Borrowing it
Nothing to install: this file belongs to levi-qiao/obsidian-llm-wiki. 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/levi-qiao/obsidian-llm-wiki/main/.claude/skills/scholar-skill/en/SKILL.mdgit clone --depth 1 https://github.com/levi-qiao/obsidian-llm-wikiWrote 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/skills/levi-qiao/obsidian-llm-wiki/en)<a href="https://agentmods.dev/skills/levi-qiao/obsidian-llm-wiki/en"><img src="https://agentmods.dev/badge/skills/levi-qiao/obsidian-llm-wiki/en/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/skills/levi-qiao/obsidian-llm-wiki/en"><img src="https://agentmods.dev/badge/skills/levi-qiao/obsidian-llm-wiki/en.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 | $0.03629 |
| Opus 5 | $0.00000 | $0.01814 |
| Sonnet 5 | $0.00000 | $0.00726 |
| Haiku 4.5 | $0.00000 | $0.00363 |
Grade A, and why
en 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.
This is a copy
100% identical to en — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 465 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ScholarSkill - Academic Paper Reading and Knowledge Internalization
Description: An Obsidian-based L3-grade paper reading and memory extraction system.
Version: v1.0.0
Last Updated: 2026-03-18
Setup Guide Before First Use
Welcome to ScholarSkill! Owl mascot included.
Before reading papers, complete the setup flow below. This package supports three setup modes.
Setup Modes
Mode 1: Fully Automatic Setup (auto)
# Choose the English package first, then explicitly point to the target Obsidian vault
python ~/.openclaw/workspace-scholar/skills/scholar-skill/en/scripts/configure.py auto --vault-path "/your/Obsidian/Vault"
Best for: first-time users with Obsidian already installed
Automatically handles:
- detecting the Obsidian vault location
- creating the folder structure (
1-Papers,2-Knowledge,3-MOCs,memory, and more) - generating the config file
- checking dependency skills
Note: it is strongly recommended to always pass --vault-path so the script never selects the wrong vault and only syncs the English templates.
Mode 2: Semi-Automatic Setup (semi) - Recommended
# Run the English package setup script and explicitly provide the target vault
python ~/.openclaw/workspace-scholar/skills/scholar-skill/en/scripts/configure.py semi --vault-path "/your/Obsidian/Vault"
Best for: users who want to confirm each step
Flow:
- detect the Obsidian vault automatically, or prompt you if needed
- ask whether to create the folder structure
- check dependency skills and ask whether to install them
- generate the config file
Mode 3: Manual Setup (manual)
# Run the English package setup script and explicitly provide the target vault
python ~/.openclaw/workspace-scholar/skills/scholar-skill/en/scripts/configure.py manual --vault-path "/your/Obsidian/Vault"
Best for: advanced users who know exactly what they want
Flow:
- enter the Obsidian vault path manually
- skip directory creation for now
- only check dependencies without prompting installation
- generate a minimal config file
What ships with it
23 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- config.example.yml 3.3 KB
- docs/CONFIGURATION.md 10 KB
- docs/DURABLE-INTEGRATION.md 8.3 KB
- docs/FIXES-SUMMARY.md 6.3 KB
- docs/INTEGRATION-SUMMARY.md 6.7 KB
- protocols/CHECKLIST-Paper-Reading.md 3.6 KB
- protocols/READING-STRATEGY-v2.1.md 12 KB
- README.md 776 B
- scripts/configure.py 15 KB runs code
- scripts/replace-placeholders.py 3.3 KB runs code
- templates/Procedure-Human-Confirmation.md 3.2 KB
- templates/Template-Concept.md 670 B
- templates/Template-Confirmation-Request.md 1.4 KB
- templates/Template-Insight.md 750 B
- templates/Template-Method.md 515 B
- templates/Template-MOC.md 434 B
- templates/Template-Paper-Note-L2.md 1.7 KB
- templates/Template-Paper-Note-L3.md 3.7 KB
- templates/Template-Person.md 377 B
- templates/Template-Question.md 342 B
- templates/Template-Reflection-L1.md 1.6 KB
- templates/Template-Reflection-L2.md 2.1 KB
- templates/Template-Reflection-L3.md 3.8 KB
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 · 465 lines · 0 tokens per session scan A b12bf67a1271
en is a skill published in the GitHub repository levi-qiao/obsidian-llm-wiki (10 stars, last pushed 28d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,629 tokens. A static security scan graded it A with 0 findings. It is 100% identical to en, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
llm-wiki
Build and maintain a persistent, interlinked Obsidian-compatible markdown wiki using Karpathy's LLM Wiki pattern. Extension-backed with auto-generated metadata, guardrails, and 14 custom tools (+3 opt-in agent-trajectory tools).
kb-lint
Health check for the PARA Knowledge Base. Detects orphan documents, broken links, index drift, tag issues, and stale content. Run periodically or as part of weekly review.
ObsidianDataWeave: NotebookLM, Atomization, and LLM Wiki
Use when the user wants to control NotebookLM programmatically, import .docx into an Obsidian vault as atomic Zettelkasten notes, build a compiled LLM Wiki layer, or full-text-search the whole vault. Claude Code and Codex both supported.
wiki-bootstrap
Initialize the kObsidian LLM Wiki in the current vault. Use when the user says "set up a wiki", "start a knowledge base", "init the wiki", "bootstrap kobsidian wiki", or similar. Scaffolds wiki/{Sources,Concepts,Entities}/ and seeds index.md, log.md, wiki-schema.md.
refresh-context
A context snapshot updater for Core Context.md, a summary file built from nine main system files and selected essays. It refreshes that summary when the underlying material changes or the snapshot is more than 30 days old.
obsidian-wiki-system
Initialize or maintain a reusable Obsidian wiki knowledge iteration system with raw inbox, wiki pages, source/concept/synthesis/project templates, workflows, prompts, indexes, logs, and AGENTS.md rules. Use in Codex, OpenCode, or any agent that can read skill folders when the user wants to create a new Obsidian vault…