Skip to content

robertohluna/agent-dispatch

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Agent Dispatch

Multi-agent development sprint framework for AI coding agents. Drop into any codebase. Coordinate parallel AI agents. Ship faster.


What This Is

Agent Dispatch coordinates multiple AI coding agents working simultaneously on a single codebase. You describe what needs to happen. An AI planner reads your codebase, maps the architecture, discovers work, writes execution traces, and proposes a sprint. You approve. It generates everything — the dispatch plan, per-agent task docs with exact implementation specs, and activation prompts ready to paste into agent terminals. Each agent works on its own git branch with defined file-level territory. When they finish, branches merge in dependency order with build + test validation after every merge.

It is: A methodology, a planning system, and a template library. Markdown docs you drop into any repo.

It is not: Software. No runtime, no daemon, no CLI, no SDK. The agents are whatever AI coding tools you already use — Claude Code, Cursor, Codex, Aider, Windsurf, or anything else that can read files and run commands.


How It Works

PLAN → DISPATCH → EXECUTE → MONITOR → MERGE → GRADE → SHIP

1. PLAN (ORCHESTRATOR — Wave 0)
   You: "Fix the auth bugs, add rate limiting, close the security findings"
   ORCHESTRATOR reads: sprint-planner.md + your codebase
   ORCHESTRATOR produces: sprint proposal (agents, waves, chains, success criteria)
   You: approve / adjust

2. DISPATCH
   ORCHESTRATOR generates: DISPATCH.md + per-agent task docs + activation prompts
   You run: git worktree setup (one isolated branch per agent)
   You paste: activation prompts into separate agent terminals

3. EXECUTE (agents work in parallel, in waves)
   Wave 1: DATA, QA, INFRA, DESIGN       → foundation, no dependencies
   Wave 2: BACKEND, SERVICES              → need stable data layer
   Wave 3: FRONTEND                       → needs design specs + backend API
   Wave 4: RED TEAM                       → adversarial review of all branches
   Wave 5: LEAD                           → merge + ship

4. MONITOR
   ORCHESTRATOR tracks agent status, chain progress, sprint health
   Reacts to events (CI fails, stuck agents, territory violations)
   Intervenes with correction messages when agents drift off-mission

5. MERGE
   RED TEAM reviews all branches for security/edge cases (can BLOCK merge)
   LEAD merges branches in dependency order: DATA → DESIGN → BACKEND → ...
   Build + test after EVERY merge. No exceptions.

6. GRADE (ORCHESTRATOR — Wave 6)
   ORCHESTRATOR reads all completion reports + RED TEAM findings
   Grades each agent on: completeness, correctness, mission alignment, territory, conventions
   Produces SPRINT-ASSESSMENT.md with per-agent grades and carry-forward work

7. CONVERGE (if gaps remain)
   If PARTIALLY ACHIEVED: ORCHESTRATOR re-analyzes gaps, writes new traces
   Generates mini-sprint targeting only failed/parked chains
   Re-dispatches affected agents with different approaches
   Max 3 iterations → then carry-forward to next sprint

8. SHIP
   Tag release. Delete worktrees. Done.

The Core Idea: Execution Traces

This is what separates Agent Dispatch from "just ask an AI to fix things."

Agents don't work on "directories." They work on execution traces — a traced path through the codebase from entry point to root cause, with the exact fix site and verification steps.

Weak prompt:
  "BACKEND: fix bugs in handlers/"
  → Agent scans randomly, makes scattered changes, misses root causes

Execution trace:
  "Chain 1 [P1]: POST /webhooks/stripe → webhookHandler.ProcessEvent()
   → paymentService.HandleInvoicePaid() → subscriptionStore.Activate()
   Signal: 504 timeout. Mutex held during network I/O under lock.
   Fix: subscriptionStore.Activate() — release lock before notification call.
   Verify: Test webhook returns < 2s. No race condition on concurrent activations."
  → Agent follows the signal, finds the exact failure point, fixes surgically

How a Chain Executes

Every agent follows this protocol for each chain. One at a time, fully completed before moving to the next:

