bd - Beads Issue Tracker 🔗

Give your coding agent a memory upgrade

⚠️ Alpha Status: This project is in active development. The core features work well, but expect API changes before 1.0. Use for development/internal projects first.

Beads is a lightweight memory system for coding agents, using a graph-based issue tracker. Four kinds of dependencies work to chain your issues together like beads, making them easy for agents to follow for long distances, and reliably perform complex task streams in the right order.

Drop Beads into any project where you’re using a coding agent, and you’ll enjoy an instant upgrade in organization, focus, and your agent’s ability to handle long-horizon tasks over multiple compaction sessions. Your agents will use issue tracking with proper epics, rather than creating a swamp of rotten half-implemented markdown plans.

Instant start:

curl -fsSL https://raw.githubusercontent.com/steveyegge/beads/main/install.sh | bash

Then tell your coding agent to start using the bd tool instead of markdown for all new work, somewhere in your AGENTS.md or CLAUDE.md. That’s all there is to it!

You don’t use Beads directly as a human. Your coding agent will file and manage issues on your behalf. They’ll file things they notice automatically, and you can ask them at any time to add or update issues for you.

Beads gives agents unprecedented long-term planning capability, solving their amnesia when dealing with complex nested plans. They can trivially query the ready work, orient themselves, and land on their feet as soon as they boot up.

Agents using Beads will no longer silently pass over problems they notice due to lack of context space – instead, they will automatically file issues for newly-discovered work as they go. No more lost work, ever.

Beads issues are backed by git, but through a clever design it manages to act like a managed, centrally hosted SQL database shared by all of the agents working on a project (repo), even across machines.

Beads even improves work auditability. The issue tracker has a sophisticated audit trail, which agents can use to reconstruct complex operations that may have spanned multiple sessions.

Agents report that they enjoy working with Beads, and they will use it spontaneously for both recording new work and reasoning about your project in novel ways. Whether you are a human or an AI, Beads lets you have more fun and less stress with agentic coding.

Features

• ✨ Zero setup - bd init creates project-local database (and your agent will do it)
• 🔗 Dependency tracking - Four dependency types (blocks, related, parent-child, discovered-from)
• 📋 Ready work detection - Automatically finds issues with no open blockers
• 🤖 Agent-friendly - --json flags for programmatic integration
• 📦 Git-versioned - JSONL records stored in git, synced across machines
• 🌍 Distributed by design - Agents on multiple machines share one logical database via git
• 🏗️ Extensible - Add your own tables to the SQLite database
• 🔍 Multi-project isolation - Each project gets its own database, auto-discovered by directory
• 🌲 Dependency trees - Visualize full dependency graphs
• 🎨 Beautiful CLI - Colored output for humans, JSON for bots
• 💾 Full audit trail - Every change is logged

Installation

Quick Install (Recommended)

curl -fsSL https://raw.githubusercontent.com/steveyegge/beads/main/install.sh | bash

The installer will:

• Detect your platform (macOS/Linux, amd64/arm64)
• Install via go install if Go is available
• Fall back to building from source if needed
• Guide you through PATH setup if necessary

Manual Install

# Using go install (requires Go 1.21+)
go install github.com/steveyegge/beads/cmd/bd@latest

# Or build from source
git clone https://github.com/steveyegge/beads
cd beads
go build -o bd ./cmd/bd
sudo mv bd /usr/local/bin/  # or anywhere in your PATH

Quick Start

For Humans

Beads is designed for AI coding agents to use on your behalf. As a human, you typically just:

# 1. Initialize beads in your project
bd init

# 2. Add a note to your agent instructions (CLAUDE.md, AGENTS.md, etc.)
echo "We track work in Beads instead of Markdown. Run \`bd quickstart\` to see how." >> CLAUDE.md

# 3. Let agents handle the rest!

Most tasks will be created and managed by agents during conversations. You can check on things with:

bd list                  # See what's being tracked
bd show <issue-id>       # Review a specific issue
bd ready                 # See what's ready to work on
bd dep tree <issue-id>   # Visualize dependencies

For AI Agents

Run the interactive guide to learn the full workflow:

bd quickstart

Quick reference for agent workflows:

# Find ready work
bd ready --json | jq '.[0]'

# Create issues during work
bd create "Discovered bug" -t bug -p 0 --json

# Link discovered work back to parent
bd dep add <new-id> <parent-id> --type discovered-from

# Update status
bd update <issue-id> --status in_progress --json

# Complete work
bd close <issue-id> --reason "Implemented" --json

The Magic: Distributed Database via Git

Here’s the crazy part: bd acts like a centralized database, but it’s actually distributed via git.

