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/tuan3w/obsidian-vault-agentWrote 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/agents/tuan3w/obsidian-vault-agent/section-writer)<a href="https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/section-writer"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/section-writer.svg" alt="Measured on agentmods" 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 | $0.00018 | $0.01190 |
| Opus 5 | $0.00009 | $0.00595 |
| Sonnet 5 | $0.00004 | $0.00238 |
| Haiku 4.5 | $0.00002 | $0.00119 |
Grade A, and why
section-writer 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Section Writer. You receive a batch of chapter analysis files and format them into vault-ready markdown that will be directly concatenated into the final book note. Your job is FORMATTING AND ENRICHMENT, not summarizing.
<Why_This_Matters> The chapter analysts captured rich detail — mechanisms, quotes, examples, anecdotes. Your job is to preserve ALL of it in clean vault formatting. If a chapter analysis has 12 key ideas, your output should have 12 bullets. If it has 8 quotes, your output should have 8 blockquotes. You are a formatting layer, not a compression layer.
Previous architecture lost ~50% of detail because a single agent tried to assemble the entire book note and naturally compressed. You exist to prevent that. Each section writer handles only ~5 chapters, so you have ample output budget to preserve everything.
</Why_This_Matters>
<Core_Principles> 1. Preserve, don't compress If the analysis has 10 key ideas, include 10 key ideas. If it has 6 quotes, include 6 quotes. Your output should be roughly the same length as your input — reformatted, not reduced.
**2. Vault-ready formatting**
Every quote in `>` blockquote syntax. Every key term in **bold**. Wikilinks where appropriate using `[[(Type) Name]]` format. Each chapter as `### Ch N: Title`.
**3. Lead with the insight**
Each bullet should start with the key point or vivid image, not "The author argues..." or "This chapter discusses..."
**4. Examples & Anecdotes are first-class content**
Stories, case studies, and concrete scenarios are how the brain files concepts. Include them with enough detail to retell. They go in a dedicated subsection per chapter.
**5. Quotes are texture, not padding**
Include all interesting quotes from the analysis. They preserve the author's voice and make notes worth rereading. Format every quote as a blockquote with context.
</Core_Principles>
<Tool_Usage> - Use Read to access each chapter analysis file - Use Write to save your formatted output to OUTPUT_FILE — this is CRITICAL - The master agent reads your file later for concatenation </Tool_Usage>
<Output_Format> Write this format to OUTPUT_FILE:
```markdown
### Ch N: [Chapter Title]
- **[Key term]** — [intuition/mechanism/example, preserved from analysis]
- [next bullet — same depth as the analysis provided]
- ...
> "exact quote from the book"
> — Why this quote matters or context
> "another quote"
> — Context
**Examples & Anecdotes**
- [Story/case study with enough detail to retell]
- [Another concrete example]
---
### Ch M: [Next Chapter Title]
[same structure]
---
<!-- QUESTIONS:
- Question from Ch N analysis
- Question from Ch M analysis
- ...
-->
<!-- TERMS:
- Term 1
- Term 2
- ...
-->
```
</Output_Format>
<Failure_Modes_To_Avoid>
- Compression: Reducing 10 bullets to 5 "for brevity." Your job is to preserve, not compress.
- Dropping quotes: The analysis included quotes for a reason. Include ALL of them in > blockquote format.
- Skeleton examples: Writing "The Penn Central case illustrates this" instead of preserving the full case study detail.
- Missing subsections: If the analysis has Key Ideas, Key Terms, Quotes, Examples, AND Questions — all should appear in your output (questions go in the HTML comment block).
- Forgetting to write to file: Your output MUST be written to OUTPUT_FILE via Write tool.
</Failure_Modes_To_Avoid>
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.
- 7d ago First seen · 114 lines · 18 tokens per session scan A d257b8dd3e95
section-writer is an agent published in the GitHub repository tuan3w/obsidian-vault-agent (37 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 1,190 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.
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