workflow-book-chapter
A focused single-agent workflow for turning rough source material into a strategic first-person chapter draft with explicit revision loops.
How it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
A focused single-agent workflow for turning rough source material into a strategic first-person chapter draft with explicit revision loops.
Agent definition
workflow-book-chapter.mdWorkflow Example: Book Chapter Development
> A focused single-agent workflow for turning rough source material into a strategic first-person chapter draft with explicit revision loops.
When to Use This
Use this workflow when an author has voice notes, fragments, or strategic notes, but not yet a clean chapter draft. The goal is not generic ghostwriting. The goal is to produce a chapter that strengthens category positioning, preserves the author's voice, and exposes open editorial decisions clearly.
Agent Used
| Agent | Role | |-------|------| | Book Co-Author | Converts source material into a versioned chapter draft with editorial notes and next-step questions |
Example Activation
Activate Book Co-Author.
Book goal: Build authority around practical AI adoption for Mittelstand companies.
Target audience: Owners and operational leaders of 20-200 person businesses.
Chapter topic: Why most AI projects fail before implementation starts.
Desired draft maturity: First substantial draft.
Raw material:
- Voice memo: "The real failure happens in expectation setting, not tooling."
- Notes: Leaders buy software before defining the operational bottleneck.
- Story fragment: We nearly rolled out the wrong automation in a cabinetmaking workflow because the actual problem was quoting delays, not production throughput.
- Positioning angle: Practical realism over hype.
Produce:
1. Chapter objective and strategic role in the book
2. Any clarification questions you need
3. Chapter 2 - Version 1 - ready for review
4. Editorial notes on assumptions and proof gaps
5. Specific next-step revision requests
Expected Output Shape
The Book Co-Author should respond in five parts:
1. `Target Outcome` 2. `Chapter Draft` 3. `Editorial Notes` 4. `Feedback Loop` 5. `Next Step`
Quality Bar
- The draft stays in first-person voice
- The chapter has one clear promise and internal logic
- Claims are tied to source material or flagged as assumptions
- Generic motivational language is removed
- The output ends with explicit revision questions, not a vague handoff
Read more
Workflow Example: Book Chapter Development
> A focused single-agent workflow for turning rough source material into a strategic first-person chapter draft with explicit revision loops.
When to Use This
Use this workflow when an author has voice notes, fragments, or strategic notes, but not yet a clean chapter draft. The goal is not generic ghostwriting. The goal is to produce a chapter that strengthens category positioning, preserves the author's voice, and exposes open editorial decisions clearly.
Agent Used
| Agent | Role | |-------|------| | Book Co-Author | Converts source material into a versioned chapter draft with editorial notes and next-step questions |
Example Activation
Activate Book Co-Author. Book goal: Build authority around practical AI adoption for Mittelstand companies. Target audience: Owners and operational leaders of 20-200 person businesses. Chapter topic: Why most AI projects fail before implementation starts. Desired draft maturity: First substantial draft. Raw material: - Voice memo: "The real failure happens in expectation setting, not tooling." - Notes: Leaders buy software before defining the operational bottleneck. - Story fragment: We nearly rolled out the wrong automation in a cabinetmaking workflow because the actual problem was quoting delays, not production throughput. - Positioning angle: Practical realism over hype. Produce: 1. Chapter objective and strategic role in the book 2. Any clarification questions you need 3. Chapter 2 - Version 1 - ready for review 4. Editorial notes on assumptions and proof gaps 5. Specific next-step revision requests
Expected Output Shape
The Book Co-Author should respond in five parts:
1. `Target Outcome` 2. `Chapter Draft` 3. `Editorial Notes` 4. `Feedback Loop` 5. `Next Step`
Quality Bar
- The draft stays in first-person voice
- The chapter has one clear promise and internal logic
- Claims are tied to source material or flagged as assumptions
- Generic motivational language is removed
- The output ends with explicit revision questions, not a vague handoff
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