ai-dispatch (aid)
aid is a Multi-AI CLI Team Orchestrator written in Rust. It lets a human dispatcher or a primary AI such as Claude Code delegate work to multiple AI CLI tools, track progress, inspect artifacts, enforce methodology, and iterate through one consistent interface.
Licensed under the MIT License.
Why aid?
Without an orchestrator, a multi-agent CLI workflow breaks down fast:
- Managing multiple AI CLIs is chaotic because every tool has different flags, output formats, and calling conventions.
- No unified progress visibility means background work is mostly blind until a process exits.
- No cost tracking across tools makes token usage and spend hard to monitor over time.
- Manual worktree management for parallel code tasks adds friction to every implementation run.
- No methodology enforcement means prompt discipline, testing standards, and review habits drift between agents.
Quick Start
Prerequisites
Install Rust (1.85 or later, required for edition 2024) and whichever AI CLIs you want aid to orchestrate. aid auto-detects supported agents on your PATH: gemini, codex, opencode, cursor, kilo, codebuff, and auto.
Install
# From crates.io (recommended)
# Or one-liner
|
Then run the interactive setup wizard:
This detects installed agents, configures your OpenRouter API key (for aid query), and shows your ready-to-use configuration.
Install From Source
Setup for Claude Code
aid ships with a recommended Claude Code prompt that enables orchestrator-first workflows. Copy it into your project or global CLAUDE.md:
# Project-level (recommended)
# Or global (applies to all projects)
See claude-prompt.md for the full recommended prompt with agent selection guide, batch file format, and completion notification pattern.
If you want an isolated state directory while testing:
First Research Task
Run a lightweight research task and write the answer to a file:
For quick ad hoc exploration, use aid ask:
First Coding Task
Dispatch a coding task into its own git worktree and ask aid to verify automatically:
Watch, Inspect, Iterate
Track progress while the agent runs, then inspect the artifacts:
Run With Auto Agent Selection
Let aid choose the best available agent using its task classifier and capability matrix:
# [aid] Auto-selected agent: cursor (reason: frontend task (medium) → cursor (score: 9))
# [aid] Auto-selected model: auto (complexity: medium)
auto classifies each prompt into one of eight task categories — research, simple-edit, complex-impl, frontend, debugging, testing, refactoring, documentation — estimates complexity (low/medium/high), then scores every installed agent against a capability matrix. The best-scoring agent wins, with adjustments for budget mode, rate limits, and historical success rates.
The model tier is auto-selected based on complexity: low → cheap/free models, medium → standard, high → premium.
Core Concepts
Agents
An agent is the CLI backend that actually performs work. aid normalizes command construction, logging, usage extraction, and completion handling behind one adapter trait.
Examples:
Tasks
Every dispatch becomes a tracked task with a stable ID like t-1234. Tasks can run in the foreground, in the background, or as retries with feedback.
Examples:
Workgroups
Workgroups are shared context containers. Create a workgroup once, then dispatch multiple tasks that inherit the same background constraints and notes.
Examples:
Agent Memory
Project-scoped persistent knowledge that auto-injects into agent prompts. Four types:
- Discovery — bug patterns, API behaviors, gotchas
- Convention — code style, naming, architecture decisions
- Lesson — what worked/failed (30-day TTL)
- Fact — versions, configs, endpoints
Shared Findings
Workgroup-scoped ephemeral evidence for investigation collaboration. Agents emit [FINDING] tags in their output, which are auto-captured and injected into subsequent task prompts within the same workgroup.
# Manual posting
# Agent auto-capture: any agent output containing [FINDING] is saved
# Example agent output: "[FINDING] WBTC as input causes all outputs to panic"
# List findings
# Findings also appear in workgroup summaries
Fast Query (v5.8)
Instant LLM queries via OpenRouter — no agent subprocess startup. Two tiers:
# Free tier (default) — $0, uses openrouter/free
# Auto tier — paid, OpenRouter selects best model
# Explicit model
# Save response as workgroup finding
Configure models and API key via aid setup or ~/.aid/config.toml:
[]
= "openrouter/free"
= "openrouter/auto"
= "sk-or-v1-..."
