ticks
A multiplayer-first issue tracker for AI coding agents.
brew install pengelbrecht/tap/ticks
tk init
tk ready
Why Ticks?
The Problem
AI coding agents lose context between sessions. They forget what they were working on, what's blocked, and what they discovered along the way. Traditional issue trackers like GitHub Issues aren't designed for this—they're slow to query, require network access, and aren't optimized for agent workflows.
Ticks gives agents persistent memory that survives session restarts, context compaction, and even switching between different AI tools. Issues live in your repo as simple JSON files, tracked by git, queryable in milliseconds.
Why Not GitHub Issues?
- Speed:
tk ready returns in ~35ms with 1000 issues. GitHub API calls take seconds.
- Offline: Works without network access.
- Agent-native: Commands like
tk next and --json output are designed for agents.
- Git-tracked: Issues travel with your code. Branch, merge, fork—issues come along.
- Multiplayer: Built-in owner scoping for multi-agent collaboration.
GitHub recently added dependencies and sub-issues, but the API latency makes it impractical for agents that need to check status frequently.
Why Ticks Over Beads?
Ticks is a radically simpler alternative to beads. Both solve the same core problem—giving AI agents persistent memory across sessions—but with different tradeoffs.
Ticks is multiplayer-first: designed for teams where multiple developers each have their own agents. Commands show your issues by default (tk ready vs tk ready --all), making it natural for a team to share a repo without stepping on each other's work.
Both support multi-agent workflows via git worktrees—ticks' lack of a daemon is actually an advantage here, as beads' daemon doesn't work correctly with worktrees. The difference is ticks adds owner scoping for teams of humans, not just teams of agents.
|
ticks |
beads |
| Multiplayer |
Owner scoping for teams |
Single-user focused |
| Storage |
One JSON file per issue |
JSONL + SQLite |
| Conflicts |
Native git merge driver |
Custom sync logic |
| Background process |
None |
Daemon required |
| Codebase |
~1k lines Go |
~130k lines Go |
| Agent hooks |
Optional tk snippet |
Complex plugin system |
| Query speed |
~35ms |
~67ms |
Benchmarks
With 1000 issues, median times (ms):
| Operation |
ticks |
beads |
ready |
35 |
69 |
list |
37 |
72 |
list --label |
35 |
67 |
list --label-any |
35 |
67 |
list --title-contains |
36 |
67 |
list --desc-contains |
35 |
66 |
list --notes-contains |
36 |
66 |
create |
15 |
91 |
update |
27 |
68 |
Full benchmark methodology and results in benchmarks/.
Choose ticks if you want:
- Team-friendly multiplayer with owner scoping
- Simple flat files you can
cat and debug
- No daemon, no SQLite, no infrastructure
- Git-native conflict resolution
- Minimal agent integration (just add output of
tk snippet to CLAUDE.md)
Choose beads if you need:
- Advanced multi-agent coordination
- Automatic context injection via hooks
Install
Homebrew (macOS/Linux)
brew install pengelbrecht/tap/ticks
Shell script (macOS/Linux)
curl -fsSL https://raw.githubusercontent.com/pengelbrecht/ticks/main/install.sh | sh
PowerShell (Windows)
irm https://raw.githubusercontent.com/pengelbrecht/ticks/main/install.ps1 | iex
From source
go install github.com/pengelbrecht/ticks/cmd/tk@latest
Quick Start
tk init # Initialize in a git repo
tk create "Fix auth timeout" -t bug -p 1 # Create an issue
tk ready # See what's ready to work on
tk next # Get the single next task
tk update <id> --status in_progress # Claim work
tk note <id> "Investigating token expiry" # Log progress
tk close <id> --reason "Fixed" # Complete
Upgrading
# Shell/Go installs: self-update
tk upgrade
# Homebrew
brew upgrade pengelbrecht/tap/ticks
Agent Integration
Run tk snippet to get CLAUDE.md content for AI agent integration:
tk snippet >> CLAUDE.md
This tells agents to use ticks for persistent tracking instead of TodoWrite.
The tk next command is particularly useful for agents:
tk next # Next ready task
tk next --epic # Next ready epic
tk next EPIC_ID # Next ready task in a specific epic
Agent-Human Workflow
Ticks supports structured handoff between agents and humans. Tasks can be routed to humans for approval, input, review, or manual work—and returned to agents with feedback.