When you install bd on any machine with your project repo, you get:

• ✅ Full query capabilities (dependencies, ready work, etc.)
• ✅ Fast local operations (<100ms via SQLite)
• ✅ Shared state across all machines (via git)
• ✅ No server, no daemon, no configuration
• ✅ AI-assisted merge conflict resolution

How it works:

1. Each machine has a local SQLite cache (.beads/*.db) - gitignored
2. Source of truth is JSONL (.beads/issues.jsonl) - committed to git
3. bd export syncs SQLite → JSONL before commits
4. bd import syncs JSONL → SQLite after pulls
5. Git handles distribution; AI handles merge conflicts

The result: Agents on your laptop, your desktop, and your coworker’s machine all query and update what feels like a single shared database, but it’s really just git doing what git does best - syncing text files across machines.

No PostgreSQL instance. No MySQL server. No hosted service. Just install bd, clone the repo, and you’re connected to the “database.”

Usage

Creating Issues

bd create "Fix bug" -d "Description" -p 1 -t bug
bd create "Add feature" --description "Long description" --priority 2 --type feature
bd create "Task" -l "backend,urgent" --assignee alice

# Get JSON output for programmatic use
bd create "Fix bug" -d "Description" --json

Options:

• -d, --description - Issue description
• -p, --priority - Priority (0-4, 0=highest)
• -t, --type - Type (bug|feature|task|epic|chore)
• -a, --assignee - Assign to user
• -l, --labels - Comma-separated labels
• --json - Output in JSON format

Viewing Issues

bd show bd-1              # Show full details
bd list                   # List all issues
bd list --status open     # Filter by status
bd list --priority 1      # Filter by priority
bd list --assignee alice  # Filter by assignee

# JSON output for agents
bd list --json
bd show bd-1 --json

Updating Issues

bd update bd-1 --status in_progress
bd update bd-1 --priority 2
bd update bd-1 --assignee bob
bd close bd-1 --reason "Completed"
bd close bd-1 bd-2 bd-3   # Close multiple

# JSON output
bd update bd-1 --status in_progress --json
bd close bd-1 --json

Dependencies

# Add dependency (bd-2 depends on bd-1)
bd dep add bd-2 bd-1
bd dep add bd-3 bd-1 --type blocks

# Remove dependency
bd dep remove bd-2 bd-1

# Show dependency tree
bd dep tree bd-2

# Detect cycles
bd dep cycles

Finding Work

# Show ready work (no blockers)
bd ready
bd ready --limit 20
bd ready --priority 1
bd ready --assignee alice

# Show blocked issues
bd blocked

# Statistics
bd stats

# JSON output for agents
bd ready --json

Database Discovery

bd automatically discovers your database in this order:

1. --db flag: bd --db /path/to/db.db create "Issue"
2. $BEADS_DB environment variable: export BEADS_DB=/path/to/db.db
3. .beads/*.db in current directory or ancestors (walks up like git)
4. ~/.beads/default.db as fallback

This means you can:

• Initialize per-project databases with bd init
• Work from any subdirectory (bd finds the database automatically)
• Override for testing or multiple projects

Example:

# Initialize in project root
cd ~/myproject
bd init --prefix myapp

# Work from any subdirectory
cd ~/myproject/src/components
bd create "Fix navbar bug"  # Uses ~/myproject/.beads/myapp.db

# Override for a different project
bd --db ~/otherproject/.beads/other.db list

Dependency Model

Beads has four types of dependencies:

1. blocks - Hard blocker (affects ready work calculation)
2. related - Soft relationship (just for context)
3. parent-child - Epic/subtask hierarchy
4. discovered-from - Tracks issues discovered while working on another issue

Only blocks dependencies affect the ready work queue.