Workspace Isolation (AID_GROUP)
Set AID_GROUP to automatically scope all commands to a workgroup without passing --group everywhere:
Worktree Management
aid manages git worktrees for parallel conflict-free task execution. Worktrees can be created automatically with --worktree or managed explicitly:
# Explicit worktree lifecycle
WT=
# Automatic worktree (created per-task)
aid merge auto-merges the worktree branch into the current branch and cleans up the worktree directory. Failed tasks auto-cleanup their worktrees. Worktree escape detection warns if an agent accidentally modifies the main repo.
Codebuff Plugin (Optional)
codebuff is an optional agent that requires separate installation. It bridges the Codebuff SDK to aid's event protocol via a Node.js wrapper.
# 1. Install the plugin
&& &&
# 2. Get an API key at https://www.codebuff.com/api-keys
# 3. Add to your shell profile to persist across sessions
# 4. Run a task
The plugin outputs codex-compatible JSONL events, so aid show, aid watch, and the TUI work seamlessly. If CODEBUFF_API_KEY is not set, aid will show setup instructions instead of failing silently.
Cost note: Codebuff SDK v0.10 runs sub-agents (Context Pruner, Nit Pick Nick) automatically, which can make even simple tasks expensive. Use --mode free via --budget flag for cost-sensitive work.
TUI Stats View
Press s in the TUI to toggle the stats/charts view, which shows:
- Cost by Agent — horizontal bar chart of spend per agent
- Success Rate — bar chart of done/merged percentage per agent
- Budget Usage — gauge bars for configured budget windows
- Summary — task counts, total/today cost, token totals, and a cost sparkline
Press a to toggle between today-only and all-time task views.
Skills
Skills are methodology files loaded from ~/.aid/skills/ and appended to the effective prompt under a --- Methodology --- section. They make agent behavior more consistent across runs.
Skills are auto-injected by default: coding agents (codex, opencode, cursor, kilo, codebuff) get the implementer skill, and gemini gets the researcher skill. Use --skill to add extras or --no-skill to disable auto-injection.
Examples:
Teams
Teams provide knowledge context and soft agent preferences for different workflows. Each team has preferred agents (scoring boost in auto-selection), capability overrides, behavioral rules, and a knowledge directory.
# Create a team
# Configure in ~/.aid/teams/dev.toml
[]
= "dev"
= "Development Team"
= ["codex", "opencode", "cursor"]
= "codex"
# Always-injected constraints (no relevance filtering)
= [
"Do NOT run cargo fmt or any auto-formatter",
"Only git add files you explicitly modified",
]
# Override agent scoring for this team's tasks
[]
= 10
= 7
Team knowledge is stored in ~/.aid/teams/<id>/knowledge/ and auto-injected (relevance-filtered) when --team is used. Rules are always injected without filtering.
Project Profiles
Project-level configuration via .aid/project.toml sets defaults for all tasks dispatched within a repository. Built-in profiles expand into sensible presets:
# Initialize in current repo
# → creates .aid/project.toml + .aid/knowledge/KNOWLEDGE.md
[]
= "my-app"
= "production" # hobby | standard | production
= "dev"
= "rust"
= [
"File size limit: 300 lines per file",
]
| Profile | Verify | Budget | Rules |
|---|---|---|---|
hobby |
- | $5/day, prefer_budget | - |
standard |
auto |
$20/day | All new functions must have tests |
production |
cargo test / npm test |
$50/day | Tests required, no unwrap(), cross-review |
Project defaults act as CLI fallbacks — explicit flags always win. Rules are always injected into agent prompts (no relevance filtering). Knowledge in .aid/knowledge/ is relevance-filtered like team knowledge.
Agent Store
aid includes a GitHub-backed community agent store for discovering and installing custom agent definitions.
# Browse all available agents
# Search for specific agents
# Preview an agent's configuration
# Install an agent (with optional version pinning)
# Check for updates
Packages can bundle agent configs, skills, and hooks together. Installing a package installs all components and records versions in ~/.aid/store.lock.
Installed agents appear in aid config agents and participate in auto-selection via their capability scores. The store is backed by agent-tools-org/aid-agents — community contributions welcome.
