patient privacy.
Why use it?
It helps clinicians keep medical information traceable and clearly marked as unverified without turning raw notes into unsupported medical advice.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to structure medical research notes, add suitable metadata, connect related concepts, and preserve visible sources while protecting patient privacy.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge
Install

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.

Any agent
npx skills add 2023Anita/clinical-ai-agent-skills --skill obsidian-medical-knowledge
Clone the repo
git clone --depth 1 https://github.com/2023Anita/clinical-ai-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for obsidian-medical-knowledge

README.md
[![agentmods](https://agentmods.dev/badge/skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge/github.svg)](https://agentmods.dev/skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge)
Your own site
<a href="https://agentmods.dev/skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge"><img src="https://agentmods.dev/badge/skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge/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.

agentmods 80×15 button for obsidian-medical-knowledge

Your own site · 80×15
<a href="https://agentmods.dev/skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge"><img src="https://agentmods.dev/badge/skills/2023anita/clinical-ai-agent-skills/obsidian-medical-knowledge.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 221 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.00221
Opus 5 $0.00016 $0.00111
Sonnet 5 $0.00007 $0.00044
Haiku 4.5 $0.00003 $0.00022

Measured 12d ago against content hash 2d401a9a4fd5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

obsidian-medical-knowledge 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 12d 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.

skills/obsidian-medical-knowledge/SKILL.md · 49 lines

What it actually says

Obsidian Medical Knowledge

Goal

Organize medical research notes in a way that remains traceable, reviewable, and safe for non-programmer clinicians.

Required Behavior

  1. Preserve original source notes.
  2. Do not rewrite raw source material as if it were verified clinical advice.
  3. Keep concepts, claims, and references separated.
  4. Use clear tags and frontmatter when the vault already uses them.
  5. Avoid bulk reorganizing the vault unless explicitly requested.

Suggested Note Shape

---
type: literature-note
status: unverified
topic:
source:
reviewed_by_human: false
---

# Title

## Source Facts

## Interpretation

## Links

## Questions for Review

Safety Defaults

  • Do not include real patient identifiers.
  • Mark unverified notes clearly.
  • Keep source links visible.
  • Prefer small incremental changes.
Changes

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.

  1. 12d ago First seen · 49 lines · 33 tokens per session scan A 2d401a9a4fd5

Subscribe to this mod's changes

obsidian-medical-knowledge is a skill published in the GitHub repository 2023Anita/clinical-ai-agent-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 33 tokens to every session and 221 once invoked, about $0.0002 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 2026-08-31.

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