An advanced AI-agent skill engineered to automate long-form manuscript planning, multi-layered structural drafting, and deep logical revision loops while maintaining ironclad voice consistency.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install autoskill-book-writing
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install autoskill-book-writing using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is autoskill-book-writing?
The autoskill-book-writing skill is a comprehensive framework designed for AI coding agents to architect, write, and refine complete books. It enforces rigorous preparation before a single line of prose is written, making it ideal for technical manuals, academic texts, novels, or business books. By shifting the focus from arbitrary word counts to structured reader outcomes, this skill ensures that manuscripts remain highly engaging, purposeful, and free of narrative drift.
Operating directly within a local workspace environment, it implements an exhaustive state machine that guides the writing process through structured phases: deconstruction, multi-disciplinary lens expansion, and rigorous self-rebuttal. This systematic approach ensures that structural flaws, logic gaps, or inconsistencies in tone are automatically surfaced and corrected early, preventing the common pitfalls of AI-generated content and delivering publish-ready manuscripts.
autoskill-book-writing Use Cases
- Outlining and structuring complex technical or academic books with multi-layered dependencies.
- Drafting long-form manuscripts while maintaining a strict, non-robotic voice profile, consistent tense, and custom lexical registers across chapters.
- Running autonomous, multi-pass editorial reviews to catch weak logic, redundant passages, or unfulfilled narrative promises.
- Local-first book production pipelines that require zero external API dependencies to safeguard intellectual property.
How autoskill-book-writing Works
- Task Decomposition & Memory Initialization: The agent loads setup parameters and instantiates a two-layer Task Decomposition Inventory (TDI) along with an Assumption Log inside local memory, mapping out variables like audience profiles, scope envelopes, and chapter architecture.
- Blueprint Alignment: A living document (
blueprint.md) tracks title candidates, core premises, and evidence logs, ensuring every section serves a distinct reader outcome. - Deconstruction & Child Node Generation: The agent populates specific detail records for each primary node, subjecting structural placeholders to rigorous validation cycles.
- Multi-Disciplinary Lens Expansion: Key assertions and technical chapters are evaluated through multiple discipline-specific viewpoints to verify accuracy and predictive depth.
- Triple-Cycle Skeptical Rebuttal: Every claim, chapter outline, and draft block undergoes three distinct self-correction passes (
Revision_1throughRevision_3) to eliminate fallacies, biases, or soft reasoning before locking content. - Token-Maximizing Content Generation & Continuous Execution: Driven by an immutable state machine, the agent systematically builds tables, audit logs, and chapter drafts, automatically entering execution recovery routines to maximize depth and content completion.
- Structured Polish & Output Handshake: The system executes targeted, separate revision passes for global structural flow, narrative arguments, and line editing, ending each interaction with the next immediate actionable micro-task.
autoskill-book-writing Setup
To activate the book-writing workspace, prepare the template files and seed the agent's local memory configuration:
# Create the local directory structure
mkdir -p ~/book-writing/chapters ~/book-writing/revisions ~/book-writing/archive
# Initialize memory tracking from templates
cp memory-template.md ~/book-writing/memory.md
# Pull down complementary voice or formatting micro-skills via Openclaw Skills hub
clawhub install writing
clawhub install writer
autoskill-book-writing Data Schema & Taxonomy
The skill manages manuscript state across isolated temperature tiers to prevent context contamination and maximize retrieval efficiency:
| Directory / File | Context Tier | Description |
|---|---|---|
~/book-writing/memory.md |
HOT | Houses current runtime status, active voice matrices, state machine gates, and immediate next actions. |
~/book-writing/chapters/ |
WARM | Contains individual chapter outlines, rough drafts, and incremental milestones. |
~/book-writing/revisions/ |
WARM | Stores pass-by-pass editorial change logs, Self-Rebuttal Ledgers, and multi-disciplinary lens tables. |
~/book-writing/archive/ |
COLD | Preserves superseded outlines, deprecated narrative arcs, and historical blueprint versions. |
blueprint.md |
CORE | Stores the core manuscript premise, verified facts, and master outcome map. |
revision-rubric.md |
RULE | Implements the deterministic evaluation benchmarks for finish-line verification. |
autoskill-book-writing Advanced Features
- Immutable State Machine Gating: Employs precise string-matched status gates to maintain architectural execution integrity and prevent premature runtime termination.
- Universal Triple-Cycle Rebuttal Ledger: Automatically challenges all AI assumptions through structural, logical, and ethical risk filters over three distinct iterations.
- Completion Escape Recovery Pass: An automated anti-truncation routine that forces the agent to expand on under-developed chapters and list open work items rather than exiting at a soft summary.
- Anti-Compression Audit Protocols: Enforces logical depth by preventing the AI agent from utilizing brevity rules on core content, ensuring detailed and complete prose.
SKILL.md
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