Task Lifecycle Hooks
Define shell hooks that run at key points in the task lifecycle. Hooks receive task JSON on stdin.
Configure hooks in ~/.aid/hooks.toml:
[[]]
= "before_run"
= "~/.aid/hooks/validate.sh"
[[]]
= "after_complete"
= "~/.aid/hooks/notify.sh"
= "codex"
[[]]
= "on_fail"
= "~/.aid/hooks/alert.sh"
Or pass hooks per-task via CLI:
Batch files support hooks in [defaults] and per-task:
[]
= ["before_run:./validate.sh"]
[[]]
= "codex"
= "Implement feature"
= ["after_complete:./notify.sh"]
Hook events:
before_run— runs after task creation, before agent starts. Fails the task if hook exits non-zero.after_complete— runs after task completes (after verify). Best-effort.on_fail— runs when task fails. Best-effort.
Prompt Budget
Check skill token overhead with aid config prompt-budget:
Token usage is also logged during dispatch:
[aid] Skills loaded: 1 skills, ~323 tokens
[aid] Context injected: 2 files, ~450 tokens
Milestones
aid injects milestone guidance into prompts so agents emit progress markers that the watcher can parse and surface in aid watch, aid board, and the TUI.
Expected milestone format:
[MILESTONE] mapped the failing code path
[MILESTONE] implemented the fix
[MILESTONE] verified tests and summarized the diff
Agent Memory (Blackboard)
aid includes a shared memory system that lets agents build up knowledge across tasks. Memories are stored in SQLite alongside tasks and automatically injected into agent prompts when relevant.
Memory types:
- Discovery — new findings about the codebase or environment
- Convention — patterns, naming rules, or style decisions
- Lesson — mistakes to avoid (auto-expires after 30 days)
- Fact — verified constants (addresses, versions, config values)
Agents can emit memories by including [MEMORY: type] content tags in their output. These are automatically extracted and deduplicated after task completion.
# Manual memory management
Memories are auto-injected into prompts during dispatch. Agents see a --- Relevant Memories --- section with matching memories from previous tasks.
Verify Status
Tasks now track verification outcome separately from execution status via verify_status:
- Skipped — no
--verifywas set - Pending — verify hasn't run yet
- Passed — verify command succeeded
- Failed — verify command failed (task may still be marked Done)
The board displays [VFAIL] next to tasks that completed but failed verification, making it easy to distinguish "agent crashed" from "code doesn't pass checks".
Command Reference
| Command | Purpose | Typical use |
|---|---|---|
aid run |
Dispatch one task to an agent. Supports --bg, --verify, --worktree, --on-done, --no-skill, --retry, --context, and --skill. |
aid run codex "Implement retry logic" --dir . --worktree feat/retry --verify auto |
aid batch |
Dispatch a TOML batch file with DAG dependency scheduling. Auto-creates a workgroup and archives the file to ~/.aid/batches/. |
aid batch tasks.toml --parallel --wait |
aid watch |
Follow live progress in text mode, quiet wait mode, or the TUI. | aid watch --tui, aid watch t-1234, aid watch --quiet --group wg-a3f1 |
aid board |
List tracked tasks with filters. Auto-detects zombie tasks. Use --stream for scrollback-preserving output. |
aid board --today, aid board --stream --group wg-a3f1 |
aid show |
Inspect one task's summary, diff, output, raw log, or AI-generated explanation. Diffs show changes vs main branch. | aid show t-1234 --diff, aid show t-1234 --output, aid show t-1234 --explain |
aid usage |
Render task-history usage plus configured budget windows. Supports --agent, --period, and --json. |
aid usage, aid usage --agent codex --period 7d --json |
aid retry |
Re-dispatch a failed task with explicit feedback. | aid retry t-1234 --feedback "Reproduce the failure before editing." |
aid respond |
Send interactive input to a running background task. | aid respond t-1234 "yes" |
aid benchmark |
Dispatch the same task to multiple agents and compare results. | aid benchmark "Fix the bug" --agents codex,opencode --dir . |
aid output |
Show task output directly. | aid output t-1234 |
aid ask |
Run a quick research or exploration task, optionally with file context. | aid ask "What changed in src/main.rs?" --files src/main.rs |
aid mcp |