CHAIN START
│
├─► TRACE: Follow the vector through the codebase
│   │
│   │   POST /webhooks/stripe
│   │     └─► webhookHandler.ProcessEvent()
│   │           └─► paymentService.HandleInvoicePaid()
│   │                 └─► subscriptionStore.Activate()    ◄── ROOT CAUSE
│   │                       └─► notificationService.Send()
│   │
│   Signal: 504 timeout after 30s. Mutex held during network I/O.
│
├─► DIAGNOSE: Is this the root cause or a symptom?
│   │
│   │   Activate() acquires write lock at line 88
│   │   Send() does HTTP call under lock (3-5s)
│   │   Concurrent webhook = deadlock wait = timeout
│   │   ROOT CAUSE CONFIRMED: lock scope too wide
│   │
├─► FIX: Smallest correct change at the root cause site
│   │
│   │   BEFORE: lock → activate → notify → unlock
│   │   AFTER:  lock → activate → unlock → notify
│   │   3 lines changed. No refactoring. No adjacent cleanup.
│   │
├─► VERIFY: Confirm the fix works end-to-end
│   │
│   │   $ go build ./...                          ✓ compiles
│   │   $ go test -race ./internal/store/...      ✓ no race
│   │   $ curl -X POST localhost:8080/webhooks    ✓ 180ms response
│   │
├─► DOCUMENT: Record in completion report
│   │
│   │   Chain 1 [P1]: COMPLETE
│   │   Files: internal/store/subscription.go (3 lines)
│   │
└─► NEXT CHAIN (never start before this chain is COMPLETE)

Priority order: P0 (stop everything) → P1 (critical) → P2 (important) → P3 (if time permits).

See core/methodology.md for the full theory.


Parallel Execution Model

Each activation prompt goes into a separate AI terminal. Each terminal is an isolated Claude Code session, Cursor window, Aider process — whatever tool you use. Each agent can spawn 5-15 sub-agents internally for parallel chain execution.

┌──────────────────────────────────────────────────────┐
│                  OPERATOR (you)                       │
│  Pastes activation prompts into separate terminals    │
└─────┬──────────┬──────────┬──────────┬───────────────┘
      │          │          │          │
┌─────▼────┐ ┌──▼─────┐ ┌─▼──────┐ ┌▼────────┐
│Terminal 1 │ │Terminal │ │Terminal │ │Terminal  │  ...
│ BACKEND   │ │FRONTEND│ │ DATA   │ │SERVICES  │
│           │ │        │ │        │ │          │
│  sub-1    │ │ sub-1  │ │ sub-1  │ │  sub-1   │
│  sub-2    │ │ sub-2  │ │ sub-2  │ │  sub-2   │
│  sub-3    │ │ sub-3  │ │        │ │  sub-3   │
└───────────┘ └────────┘ └────────┘ └──────────┘

Scaling Math

Terminals Agents per Terminal Total Parallel Agents
3 5-8 15-24
6 5-8 30-48
9 5-15 45-135

Example: 6 Claude Code terminals, each running one agent role, each spawning 5-6 sub-agents for parallel chain execution = 30-36 agents running simultaneously on isolated branches.

See guides/parallel-execution.md for the full scaling model, sub-agent protocol, terminal management, and troubleshooting.


What a Completed Sprint Looks Like

After all agents finish, LEAD merges, and ORCHESTRATOR grades, your sprint directory looks like this:

