Tracer Issue Tracker

Track tasks and dependencies with a CLI supporting JSONL storage.

Updated Oct 20, 2025
One-click install
npx skills add https://github.com/scottatron/claude-skills --skill tracer-issue-tracker
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Tracer Issue Tracker
Source: https://github.com/scottatron/claude-skills/tree/main/tracer
Command: npx skills add https://github.com/scottatron/claude-skills --skill tracer-issue-tracker

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manual issue tracking is slow and cumbersome, especially for AI agents. Managing complex task dependencies and identifying the next unblocked piece of work can be a significant bottleneck, leading to inefficiencies and delays in project execution.

Core Features & Use Cases

  • Dependency-Aware Tracking: Automatically identifies what tasks are blocked and what work is ready to start, streamlining AI agent workflows.
  • AI-Optimized Output: Provides lightning-fast, JSON-formatted output for all commands, making programmatic parsing and integration with AI agents seamless.
  • Git-Native Storage: Stores issues in human-readable JSONL files that sync easily via Git, enabling distributed collaboration across multiple agents and sessions.
  • Use Case: An AI agent is tasked with building a new feature. It uses Tracer to break down the epic into dependent tasks, automatically discovers the first unblocked task, and updates its status as it progresses, ensuring a clear, efficient path to completion.

Quick Start

Use the Tracer skill to initialize a new project and create a task 'Implement user login'.

Frequently Asked Questions about Tracer Issue Tracker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track task dependencies and identify unblocked work for AI agents?

Tracer automatically manages task dependencies through a CLI-based tracker that identifies blocked tasks and surfaces ready work. It outputs JSON on all commands, enabling AI agents to programmatically discover the next unblocked task and update progress without manual intervention.

Can I store issues in Git-friendly format for distributed collaboration?

Yes, Tracer stores all issues in human-readable JSONL files that sync via Git, enabling multiple agents and sessions to collaborate without centralized infrastructure. Changes are tracked naturally as part of version control.

How do I set up dependency-aware task tracking in a Rust workflow?

Initialize a Tracer project via CLI, create tasks with dependency links, then use commands to create, list, show, update, close, and link dependencies. Rust performance ensures fast JSON output even with complex dependency graphs.

What's the best way to break down an epic into dependent tasks for AI agents?

Use Tracer to decompose the epic into subtasks, then establish dependency relationships between them. The tracker automatically exposes task order, so agents discover and execute work sequentially without manual scheduling.

Does Tracer provide JSON output for programmatic integration with AI workflows?

All Tracer commands output structured JSON, making it trivial to parse results programmatically and integrate with AI agent orchestration, logging, and decision-making systems without custom parsing logic.

Why is manual issue tracking inefficient for AI agent task management?

Manual tracking obscures task dependencies and blocks, forcing agents to query state repeatedly or wait for human intervention. Tracer eliminates this by automating dependency resolution and exposing ready work instantly via CLI.