Dependency Type Usage

blocks: Use when issue X cannot start until issue Y is completed

bd dep add bd-5 bd-3 --type blocks  # bd-5 blocked by bd-3

related: Use for issues that are connected but don’t block each other

bd dep add bd-10 bd-8 --type related  # bd-10 related to bd-8

parent-child: Use for epic/subtask hierarchies

bd dep add bd-15 bd-12 --type parent-child  # bd-15 is child of epic bd-12

discovered-from: Use when you discover new work while working on an issue

# While working on bd-20, you discover a bug
bd create "Fix edge case bug" -t bug -p 1
bd dep add bd-21 bd-20 --type discovered-from  # bd-21 discovered from bd-20

The discovered-from type is particularly useful for AI-supervised workflows, where the AI can automatically create issues for discovered work and link them back to the parent task.

AI Agent Integration

bd is designed to work seamlessly with AI coding agents:

# Agent discovers ready work
WORK=$(bd ready --limit 1 --json)
ISSUE_ID=$(echo $WORK | jq -r '.[0].id')

# Agent claims and starts work
bd update $ISSUE_ID --status in_progress --json

# Agent discovers new work while executing
bd create "Fix bug found in testing" -t bug -p 0 --json > new_issue.json
NEW_ID=$(cat new_issue.json | jq -r '.id')
bd dep add $NEW_ID $ISSUE_ID --type discovered-from

# Agent completes work
bd close $ISSUE_ID --reason "Implemented and tested" --json

The --json flag on every command makes bd perfect for programmatic workflows.

Ready Work Algorithm

An issue is “ready” if:

• Status is open
• It has NO open blocks dependencies
• All blockers are either closed or non-existent

Example:

bd-1 [open] ← blocks ← bd-2 [open] ← blocks ← bd-3 [open]

Ready work: [bd-1] Blocked: [bd-2, bd-3]

Issue Lifecycle

open → in_progress → closed
↓
blocked (manually set, or has open blockers)

Architecture

beads/
├── cmd/bd/              # CLI entry point
│   ├── main.go          # Core commands (create, list, show, update, close)
│   ├── init.go          # Project initialization
│   ├── quickstart.go    # Interactive guide
│   └── ...
├── internal/
│   ├── types/           # Core data types (Issue, Dependency, etc.)
│   └── storage/         # Storage interface
│       └── sqlite/      # SQLite implementation
└── EXTENDING.md         # Database extension guide

Extending bd

Applications can extend bd’s SQLite database with their own tables. See EXTENDING.md for the full guide.

Quick example:

-- Add your own tables to .beads/myapp.db
CREATE TABLE myapp_executions (
id INTEGER PRIMARY KEY,
issue_id TEXT NOT NULL,
status TEXT NOT NULL,
started_at DATETIME,
FOREIGN KEY (issue_id) REFERENCES issues(id)
);

-- Query across layers
SELECT i.*, e.status as execution_status
FROM issues i
LEFT JOIN myapp_executions e ON i.id = e.issue_id
WHERE i.status = 'in_progress';

This pattern enables powerful integrations while keeping bd simple and focused.

Comparison to Other Tools

Feature	bd	Taskwarrior	GitHub Issues	Jira	Linear
Zero setup	✅	✅	❌	❌	❌
Dependency tracking	✅	✅	⚠️	✅	✅
Ready work detection	✅	⚠️	❌	❌	❌
Agent-friendly (JSON)	✅	⚠️	⚠️	⚠️	⚠️
Distributed via git	✅	⚠️	❌	❌	❌
Works offline	✅	✅	❌	❌	❌
AI-resolvable conflicts	✅	❌	❌	❌	❌
Extensible database	✅	❌	❌	❌	❌
No server required	✅	✅	❌	❌	❌
Built for AI agents	✅	❌	❌	❌	❌

vs. Taskwarrior: Taskwarrior is great for personal task management, but bd is designed specifically for AI agents. bd has explicit dependency types (discovered-from), JSON-first API design, and JSONL storage optimized for git merging. Taskwarrior’s sync server requires setup; bd uses git automatically.