Start the stdio MCP server so another tool can call aid natively. |
aid mcp |
aid merge |
Mark done task(s) as merged. Supports --group for bulk merge, --approve for interactive approval via hiboss. |
aid merge t-1234, aid merge --group wg-a3f1 --approve |
aid clean |
Remove old tasks/events and orphaned worktrees/logs. Supports --dry-run. |
aid clean --older-than 7 --worktrees |
aid config |
Inspect agent profiles, skills, pricing (with --update to fetch latest), and prompt token budget. |
aid config agents, aid config pricing --update |
aid worktree |
Explicit worktree lifecycle management: create, list, remove. | aid worktree create feat/x, aid worktree list, aid worktree remove feat/x |
aid group |
Workgroup management: create, list, show, update, delete, summary, finding, broadcast. | aid group create dispatch -c "Shared rollout notes", aid group summary wg-a3f1 |
aid store |
Browse, install (with version pinning), update community agent/skill packages. | aid store install community/aider@1.0.0, aid store update --apply |
aid upgrade |
Upgrade aid to latest crates.io version (checks for running tasks). | aid upgrade, aid upgrade --force |
aid agent |
Manage custom agent definitions: list, show, add, remove, fork. | aid agent list, aid agent fork codex --as codex-fast |
aid export |
Export a task with full context (prompt, events, output, diff). Supports markdown and JSON. | aid export t-1234, aid export t-1234 --format json --output task.json |
aid memory |
Manage shared agent memory: add, list, search, update, forget. | aid memory add discovery "Finding", aid memory search "query" |
aid tree |
Show retry chain as an ASCII tree with agent/status/cost per node. | aid tree t-1234 |
aid query |
Fast LLM query via OpenRouter (no agent startup). Free and auto tiers. | aid query "question", aid query --auto "question" |
aid setup |
Interactive setup wizard. Detects agents, sets API keys, initializes skills and templates. | aid setup |
aid team |
Manage teams: create, list, show, delete. Teams inject knowledge and rules into agent prompts. | aid team list, aid team show dev, aid team create ops |
aid project |
Initialize and show project configuration (.aid/project.toml). Profiles expand into verify/budget/rules defaults. |
aid project init, aid project show |
aid stop |
Stop a running task. Graceful by default (SIGTERM + 5s + SIGKILL), --force for immediate SIGKILL. |
aid stop t-1234, aid stop t-1234 --force |
aid steer |
Inject guidance into a running PTY task. | aid steer t-1234 "focus on tests" |
Best Practices / Methodology
The Orchestrator Pattern
The most effective aid workflow is:
- Plan the work — decompose into 5–10 independent subtasks.
- Dispatch agents in parallel via batch files.
- Monitor with background watch (auto-notifies on completion).
- Review artifacts with
aid show --diff. - Iterate with retries, or re-dispatch with
--best-offor critical tasks.
Think big — 6–10 parallel agents finish faster and often produce better results than one agent doing everything serially. Each agent stays focused on a small, well-defined task.
A practical sequence looks like this:
# Phase 1: Research (free)
# Phase 2: Parallel implementation (batch file, 4–6 tasks)
# Phase 3: Background watch (push notification, no polling)
# Phase 4: Review and iterate
For AI orchestrators (Claude Code, etc.): Use aid watch --quiet --group <wg-id> as a background command to get automatic completion callbacks instead of polling aid board.
Quality Tiers
Match effort to task importance:
| Tier | When | Pattern |
|---|---|---|
| Draft | Exploration, prototyping | aid run codex "..." --dir . |
| Standard | Normal development | aid run codex "..." --worktree feat/x --verify auto |
| Reviewed | Important features | aid run codex "..." --verify auto --peer-review gemini |
| Best-of | Critical code paths | aid run codex "..." --best-of 3 --metric "<cmd>" --verify auto |
--best-of N dispatches the same task to N agents (or the same agent N times), runs an optional --metric command on each result, and keeps the best. Use it for bug fixes, core modules, and public APIs where quality matters more than speed.
--peer-review <agent> sends the completed diff to a second agent for scored critique (1–10). Cheap agents like gemini make excellent reviewers.
