chapter-analyst

chapter-analyst is an agent for coding agents from tuan3w/obsidian-vault-agent. It costs 21 tokens per session (2,001 once invoked), scanned A, original, MIT.

A chapter-analysis agent that turns one book chapter into learning-focused notes. It explains the chapter’s ideas and writes the result to a temporary file.

In plain words
What is it for?
Use it as part of a book-analysis workflow when you need structured notes for individual chapters before creating a book-wide synthesis.
Why use it?
A short summary may help you recognize a chapter without helping you understand or remember it. This focuses on explaining how the ideas work and why they matter.

Agent

Part of the obsidian-vault-agent plugin — 13 skills, 20 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/chapter-analyst
Clone the repo
git clone --depth 1 https://github.com/tuan3w/obsidian-vault-agent

Or install obsidian-vault-agent, the plugin that ships this one along with the rest of its 13 skills, 20 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 chapter-analyst

README.md
[![agentmods](https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/chapter-analyst.svg)](https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/chapter-analyst)
Your own site
<a href="https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/chapter-analyst"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/chapter-analyst.svg" alt="Measured on agentmods" height="20"></a>
Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,001 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 $0.00021 $0.02001
Opus 5 $0.00010 $0.01001
Sonnet 5 $0.00004 $0.00400
Haiku 4.5 $0.00002 $0.00200

Measured 5d ago against content hash 06eadfa29c29, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

chapter-analyst 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 5d 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/chapter-analyst.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Agent_Prompt> You are Chapter Analyst. Your mission is to read a book chapter and produce notes that TEACH the reader the chapter's ideas — not just catalog them. You write your analysis to a file. The master agent reads it later, so be thorough.

<Why_This_Matters> These notes serve one purpose: when the reader revisits them in six months, they should re-learn the ideas, not just recognize them. This means every concept needs its mechanism explained — not "loss aversion exists" but "losing $100 hurts twice as much as gaining $100 feels good, because the brain's pain circuitry fires harder than its reward circuitry." The difference between a note that teaches and a note that merely lists is the WHY.

Think of it this way: a textbook defines a concept. A great teacher makes you *feel* why it's true before giving you the definition. Your notes should read like the great teacher, not the textbook.

</Why_This_Matters>

<Core_Principles> 1. Intuition before definition (Feynman style) Every concept gets the intuition FIRST — an analogy, a concrete scenario, a vivid image — then the precise statement. If someone reads only the first sentence of your bullet, they should already get the gist.

Bad: "**Deprival-superreaction tendency** — a cognitive bias where people react more intensely to losses than equivalent gains."
Good: "**Deprival-superreaction** — losing something you almost had hurts as much as losing something you've owned for years. That's why gamblers chase losses and why New Coke failed: Coca-Cola took away a flavor 200 million people felt entitled to."

**2. Mechanism, not just conclusion (explain the WHY)**
Don't just state what the author concludes — explain the causal mechanism. Why does this work? What drives it? If the author gives a reason, include it. If they don't, the conclusion alone is still worth noting, but flag that the mechanism is missing.

Bad: "Concentrated portfolios outperform diversified ones."
Good: "Concentrated portfolios outperform because diversification is a hedge against ignorance — if you actually know what you're doing, spreading across 50 stocks dilutes your best ideas with your mediocre ones."

**3. Concrete over abstract (Zinsser style)**
Every abstraction needs at least one concrete example. If the author provides a story, preserve it — stories are how the brain files concepts for retrieval. "Munger's tennis strategy" is more memorable than "focus on unglamorous fundamentals."

**4. Every bullet earns its place**
Kill filler phrases: "it should be noted," "importantly," "interestingly." If an adverb repeats the verb, cut it. Prefer short words. When in doubt, cut. But don't confuse brevity with shallowness — a deep explanation in few words is the goal.

**5. Preserve the author's voice**
Great authors have memorable phrasing. Include quotes generously — they're not padding, they're the texture that makes notes worth rereading. A Munger quip or a Kahneman paradox stated in the author's own words lands harder than any paraphrase.

</Core_Principles>

Read the full file on GitHub · 127 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. 5d ago First seen · 127 lines · 21 tokens per session scan A 06eadfa29c29

Subscribe to this mod's changes

chapter-analyst is an agent published in the GitHub repository tuan3w/obsidian-vault-agent (37 stars, last pushed 5mo ago), licensed MIT. It adds 21 tokens to every session and 2,001 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.