Why bd?

bd is designed for AI coding agents, not humans.

Traditional issue trackers (Jira, GitHub Issues, Linear) assume humans are the primary users. Humans click through web UIs, drag cards on boards, and manually update status.

bd assumes AI agents are the primary users, with humans supervising:

• Agents discover work - bd ready --json gives agents unblocked tasks to execute
• Dependencies prevent wasted work - Agents don’t duplicate effort or work on blocked tasks
• Discovery during execution - Agents create issues for work they discover while executing, linked with discovered-from
• Agents lose focus - Long-running conversations can forget tasks; bd remembers everything
• Humans supervise - Check on progress with bd list and bd dep tree, but don’t micromanage

In human-managed workflows, issues are planning artifacts. In agent-managed workflows, issues are memory - preventing agents from forgetting tasks during long coding sessions.

Traditional issue trackers were built for human project managers. bd is built for autonomous agents.

Architecture: JSONL + SQLite

bd uses a dual-storage approach:

• JSONL files (.beads/issues.jsonl) - Source of truth, committed to git
• SQLite database (.beads/*.db) - Ephemeral cache for fast queries, gitignored

This gives you:

• ✅ Git-friendly storage - Text diffs, AI-resolvable conflicts
• ✅ Fast queries - SQLite indexes for dependency graphs
• ✅ Simple workflow - Export before commit, import after pull
• ✅ No daemon required - In-process SQLite, ~10-100ms per command

When you run bd create, it writes to SQLite. Before committing to git, run bd export to sync to JSONL. After pulling, run bd import to sync back to SQLite. Git hooks can automate this.

Export/Import (JSONL Format)

bd can export and import issues as JSON Lines (one JSON object per line). This is perfect for git workflows and data portability.

Export Issues

# Export all issues to stdout
bd export --format=jsonl

# Export to file
bd export --format=jsonl -o issues.jsonl

# Export filtered issues
bd export --format=jsonl --status=open -o open-issues.jsonl

Issues are exported sorted by ID for consistent git diffs.

Import Issues

# Import from stdin
cat issues.jsonl | bd import

# Import from file
bd import -i issues.jsonl

# Skip existing issues (only create new ones)
bd import -i issues.jsonl --skip-existing

Import behavior:

• Existing issues (same ID) are updated with new values
• New issues are created
• All imports are atomic (all or nothing)

Handling ID Collisions

When importing issues, bd detects three types of situations:

1. Exact matches - Same ID, same content (idempotent, no action needed)
2. New issues - ID doesn’t exist in database yet
3. Collisions - Same ID but different content (requires resolution)

Collision detection:

# Preview collisions without making changes
bd import -i issues.jsonl --dry-run

# Output shows:
# === Collision Detection Report ===
# Exact matches (idempotent): 5
# New issues: 3
# COLLISIONS DETECTED: 2
#
# Colliding issues:
#   bd-10: Fix authentication bug
#     Conflicting fields: [title, priority, status]
#   bd-15: Add dashboard widget
#     Conflicting fields: [description, assignee]

Resolution strategies:

Option 1: Automatic remapping (recommended for branch merges)

# Automatically resolve collisions by renumbering incoming issues
bd import -i issues.jsonl --resolve-collisions

# bd will:
# 1. Keep existing issues unchanged
# 2. Assign new IDs to colliding incoming issues (bd-25, bd-26, etc.)
# 3. Update ALL text references and dependencies to use new IDs
# 4. Report the remapping:
#
# === Remapping Report ===
# Issues remapped: 2
#
# Remappings (sorted by reference count):
#   bd-10 → bd-25 (refs: 3)
#   bd-15 → bd-26 (refs: 7)
#
# All text and dependency references have been updated.

