A professional writing utility that generates structural intent cards for H2 chapters to ensure logical flow and cross-subsection coherence without generating prose.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chapter-briefs
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 chapter-briefs 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 Chapter Briefs?
Chapter Briefs is a specialized utility within the Openclaw Skills ecosystem designed to bridge the gap between a raw outline and the final drafting phase. It focuses on transforming H2 chapters that contain multiple H3 subsections into actionable writing cards. By defining the internal intent, comparison axes, and synthesis modes, this skill prevents the common failure mode of island paragraphs where subsections feel disconnected or repetitive.
This skill is strictly for structural planning and decision constraints; it does not generate reader-facing prose. Instead, it provides a technical framework for writers or AI agents to maintain a consistent throughline, stabilize terminology via bridge terms, and plan lead paragraphs that preview complex comparison lenses across technical documents.
Chapter Briefs Use Cases
- Transforming high-level outlines into detailed H2 chapter execution plans.
- Ensuring logical coherence across multiple H3 subsections within a technical paper or survey.
- Establishing synthesis modes like tradeoff matrices or timeline resolutions before drafting.
- Stabilizing technical terminology across large-scale documentation projects.
How Chapter Briefs Works
- The tool ingests the existing outline.yml and subsection_briefs.jsonl files from the workspace.
- It identifies all H2 chapters that contain nested H3 subsections to determine where synthesis is required.
- The skill analyzes the subsection briefs to extract key contrasts and bridge terms that span the entire chapter.
- It generates a throughline and a specific lead paragraph plan consisting of 2-3 paragraph objectives.
- A final chapter_briefs.jsonl file is produced, serving as a contract for the final writing stage.
Chapter Briefs Setup
To use this Openclaw Skills module, ensure you have python3 installed and a workspace configured with an existing outline.
# View help and available options
python scripts/run.py --help
# Run the skill on a specific workspace
python scripts/run.py --workspace workspaces/<your-workspace-dir>
# Run with explicit input and output paths
python scripts/run.py --workspace workspaces/<ws> --inputs "outline/outline.yml;outline/subsection_briefs.jsonl;GOAL.md" --outputs "outline/chapter_briefs.jsonl"
Chapter Briefs Data Schema & Taxonomy
The skill produces a JSONL output located at outline/chapter_briefs.jsonl. Each object in the file represents one H2 chapter and includes the following schema:
| Field | Description |
|---|---|
section_id |
Unique identifier for the H2 chapter. |
synthesis_mode |
Logic type: clusters, timeline, tradeoff_matrix, case_study, or tension_resolution. |
throughline |
3-6 bullets defining the core explanatory goal of the chapter. |
key_contrasts |
2-6 bullets highlighting comparisons across H3 subsections. |
lead_paragraph_plan |
2-3 objectives for the chapter's introductory block. |
bridge_terms |
A set of 5-12 tokens to maintain terminology stability. |
Chapter Briefs Advanced Features
- Refinement Markers: Create an outline/chapter_briefs.refined.ok file to lock your manual refinements and prevent automated scripts from overwriting your work.
- Synthesis Diversity: Automatically enforces different synthesis modes across chapters to prevent repetitive document structures.
- Context Injection: Supports reading from GOAL.md to align chapter throughlines with specific audience constraints and project scopes.
- Multi-Input Mapping: Aggregates contrast hooks and bridge terms from all child H3 subsections into a unified H2 intent card.
SKILL.md
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