Agent Selection Guide
auto uses a capability matrix to match agents to task types. The scores below reflect relative strengths (higher = better fit):
| Agent | Research | Simple Edit | Complex Impl | Frontend | Debugging | Testing | Refactoring | Documentation |
|---|---|---|---|---|---|---|---|---|
gemini |
9 | 2 | 3 | 2 | 5 | 3 | 3 | 6 |
codex |
1 | 4 | 9 | 4 | 7 | 7 | 8 | 3 |
opencode |
1 | 8 | 3 | 2 | 4 | 4 | 4 | 5 |
kilo |
1 | 7 | 2 | 2 | 3 | 3 | 3 | 4 |
cursor |
2 | 4 | 7 | 9 | 5 | 5 | 6 | 4 |
codebuff |
2 | 5 | 8 | 7 | 6 | 6 | 7 | 4 |
Additional scoring adjustments: budget mode boosts cheap agents (+4) and penalizes expensive ones (-6); high-complexity tasks boost codex/cursor (+2); rate-limited agents get -10; historical success rates apply ±2-3.
Scores above are per-agent baselines. When auto selects, it also factors in model capability (1-10 scale): Premium (cap 9-10): gpt-5.4, gemini-pro, cursor opus-thinking. Standard (cap 6-8): gpt-4.1, gemini-flash, cursor-auto, opencode/glm-5. Budget (cap 3-5): gpt-4.1-nano, gemini-flash-lite, mimo-free. Final score = (agent_base × 0.4) + (model_capability × 0.6). Use aid config agents to see all model scores.
If you are unsure, start with aid ask or aid run auto, then escalate to a more expensive agent only when the task scope is clear.
Use Skills To Enforce Quality
Skills give you repeatable task methodology instead of relying on ad hoc prompt wording. In practice: use code-scout for unfamiliar code, researcher for fact-heavy work, implementer for minimal diffs, test-writer for regression coverage, and debugger when the task starts with a failure.
Example:
Workgroup-Based Batch Collaboration
A workgroup lets several agents collaborate without repeating shared context. Batch files support DAG dependencies via depends_on — tasks dispatch as soon as their dependencies complete.
Think in phases: research (free) → parallel implementation (4–6 agents) → integration + validation. Each agent gets a focused, bounded task.
[]
= "codex"
= "."
= "cargo check"
# Phase 1: Research (free, fast)
[[]]
= "research"
= "gemini"
= "Analyze src/api/ and src/types.rs. List all public types, relationships, and extension points for adding a webhook system."
= "/tmp/research.md"
= true
# Phase 2: Parallel implementation (all depend on research)
[[]]
= "types"
= "Create src/webhook/types.rs with WebhookConfig, WebhookEvent, WebhookPayload structs. Use serde. Match patterns in src/types.rs. Include tests. Keep < 150 lines."
= "feat/webhook-types"
= ["research"]
[[]]
= "handler"
= "Create src/webhook/handler.rs that sends HTTP POST on task completion. Use reqwest with 10s timeout. Log + continue on error. Include tests. Keep < 200 lines."
= "feat/webhook-handler"
= ["research"]
[[]]
= "config"
= "Add [[webhook]] config parsing to src/config.rs with url, events, headers fields. Include tests for valid/invalid configs. Keep changes < 100 lines."
= "feat/webhook-config"
= ["research"]
[[]]
= "cli"
= "Add 'aid webhook test <url>' command in src/cli.rs and src/cmd/webhook.rs. Send test payload, print result. Keep < 80 lines."
= "feat/webhook-cli"
= ["research"]
# Phase 3: Integration (depends on all implementations)
[[]]
= "integration"
= "Wire webhook handler into task completion flow in src/watcher.rs. Import from src/webhook/. Call on Done/Failed. Add integration test. Keep < 50 lines."
= "feat/webhook-integration"
= ["types", "handler", "config"]
= "cargo test"
# Phase 4: Docs (cheap agent, depends on CLI)
[[]]
= "docs"
= "opencode"
= "Add webhook configuration section to README.md. Show config.toml example and 'aid webhook test' usage. Keep < 40 lines."