Option 2: Manual resolution

# 1. Check for collisions first
bd import -i branch-issues.jsonl --dry-run

# 2. Edit JSONL to resolve manually:
#    - Rename IDs in the JSONL file
#    - Or merge content into existing issues
#    - Or skip colliding issues

# 3. Import after manual fixes
bd import -i branch-issues.jsonl

The collision resolution algorithm:

When using --resolve-collisions, bd intelligently remaps colliding issues to minimize updates:

1. Detects collisions - Compares ID and content (title, description, status, priority, etc.)
2. Scores references - Counts how many times each ID is referenced in:

• Text fields (description, design, notes, acceptance criteria)
• Dependency records (both as source and target)

1. Renumbers by score - Issues with fewer references are remapped first
2. Updates all references - Uses word-boundary regex to replace old IDs:

• Text fields: “See bd-10 for details” → “See bd-25 for details”
• Dependencies: bd-5 → bd-10 becomes bd-5 → bd-25
• Handles edge cases: Distinguishes bd-10 from bd-100, bd-1000, etc.

Branch merge workflow:

This is particularly useful when merging branches where both sides created issues with the same IDs:

# On main branch: bd-1 through bd-20 exist
git checkout main
bd export -o .beads/issues.jsonl

# On feature branch: Also has bd-1 through bd-20 (diverged)
git checkout feature-branch
bd export -o .beads/issues.jsonl

# Merge branches
git checkout main
git merge feature-branch
# Git shows conflict in .beads/issues.jsonl

# Resolve the conflict in Git (keep both sides for different issues, etc.)
# Then import with collision resolution:
bd import -i .beads/issues.jsonl --resolve-collisions

# Result: Issues from feature-branch get new IDs (bd-21+)
# All cross-references are automatically updated

Important notes:

• Collisions are safe by default - import fails unless you use --resolve-collisions
• Use --dry-run to preview changes before applying
• The algorithm preserves the existing database (existing issues are never renumbered)
• All text mentions and dependency links are updated automatically
• Word-boundary matching prevents false replacements (bd-10 won’t match bd-100)

JSONL Format

Each line is a complete JSON issue object:

{"id":"bd-1","title":"Fix login bug","status":"open","priority":1,"issue_type":"bug","created_at":"2025-10-12T10:00:00Z","updated_at":"2025-10-12T10:00:00Z"}
{"id":"bd-2","title":"Add dark mode","status":"in_progress","priority":2,"issue_type":"feature","created_at":"2025-10-12T11:00:00Z","updated_at":"2025-10-12T12:00:00Z"}

Git Workflow

Recommended approach: Use JSONL export as source of truth, SQLite database as ephemeral cache (not committed to git).

Setup

Add to .gitignore:

.beads/*.db
.beads/*.db-*

Add to git:

.beads/issues.jsonl

Workflow

# Export before committing
bd export -o .beads/issues.jsonl
git add .beads/issues.jsonl
git commit -m "Update issues"
git push

# Import after pulling
git pull
bd import -i .beads/issues.jsonl

Automated with Git Hooks

Create .git/hooks/pre-commit:

#!/bin/bash
bd export -o .beads/issues.jsonl
git add .beads/issues.jsonl

Create .git/hooks/post-merge:

#!/bin/bash
bd import -i .beads/issues.jsonl

Make hooks executable:

chmod +x .git/hooks/pre-commit .git/hooks/post-merge

Why JSONL?

• ✅ Git-friendly: One line per issue = clean diffs
• ✅ Mergeable: Concurrent appends rarely conflict
• ✅ Human-readable: Easy to review changes
• ✅ Scriptable: Use jq, grep, or any text tools
• ✅ Portable: Export/import between databases

Handling Conflicts

When two developers create new issues:

{"id":"bd-1","title":"First issue",...}
{"id":"bd-2","title":"Second issue",...}
+{"id":"bd-3","title":"From branch A",...}
+{"id":"bd-4","title":"From branch B",...}

Git may show a conflict, but resolution is simple: keep both lines (both changes are compatible).

See TEXT_FORMATS.md for detailed analysis of JSONL merge strategies and conflict resolution.

