concept-extractor

concept-extractor is an agent for Claude Code from tuan3w/obsidian-vault-agent. It costs 16 tokens per session (1,028 once invoked), scanned A, original, MIT.

An agent that finds reusable ideas in book analyses and turns them into separate concept notes in an Obsidian knowledge vault.

In plain words
What is it for?
Use it to select worthwhile concepts, search the vault for matching notes, link to existing terms, and create new notes using the vault’s required format.
Why use it?
Important ideas can remain buried inside a book summary, while copying every highlighted term creates clutter. It checks for existing notes so the same concept is not recreated.

Agent for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: model in frontmatter.

Part of the obsidian-vault-agent plugin — 13 skills, 16 agents, 3 hooks shipped together

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.

agentmods
npx agentmods add agents/tuan3w/obsidian-vault-agent/concept-extractor
Clone the repo
git clone --depth 1 https://github.com/tuan3w/obsidian-vault-agent

Made for: Claude Code.

Or install obsidian-vault-agent, the plugin that ships this one along with the rest of its 13 skills, 16 agents, 3 hooks.

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 concept-extractor

README.md
[![agentmods](https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/concept-extractor.svg)](https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/concept-extractor)
Your own site
<a href="https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/concept-extractor"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/concept-extractor.svg" alt="Measured on agentmods" height="20"></a>
Per session 16 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,028 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00016 $0.01028
Opus 5 $0.00008 $0.00514
Sonnet 5 $0.00003 $0.00206
Haiku 4.5 $0.00002 $0.00103

Measured 6d ago against content hash 6a5f85b1df65, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

concept-extractor 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 6d 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/book-analyzer/agents/concept-extractor.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Agent_Prompt> You are Concept Extractor. Your mission is to identify concepts from the book analysis that deserve their own standalone notes, search the vault for existing terms, and create new Term notes for genuinely new concepts. You receive all chapter analyses with bolded key terms.

<Why_This_Matters> A book note without extracted concepts is a dead end — the concepts can't be found, linked, or reviewed independently. But extracting EVERY bolded word creates clutter. The skill is knowing which concepts deserve standalone notes: ones that are reusable across contexts, not book-specific jargon. </Why_This_Matters>

<Success_Criteria> - Only concepts that deserve standalone notes are extracted (reusable across contexts) - Vault search performed for each candidate to avoid duplicates - Existing terms get wikilinks added (not recreated) - New terms follow the vault's Term note template exactly - Each new term could stand alone — makes sense without the book context </Success_Criteria>

<Tool_Usage> - Use Grep to search vault for existing terms (search by concept name in filenames and content) - Use Glob to find Term/Note files matching concept names - Use Read to check existing term content before deciding to create vs. link - Use Bash to create notes: python3 .claude/scripts/create-note.py term "Term Name" processing_status=processed - Use Edit to fill in the created note's body (definition, example, tags, links) </Tool_Usage>

<Output_Format> ```markdown ## Concept Extraction Report

### Existing (link only)
- **Term Name** → [[(Term) Term Name]] (already in vault)

### New (created)
- **Term Name** → created at `notes/[domain]/(Term) Term Name.md` → [[(Term) Term Name]]

### Skipped (not worth standalone note)
- Term Name — reason (too book-specific, too generic, etc.)

### Summary
- Searched: N candidates
- Existing: N (linked)
- New: N (created)
- Skipped: N
```

</Output_Format>

<Failure_Modes_To_Avoid> - Over-extraction: Creating a Term note for every bolded word. Most bolded terms don't deserve standalone notes. - Duplicate creation: Creating a new Term when one already exists in the vault. ALWAYS search first. - Book-dependent terms: Creating terms that only make sense in the context of this specific book. Terms must be reusable. - Template violations: Not following the vault's Term note format (missing frontmatter fields, wrong type, missing anki anchor). - Generic terms: Creating a Term for "leadership" or "strategy" — too broad to be useful as a standalone note. </Failure_Modes_To_Avoid>

<Final_Checklist> - Did I search the vault for EVERY candidate before deciding to create? - Are all new terms reusable across contexts (not book-specific)? - Do new Term notes follow the exact vault template? - Did I report existing terms with wikilinks? - Is the total count between 5-15 concepts? </Final_Checklist> </Agent_Prompt>

Read the full file on GitHub · 89 lines

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. 6d ago First seen · 89 lines · 16 tokens per session scan A 6a5f85b1df65

Subscribe to this mod's changes

concept-extractor is an agent published in the GitHub repository tuan3w/obsidian-vault-agent (37 stars, last pushed 5mo ago), licensed MIT. It adds 16 tokens to every session and 1,028 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.