---
name: book-mirror
description: "Reads a book the owner provides (PDF, ePub, web link, or text), walks it chapter by chapter, and produces a personalised mirror that maps each chapter's claims to the owner's known context. Triggers when the owner says 'mirror this book', 'two-column analysis', 'how does this book apply to me', 'personalise this book against my business'."
---

# Book mirror

Invoked from `specialists:research-assistant`.

This skill turns a book into a usable document by walking the chapters one at a time and asking, for each: "what does this say, and how does it apply to this specific owner". The output is a personalised pack the owner can read once and act on. It is grounded in the graph; the right-hand column is always specific to what the graph already knows about the owner.

## When to run

Run when the owner asks for a book to be applied to their situation. The trigger phrases are above. Do not run when the owner asks for a simple summary; a summary is what `deep-research` produces, and that is the right skill for that intent.

## Inputs

| Input | Meaning |
|---|---|
| `source` | The book. A path to a file in `$ACCOUNT_DIR`, a web URL, or pasted text. |
| `anchor` | A node in the graph the book is being mirrored against. Usually the `LocalBusiness` node; can also be a named `Project` or `Goal`. |

If the anchor is missing, ask for it in one sentence: "Mirror against the business, or a specific project?".

## Method

1. **Confirm the source.** If `source` is a file path, read it. If it is a URL, fetch it. If it is pasted text, work from the text directly. Reject sources that cannot be read; do not paraphrase a book the skill has not seen.
2. **Identify the chapters.** Look for chapter headings in the text. If the book has none, segment by first-level headings or by every 2000 to 4000 words. Tell the owner the chapter count before starting.
3. **For each chapter, build the two columns.**
   - **Left.** A two-to-three-sentence summary of the chapter's actual claim. Quote verbatim only when the wording matters; otherwise paraphrase tightly.
   - **Right.** A two-to-three-sentence note on how the claim applies to the anchor, grounded in graph specifics. Pull from `memory-search` against the anchor: the owner's business stage, recent obstacles, named projects, the LocalBusiness `businessType` schema. Name specific entities. Do not write "this applies to your business in general": that is jargon for "I have nothing specific to say".
   - **Actions.** End each chapter with one or two concrete steps the owner could take this week. Use the imperative ("Call the photographer to confirm the brief for 14 Garth Road" rather than "Consider arranging photography").
4. **Save the result.** Compose the whole pack as one `:KnowledgeDocument` with `:Section:Chapter` children per chapter. Link the document to the anchor node via `MIRRORS` (or `REFERENCES` if `MIRRORS` is not in the live ontology: call `maxy-graph-get_neo4j_schema` first).

## Output format

```
# Mirror: <book title> against <anchor name>

## Chapter 1: <chapter title>

**The chapter.** <2-3 sentence summary>

**For <anchor>.** <2-3 sentence application, grounded in graph specifics>

**This week.** 
- <one concrete action>
- <one concrete action>

---

## Chapter 2: ...
```

Present the assembled pack as a single fenced markdown block in chat for owner review before saving. The owner reads the pack inline and can ask for chapter-level edits in their next message. Once the owner approves, write to the graph.

## Length discipline

Each chapter must fit on one screen (roughly 30 lines). If a chapter's claims need more, split the application across two or three chapter mirrors; do not pad. The whole pack should be readable in one sitting; a 20-chapter book becomes a 60-page pack only if every chapter genuinely earns its application.

## Failure modes

- **No chapters detectable and no headings.** Ask the owner to confirm the chunk size or to provide a chapter list.
- **Anchor has thin graph context** (LocalBusiness with no recent activity, Project with no Tasks). Surface the gap: "the graph has limited context for <anchor>. The right column will be general where it should be specific. Continue?". Wait for confirmation.
- **`memory-search` returns no useful results for the anchor**. Stop. The book cannot be mirrored against an empty anchor; tell the owner and recommend running `business-profile` or naming a different anchor.
- **Source fetch fails.** Surface the error literally. Do not summarise from training memory.

## What this skill does not do

It does not summarise a book without an anchor; that is generic content, which `deep-research` can produce. It does not produce a study guide, a literature review, or a comparative essay. It produces one specific output: a personalised application of one book to one named entity in the graph.