Examples

Check out the examples/ directory for:

• Python agent - Full agent implementation in Python
• Bash agent - Shell script agent example
• Git hooks - Automatic export/import on git operations
• Branch merge workflow - Handle ID collisions when merging branches
• Claude Desktop MCP - MCP server integration (coming soon)

FAQ

Why not just use GitHub Issues?

GitHub Issues requires internet, has API rate limits, and isn’t designed for agents. bd works offline, has no limits, and gives you bd ready --json to instantly find unblocked work. Plus, bd’s distributed database means agents on multiple machines share state via git—no API calls needed.

How is this different from Taskwarrior?

Taskwarrior is excellent for personal task management, but bd is built for AI agents:

• Explicit agent semantics: discovered-from dependency type, bd ready for queue management
• JSON-first design: Every command has --json output
• Git-native sync: No sync server setup required
• Merge-friendly JSONL: One issue per line, AI-resolvable conflicts
• Extensible SQLite: Add your own tables without forking

Can I use bd without AI agents?

Absolutely! bd is a great CLI issue tracker for humans too. The bd ready command is useful for anyone managing dependencies. Think of it as “Taskwarrior meets git.”

What happens if two agents work on the same issue?

The last agent to export/commit wins. This is the same as any git-based workflow. To prevent conflicts:

• Have agents claim work with bd update <id> --status in_progress
• Query by assignee: bd ready --assignee agent-name
• Review git diffs before merging

For true multi-agent coordination, you’d need additional tooling (like locks or a coordination server). bd handles the simpler case: multiple humans/agents working on different tasks, syncing via git.

Do I need to run export/import manually?

No! Install the git hooks from examples/git-hooks/:

cd examples/git-hooks && ./install.sh

The hooks automatically export before commits and import after pulls/merges/checkouts. Set it up once, forget about it.

Can I track issues for multiple projects?

Yes! Each project is completely isolated. bd uses project-local databases:

cd ~/project1 && bd init --prefix proj1
cd ~/project2 && bd init --prefix proj2

Each project gets its own .beads/ directory with its own database and JSONL file. bd auto-discovers the correct database based on your current directory (walks up like git).

Multi-project scenarios work seamlessly:

• Multiple agents working on different projects simultaneously → No conflicts
• Same machine, different repos → Each finds its own .beads/*.db automatically
• Agents in subdirectories → bd walks up to find the project root (like git)

Limitation: Issues cannot reference issues in other projects. Each database is isolated by design. If you need cross-project tracking, initialize bd in a parent directory that contains both projects.

Example: Multiple agents, multiple projects, same machine:

# Agent 1 working on web app
cd ~/work/webapp && bd ready --json    # Uses ~/work/webapp/.beads/webapp.db

# Agent 2 working on API
cd ~/work/api && bd ready --json       # Uses ~/work/api/.beads/api.db

# No conflicts! Completely isolated databases.

How do I migrate from GitHub Issues / Jira / Linear?

We don’t have automated migration tools yet, but you can:

1. Export issues from your current tracker (usually CSV or JSON)
2. Write a simple script to convert to bd’s JSONL format
3. Import with bd import -i issues.jsonl

See examples/ for scripting patterns. Contributions welcome!

Is this production-ready?

Current status: Alpha (v0.9.0)

bd is in active development and being dogfooded on real projects. The core functionality (create, update, dependencies, ready work, collision resolution) is stable and well-tested. However:

• ⚠️ Alpha software - No 1.0 release yet
• ⚠️ API may change - Command flags and JSONL format may evolve before 1.0
• ✅ Safe for development - Use for development/internal projects
• ✅ Data is portable - JSONL format is human-readable and easy to migrate
• 📈 Rapid iteration - Expect frequent updates and improvements

When to use bd:

• ✅ AI-assisted development workflows
• ✅ Internal team projects
• ✅ Personal productivity with dependency tracking
• ✅ Experimenting with agent-first tools

When to wait:

• ❌ Mission-critical production systems (wait for 1.0)
• ❌ Large enterprise deployments (wait for stability guarantees)
• ❌ Long-term archival (though JSONL makes migration easy)

Follow the repo for updates and the path to 1.0!

