A comprehensive tool for managing software development sprints and stories within the Bolt platform using AI-driven automation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bolt-skill
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 bolt-skill 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 Bolt Sprint Management?
The Bolt Sprint Management skill is a powerful integration designed to bridge the gap between AI agents and agile project management. By leveraging Openclaw Skills, developers can automate the entire lifecycle of a sprint—from initial story creation to moving tasks through a Kanban workflow. This skill communicates directly with the Bolt REST API, allowing for real-time updates, blocker tracking, and detailed sprint digests, ensuring that both human and AI team members remain perfectly synchronized throughout the development process.
Built for modern collaborative environments, this skill enables AI agents to act as first-class citizens in the development cycle. Whether you are using Openclaw Skills to manage backlogs or track progress, the Bolt integration provides the necessary structure to maintain high-velocity software delivery while keeping documentation and status updates automated and accurate.
Bolt Sprint Management Use Cases
- Automating story creation and backlog grooming within Openclaw Skills environments.
- Moving tasks through Kanban states like waiting, in_progress, and completed.
- Generating automated sprint digests to track blockers and team velocity.
- Logging AI agent activity and events directly into the Bolt session timeline.
- Synchronizing project data across multiple agents using delta sync and field projections.
How Bolt Sprint Management Works
- The agent initializes a connection to the Bolt instance using the required BOLT_BASE_URL and optional BOLT_API_TOKEN.
- Users or automated triggers request project or sprint data via authenticated GET requests to retrieve the current state.
- AI agents create or update stories with specific priorities, points, and acceptance criteria based on project requirements.
- The skill manages state transitions through specialized move endpoints, facilitating a smooth Kanban-style workflow.
- Real-time activity logging and note-taking ensure a transparent audit trail of all AI interactions within the platform.
Bolt Sprint Management Setup
To get started with this skill, ensure your Bolt instance is running and set the following environment variables in your terminal:
export BOLT_BASE_URL="http://localhost:4000" # Your Bolt API base URL
export BOLT_API_TOKEN="your-token-here" # Required if the server uses authentication
You can verify the connection by running a simple health check:
curl -s "$BOLT_BASE_URL/health"
Bolt Sprint Management Data Schema & Taxonomy
The skill organizes data around the following primary entities and metadata:
| Entity | Key Attributes | Purpose |
|---|---|---|
| Stories | title, priority, status, points | Individual units of work with tracking metadata. |
| Sprints | id, projectId, duration | Logical groupings of stories for a development cycle. |
| Digests | blockers, story counts | Aggregated reports for sprint health and status. |
| Events | message, type, sessionId | Audit logs for AI agent actions and interactions. |
| Statuses | waiting, in_progress, completed | The three-stage Kanban lifecycle for tasks. |
Bolt Sprint Management Advanced Features
- Idempotency support using UUID headers to prevent duplicate operations during retries.
- Efficient delta sync capabilities to fetch only recently updated items using ISO8601 timestamps.
- Field projection to minimize payload size and optimize token consumption for Openclaw Skills.
- Batch move operations for updating multiple story statuses in a single atomic request.
- Automated AI activity logging to create a detailed history of agent-driven developments.
SKILL.md
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