Awaiting States
| State |
When Used |
work |
Human must complete the task |
approval |
Agent done, needs sign-off |
input |
Agent needs information |
review |
PR needs code review |
content |
UI/copy needs human judgment |
escalation |
Agent found issue, needs direction |
checkpoint |
Phase complete, verify before next |
Creating Tasks for Humans
# Task requiring approval before closing
tk create "Update auth flow" --requires approval
# Task assigned directly to human
tk create "Configure AWS credentials" --awaiting work
Human Workflow
# See what needs attention
tk list --awaiting
tk next --awaiting
# Review and respond
tk show <id>
tk approve <id>
tk reject <id> "Soften the error messages"
Notes for Feedback
tk note <id> "Use Stripe for payments" --from human
Commands
| Command |
Description |
tk init |
Initialize ticks in current repo |
tk create "title" |
Create a new issue |
tk next |
Show next ready task |
tk ready |
List all ready tasks |
tk show <id> |
Show issue details |
tk update <id> |
Update issue fields |
tk note <id> "msg" |
Append a note |
tk close <id> |
Close an issue |
tk block <id> <blocker> |
Add a dependency |
tk graph <epic> |
Show dependency graph |
tk list |
List issues with filters |
tk view |
Interactive TUI |
tk run <epic> |
Run agent on epic |
tk run --board |
Start web board UI |
tk run --cloud |
Board with cloud sync |
tk approve <id> |
Approve awaiting tick |
tk reject <id> |
Reject with feedback |
tk snippet |
Output CLAUDE.md content |
All commands support --help for options and --json for machine-readable output.
TUI
tk view
j/k or arrows: navigate
space/enter: fold/unfold epics
/: search
z: focus on epic
a: approve awaiting tick
x: reject awaiting tick
q: quit
Web Board
# Run with local board UI
tk run --board
# Run agent on epic with board
tk run abc --board
# Board on custom port
tk run --board --port 8080
Opens a web kanban board at http://localhost:3000 with real-time updates. Built with Lit web components and Shoelace UI.
- Drag-free kanban columns: Blocked, Agent Queue, In Progress, Needs Human, Done
- Real-time SSE updates when ticks change
- Mobile-responsive with tab navigation
- Keyboard navigation (
hjkl, ? for help)
- PWA support for offline use
See internal/tickboard/ui/README.md for development docs.
Cloud Sync
Access your ticks from anywhere at ticks.sh.
Setup
- Get a token from https://ticks.sh/settings
- Add to
~/.ticksrc:
token=your-token-here
- Run with
--cloud flag:
tk run abc --cloud # Agent + board + cloud sync
tk run --cloud # Board + cloud sync, no agent
How It Works
- Local
tk run --cloud connects to Cloudflare Durable Object
- File changes sync to cloud in real-time (~50ms)
- Cloud UI edits sync back to local
- Works offline—changes queue and sync on reconnect
Privacy
- Ticks stored in Cloudflare Durable Objects
- Only accessible with your token
- Project isolation enforced
- No telemetry or analytics
Dependency Graph
See parallelization opportunities for an epic:
tk graph <epic-id>
Output shows tasks organized into "waves"—groups that can be executed in parallel:
Epic: Implement auth
Stats: 5 tasks, 3 waves, max 2 parallel
Wave 1 (ready now) (2 parallel)
○ abc P1 Design database schema
○ def P2 Set up OAuth provider
Wave 2
⊘ ghi P1 Implement user model ← abc
Wave 3
⊘ jkl P2 Integration tests ← ghi
Critical path: 3 waves (minimum sequential steps)
Use --json for machine-readable output (useful for agents planning parallel work).
Parallel Execution
Run multiple tasks concurrently using git worktrees for isolation:
tk run abc123 --parallel 3 # Run 3 tasks in parallel
Each parallel worker gets its own git worktree, preventing file conflicts between concurrent tasks. Changes are merged back to the main branch as tasks complete.
How It Works
tk run analyzes the dependency graph to find tasks that can run in parallel
- Creates isolated git worktrees for each worker
- Spawns agents that work independently without file conflicts
- Merges completed work back to the main branch
- Proceeds to the next wave of parallelizable tasks
Planning Parallel Work
Use tk graph to understand how many parallel workers make sense:
tk graph abc123
The "max parallel" stat tells you the optimal --parallel value. Setting it higher than the maximum parallelizable tasks at any wave just wastes resources.
Combining with Other Flags
# Parallel execution with cost limit
tk run abc123 --parallel 3 --max-cost 10.00
# Parallel execution in watch mode
tk run abc123 --parallel 2 --watch
# Parallel execution with iteration limit per task
tk run abc123 --parallel 4 --max-iterations 20
Search and Filtering
tk list --label-any backend,auth --all
tk list --title-contains "auth" --all
tk list --status in_progress
tk ready --owner alice
Multiplayer
Commands show your issues by default. Use --all to see everyone's:
tk ready --all # All ready tasks
tk next --all # Next task from anyone
tk list --all # All issues
Assign work with --owner:
tk create "Review API" --owner alice
tk list --owner bob
Environment Variables
| Variable |
Description |
TICK_OWNER |
Override owner detection |
TICK_DIR |
Override .tick directory location |
NO_COLOR |
Disable colored output |
How It Works
Each issue is a JSON file in .tick/issues/<id>.json. Git handles merges naturally since different issues are different files. For the rare case of conflicting edits to the same issue, ticks provides a custom merge driver that intelligently combines changes.
Acknowledgements
Ticks is inspired by beads by Steve Yegge, which pioneered the idea of giving AI coding agents persistent memory through git-tracked issue management. Ticks takes a simpler approach to the same problem.
License
MIT