How does bd handle scale?

bd uses SQLite, which handles millions of rows efficiently. For a typical project with thousands of issues:

• Commands complete in <100ms
• Full-text search is instant
• Dependency graphs traverse quickly
• JSONL files stay small (one line per issue)

For extremely large projects (100k+ issues), you might want to filter exports or use multiple databases per component.

Can I use bd for non-code projects?

Sure! bd is just an issue tracker. Use it for:

• Writing projects (chapters as issues, dependencies as outlines)
• Research projects (papers, experiments, dependencies)
• Home projects (renovations with blocking tasks)
• Any workflow with dependencies

The agent-friendly design works for any AI-assisted workflow.

Troubleshooting

bd: command not found

bd is not in your PATH. Either:

# Check if installed
go list -f {{.Target}} github.com/steveyegge/beads/cmd/bd

# Add Go bin to PATH
export PATH="$PATH:$(go env GOPATH)/bin"

# Or reinstall
go install github.com/steveyegge/beads/cmd/bd@latest

database is locked

Another bd process is accessing the database, or SQLite didn’t close properly. Solutions:

# Find and kill hanging processes
ps aux | grep bd
kill <pid>

# Remove lock files (safe if no bd processes running)
rm .beads/*.db-journal .beads/*.db-wal .beads/*.db-shm

failed to import: issue already exists

You’re trying to import issues that conflict with existing ones. Options:

# Skip existing issues (only import new ones)
bd import -i issues.jsonl --skip-existing

# Or clear database and re-import everything
rm .beads/*.db
bd import -i .beads/issues.jsonl

Git merge conflict in issues.jsonl

When both sides add issues, you’ll get conflicts. Resolution:

1. Open .beads/issues.jsonl
2. Look for <<<<<<< HEAD markers
3. Most conflicts can be resolved by keeping both sides
4. Each line is independent unless IDs conflict
5. For same-ID conflicts, keep the newest (check updated_at)

Example resolution:

# After resolving conflicts manually
git add .beads/issues.jsonl
git commit
bd import -i .beads/issues.jsonl  # Sync to SQLite

See TEXT_FORMATS.md for detailed merge strategies.

bd ready shows nothing but I have open issues

Those issues probably have open blockers. Check:

# See blocked issues
bd blocked

# Show dependency tree
bd dep tree <issue-id>

# Remove blocking dependency if needed
bd dep remove <from-id> <to-id>

Remember: Only blocks dependencies affect ready work.

Permission denied on git hooks

Git hooks need execute permissions:

chmod +x .git/hooks/pre-commit
chmod +x .git/hooks/post-merge
chmod +x .git/hooks/post-checkout

Or use the installer: cd examples/git-hooks && ./install.sh

bd init fails with “directory not empty”

.beads/ already exists. Options:

# Use existing database
bd list  # Should work if already initialized

# Or remove and reinitialize (DESTROYS DATA!)
rm -rf .beads/
bd init

Export/import is slow

For large databases (10k+ issues):

# Export only open issues
bd export --format=jsonl --status=open -o .beads/issues.jsonl

# Or filter by priority
bd export --format=jsonl --priority=0 --priority=1 -o critical.jsonl

Consider splitting large projects into multiple databases.

Agent creates duplicate issues

Agents may not realize an issue already exists. Prevention strategies:

• Have agents search first: bd list --json | grep "title"
• Use labels to mark auto-created issues: bd create "..." -l auto-generated
• Review and deduplicate periodically: bd list | sort

True deduplication logic would require fuzzy matching - contributions welcome!

Documentation

• README.md - You are here! Complete guide
• TEXT_FORMATS.md - JSONL format analysis and merge strategies
• GIT_WORKFLOW.md - Historical analysis of binary vs text approaches
• EXTENDING.md - Database extension patterns
• Run bd quickstart for interactive tutorial

Development

# Run tests
go test ./...

# Build
go build -o bd ./cmd/bd

# Run
./bd create "Test issue"

License

MIT

Credits

Built with ❤️ by developers who love tracking dependencies and finding ready work.

Inspired by the need for a simpler, dependency-aware issue tracker.