= "feat/webhook-docs"
= ["cli"]
Dispatch and monitor:
Batch dispatches with 2+ tasks auto-create a workgroup. The batch file is archived to ~/.aid/batches/.
For critical tasks within a batch, use best_of = 3 to dispatch to multiple agents and keep the best result:
[[]]
= "critical-fix"
= "codex"
= "Fix the race condition in src/store.rs. Add a test that reproduces it."
= "fix/store-race"
= 3
= "cargo test 2>&1 | grep -c 'test.*ok'"
= "cargo test"
Cost Optimization Tips
- Use
aid askorgeminifirst when the task is still exploratory. - Prefer
opencodefor straightforward single-file edits or rename work. - Use
autowhen you want a reasonable default without thinking about the agent first. - Set
[[usage.budget]]entries and checkaid usagebefore long coding sessions. - Reuse workgroups so shared context is stored once instead of repeated in every prompt.
- Use
--modelonly when you need a specific backend behavior or cost profile. - Use
--on-done "command"to get notified when a background task completes (setsAID_TASK_IDandAID_TASK_STATUSenv vars). - Use
--template <name>to wrap prompts with structured methodology (bug-fix, feature, refactor). - Use
--repo /path/to/other-projectto dispatch tasks to a different git repository. - Use
--budgetto force cheaper agent/model selection for low-priority tasks. - Low-value tasks (tests, formatting, linting, docs) auto-detect as budget mode.
- Use
read_only = truein batch tasks for research/review that should not modify files. - Use
aid benchmarkto compare agent quality/speed/cost on the same task. - Use
codebuffwith--budgetfor cost-sensitive tasks — the SDK's sub-agents can make simple tasks expensive in normal mode. - Configure webhooks in
config.tomlfor Slack/Discord notifications on task completion.
Built-in Skills
The default skill directory is ~/.aid/skills/.
| Skill | Description |
|---|---|
test-writer |
Writes tests that target real failure modes, boundary cases, and integration seams instead of mirroring the implementation. |
code-scout |
Maps the entry point, call chain, relevant files, patterns, and risks before a change is made. |
researcher |
Collects verified information from primary sources, records confidence, and extracts facts that are safe to use downstream. |
implementer |
Makes the requested change with a minimal diff, matches the local style, and verifies the result. |
debugger |
Reproduces issues, traces execution, isolates the root cause, and validates the fix with evidence. |
MCP Integration
aid can run as a stdio MCP server so Claude Code or another MCP client can call it without shell parsing.
Start the server directly:
The server exposes these tools:
aid_runaid_boardaid_showaid_retryaid_usageaid_ask
To connect from Claude Code, register aid as a stdio MCP server in your Claude Code MCP configuration. The exact config file location depends on your Claude Code setup, but the server definition itself looks like this:
If you are developing from source instead of using an installed binary, point Claude Code at cargo run:
Once connected, Claude Code can call aid_board to list tasks, aid_show to inspect artifacts, aid_run to dispatch new work, and aid_retry to iterate on failures.
Configuration
By default, aid stores state in ~/.aid/. Override it with AID_HOME when you want a disposable sandbox or separate environment.
Example:
Typical directory layout:
~/.aid/
├── aid.db
├── config.toml
├── logs/
│ ├── t-1234.jsonl
│ └── t-1234.stderr
├── jobs/
│ └── t-1234.json
├── batches/
│ └── 20260313-112850-v15-fixes.toml
├── hooks.toml
├── skills/
│ ├── code-scout.md
│ ├── debugger.md
│ ├── implementer.md
│ ├── researcher.md
│ └── test-writer.md
├── agents/
│ └── *.toml
└── cargo-target/
What lives there:
aid.db: SQLite task, workgroup, event, and memory storelogs/: raw agent output plus stderr capturejobs/: detached background worker specsbatches/: archived batch TOML files (auto-saved after dispatch)hooks.toml: task lifecycle hooks (before_run, after_complete, on_fail)skills/: methodology files loaded by--skill(auto-injected by default)templates/: prompt templates loaded by--template(see default-templates/ for examples)agents/: custom agent TOML definitionscargo-target/: shared Rust build cache for worktree-based tasks
Configure budgets and webhooks in ~/.aid/config.toml:
[[]]
= "codex-dev"
= "codex"
= "24h"
= 20
= 1000000
= 15.0
[[]]
= "claude-code"
= "max"
= "5h"
= 200
= 120
= "2026-03-13T02:00:00+07:00"
= "Track Claude Code separately from aid task history."
