Blocpad CLI-The missing layer for cursor

Product Introduction

1. Definition: Blocpad CLI is a command-line interface tool categorized as a context automation layer for AI-assisted software development. It integrates directly with the BlocPad task/project management platform.
2. Core Value Proposition: It exists to eliminate AI guesswork by providing exact task context from BlocPad to coding assistants (like Cursor, Codex CLI, Claude CLI, GitHub Copilot). This ensures AI tools receive structured, scope-bound instructions, leading to faster, more accurate code generation with fewer iterative corrections.

Main Features

1. Explicit Scope Management: Blocpad CLI operates within a defined BlocPad project and task context. Commands like blocpad tasks focus <TASK_ID> require an active context, ensuring exported information is always relevant and bounded. This prevents AI hallucinations from incomplete scope.
2. Dual-Format Context Export: It provides two key export mechanisms. --json flag outputs stable, parseable JSON for automation scripts and CI/CD pipelines. --md flag generates Markdown-formatted task details, descriptions, and hierarchies optimized for direct copy/paste into LLM chat interfaces of coding assistants.
3. Structured Agent Workflow Support: Features like blocpad tasks next <TASK_ID> --json and blocpad tasks focus <TASK_ID> --md are designed specifically for AI agent workflows. They identify the next actionable "leaf" task (an independent unit of work) and export its full context, enabling step-by-step AI task execution guided by hierarchy (parent/child relationships) and status.
4. Secure & Parseable Output: Prioritizes security and automation. Personal Access Tokens (bp_pat_...) are stored locally in the user config dir (e.g., ~/Library/Application Support/blocpad/ on macOS) and handled securely. Using --json routes all prompts and non-data output to stderr, guaranteeing stdout remains pure, machine-readable JSON for reliable scripting.
5. Configurable Overrides: Supports runtime flexibility through command-line flags (e.g., --token) and environment variables (e.g., BLOCPAD_TOKEN, BLOCPAD_CONFIG_DIR). This allows clean overrides of local configuration for specific scripts or temporary environments without altering persistent settings.

Problems Solved

1. Pain Point: AI coding tools (Cursor, Copilot, Claude, etc.) often produce inaccurate or irrelevant output due to insufficient or ambiguous task context derived solely from open files or minimal prompts.
2. Target Audience: Frontend/backend engineers using AI coding assistants; DevOps engineers automating task-driven workflows; teams managing complex projects with hierarchical tasks in BlocPad seeking to integrate AI reliably.
3. Use Cases: Feeding precise task requirements and acceptance criteria to an AI assistant for implementation; automating CI/CD steps based on BlocPad task status/completion; enabling AI agents to autonomously navigate and execute tasks within a predefined project hierarchy; ensuring consistent context sharing across team members using different AI tools.

Unique Advantages

1. Differentiation: Unlike generic AI prompt helpers or manual context copying, Blocpad CLI is deeply integrated with BlocPad's task hierarchy and provides structured, tool-specific exports. It uniquely focuses on actionable task execution for AI agents, not just prompt enhancement. Competitors lack this direct task-management system integration and hierarchical task navigation.
2. Key Innovation: The focus and next commands, combined with hierarchical task analysis (parentTaskId), enable AI agents to intelligently select and work on independent "leaf" tasks within complex projects. This structured approach to AI task execution, coupled with guaranteed parseable output (stdout/stderr separation) and secure token handling, is its core technical innovation.

Frequently Asked Questions (FAQ)

1. How does Blocpad CLI improve AI coding assistant accuracy? Blocpad CLI feeds AI tools exact, structured context (task details, hierarchy, acceptance criteria) directly from BlocPad via Markdown exports, eliminating guesswork and ensuring the AI works on the correct scope, leading to more relevant and correct code output.
2. Is Blocpad CLI safe to use with sensitive projects? Yes, it's designed for security. The CLI is read-only (cannot modify BlocPad data), tokens (bp_pat_...) are stored securely locally and never output, and users are instructed never to share tokens with LLMs. JSON exports ensure clean data for automation.
3. How do I integrate Blocpad CLI with Cursor or GitHub Copilot? Define tool-specific rules (e.g., in .cursorrules for Cursor or .github/copilot-instructions.md for Copilot) instructing the AI to use Blocpad CLI commands. Then, use blocpad tasks focus <TASK_ID> --md to export Markdown context and paste it into the AI's chat prompt when requesting work on a task.
4. What's the difference between JSON and Markdown exports? Use --json output for machine consumption in scripts, automation, or custom integrations. Use --md output for human-readable context to paste directly into the chat interfaces of AI coding assistants like Cursor, Claude, or Codex CLI.
5. Can Blocpad CLI automate task workflows without AI? Absolutely. The stable JSON output (blocpad tasks list --json, blocpad tasks tree <TASK_ID> --json) is ideal for scripting task status checks, generating reports, triggering builds based on task completion, or integrating BlocPad data into other DevOps tools.