Then inspect usage and budget status:
aid usage combines tracked task history with any external counters you record in config.toml.
Webhooks
Configure webhooks to receive notifications when tasks complete:
[[]]
= "slack-notify"
= "https://hooks.slack.com/services/..."
= true
= true
Webhooks fire automatically when background tasks reach a terminal state. Custom headers can be added via headers.
Reliability
aid includes several mechanisms to keep long-running multi-agent workflows healthy:
- Zombie detection:
aid boardautomatically detects dead worker processes (including defunct/zombie state) and marks their tasks as FAILED. - Max task duration: Tasks running longer than 60 minutes are automatically killed and marked FAILED.
- Auto-commit enforcement: Background worktree tasks auto-commit uncommitted changes after completion, preventing lost work.
- Zombie recovery: When a zombie task is detected in a worktree with uncommitted changes, those changes are preserved via auto-commit before marking the task as failed.
- Shared build cache: Rust worktree tasks share
CARGO_TARGET_DIRto avoid redundant recompilation across parallel dispatches. - Worktree escape detection: After each worktree task,
aidchecks if the agent accidentally modified the main repo and warns with a file list. - Auto merge on
aid merge: Merges the worktree branch into the current branch, runs pre-merge verification, and cleans up the worktree directory. - SQLite concurrency:
busy_timeout=5000prevents "database is locked" errors under parallel task access. - Fallback chain: When an agent is rate-limited,
aidsuggests the next capable alternative (codex → cursor → opencode → kilo). - Retry worktree preservation: When a failed task's worktree is auto-cleaned, retries recreate a fresh worktree on the same branch instead of falling back to the main repo.
Architecture
At a high level, aid is a CLI front end over a task manager, a watcher pipeline, persistent storage, and agent-specific adapters.
The diagram below is adapted from DESIGN.md to reflect the current show command name:
┌─────────────────────────────────────┐
│ aid (CLI binary) │
├──────┬──────┬──────┬───────┬────────┬───────────┤
│ run │ watch│ show │ board │ usage │ benchmark │ ← user-facing commands
├──────┴──────┴──────┴───────┴────────┤
│ Task Manager │
│ ┌────────┐ ┌────────┐ ┌────────┐ │
│ │Classif.│ │ Watch │ │ Store │ │
│ │+ Agent │ │ Engine │ │(SQLite)│ │
│ │Registry│ │ │ │ │ │
│ └────┬───┘ └────┬───┘ └────┬───┘ │
│ │ │ │ │
├───────┴──────────┴──────────┴───────┤
│ Agent Adapters │
│ ┌──────┐ ┌─────┐ ┌────────┐ ┌──────┐ ┌────┐ ┌───┐ ┌────────┐ ┌──────┐
│ │Gemini│ │Codex│ │OpenCode│ │Cursor│ │Kilo│ │Codebuff│ │Custom│
│ └──────┘ └─────┘ └────────┘ └──────┘ └────┘ └───┘ └────────┘ └──────┘
└─────────────────────────────────────┘
How the pieces fit together:
- The CLI entrypoint parses commands and routes them to task-oriented handlers such as
run,watch,show,usage, andmcp. - The task classifier categorizes prompts into eight task types and estimates complexity, then the capability matrix scores each agent to pick the best fit.
- The agent registry selects and instantiates adapters for
gemini,codex,opencode,cursor,kilo, andcodebuff. - The watcher parses streamed or buffered output into milestones, tool activity, usage totals, and completion events.
- SQLite keeps task history, workgroups, and events queryable for
board,show,watch,usage, and MCP clients. - Artifact files under
~/.aid/preserve the raw execution trail so the dispatcher can review what actually happened.
That combination is the core value of aid: one binary that turns a pile of incompatible AI CLIs into a trackable, reviewable, and methodology-aware team workflow.