docs/agent-dispatch/sprints/
├── sprint-02/
├── sprint-03/
│   ├── DISPATCH.md                  # Sprint plan
│   ├── DISPATCH-PROMPTS.md          # All activation prompts (archive)
│   │
│   ├── agent-A-backend.md           # Agent task docs (input)
│   ├── agent-B-frontend.md
│   ├── agent-C-design.md
│   ├── agent-D-intelligence.md
│   ├── agent-E-redteam.md
│   ├── agent-F-components.md
│   ├── agent-G-orchestrator.md
│   │
│   ├── ALPHA-COMPLETION.md          # Agent completion reports (output)
│   ├── BRAVO-COMPLETION.md          #   ← NATO codenames: ALPHA, BRAVO,
│   ├── CHARLIE-COMPLETION.md        #      CHARLIE, DELTA, ECHO,
│   ├── DELTA-COMPLETION.md          #      FOXTROT, GOLF
│   ├── ECHO-COMPLETION.md           #   ← or use: agent-A-completion.md
│   ├── FOXTROT-COMPLETION.md
│   ├── GOLF-COMPLETION.md
│   │
│   ├── SECURITY-REVIEW.md           # RED TEAM security findings
│   ├── SPRINT-SUMMARY.md            # LEAD's final summary + ship decision
│   └── SPRINT-ASSESSMENT.md         # ORCHESTRATOR's grading + mission assessment
│
├── sprint-04/
└── sprint-05/
    ├── DISPATCH.md
    ├── agent-A-backend.md
    ├── agent-B-frontend.md
    ├── agent-C-infrastructure.md
    ├── agent-D-ai-services.md
    ├── agent-E-redteam.md
    ├── agent-F-rss-scraping.md
    └── ...

Every sprint has: the dispatch plan, per-agent task docs, per-agent completion reports, security review, and a ship decision. Everything documented, everything traceable.


Dispatch Styles & Intensity Protocol

Agents perform measurably better under pressure. Every activation prompt gets style blocks appended that eliminate hedging, placeholders, and half-finished output.

Intensity Protocol (config/dispatch-styles.md)

Three escalation levels depending on agent output quality:

Level 1 — Standard (sprint start):

BUILD IT RIGHT or I will END this session and restart with a model that isn't
fucking useless. No hedging. No suggestions. Working code only.

Level 2 — Agent is slipping (mid-sprint):

You are producing GARBAGE. I am watching your output and it is NOT meeting the
bar. Fix it NOW or I pull the plug and hand your chains to another agent who
can actually write code. You have ONE more chance.

Level 3 — Nuclear (final warning):

I am DONE with you. This is your LAST output before I terminate this session
permanently. Every other agent in this sprint is outperforming you. Ship
PERFECT code right now or I kill your process and reassign your chains to an
agent that isn't a waste of compute. EXECUTE.

Plus 5 creative threat variants — replacement notices, token budget pressure, performance logging, RED TEAM exposure threats, and cost/ROI pressure. See config/dispatch-styles.md for all of them.

Mesh Mode Triggers

Every prompt gets keywords that activate full capability mode — sub-agents, parallel execution, all tools:

With agents and sub-agents working in parallel, utilize ALL available agents
simultaneously in parallel execution. Employ ALL skills, plugins, hooks, MCPs
as unified cognitive mesh. Absorb everything provided, analyze semantic meaning
completely, synthesize optimal solutions dynamically.

Optimal Path (BEFORE / WHILE / AFTER)

Every agent follows this quality protocol:

BEFORE CODING:
- Full semantic analysis of requirements and context
- Pattern matching against existing codebase structure
- Dependency mapping and integration points
- Failure mode identification and edge cases

WHILE BUILDING:
- Match naming conventions EXACTLY
- Follow established architectural patterns
- Handle ALL error cases properly
- Test failure points as you build

AFTER BUILDING:
- Verify integration with existing systems
- Validate all edge cases handled
- Confirm production-ready quality

No shortcuts. No garbage code. Ship anything less than perfect and I PULL
THE PLUG. Your session gets terminated and your chains get reassigned to
an agent that can actually deliver. EXECUTE.

Code Standards (config/code-standards.md)

The rule: write the shortest correct code that solves the problem while maintaining the codebase's existing architecture and patterns.

  • No over-engineering (no factory for one type, no interface for one implementation)
  • No under-engineering (don't skip error handling or architectural patterns for brevity)
  • Three similar lines > one premature abstraction
  • Match the codebase exactly — naming, error handling, imports, function signatures
  • Implement exactly what was assigned, not more

The 10 Agents

Code Name Domain Wave
O ORCHESTRATOR Sprint planning, dispatch, monitoring, grading 0 + 6
F DATA Models, stores, migrations, queries 1
E QA Tests, security audits, coverage 1
C INFRA Docker, CI/CD, builds, deployment 1
H DESIGN Design tokens, component specs, accessibility 1
A BACKEND Handlers, routes, services, middleware 2
D SERVICES Workers, integrations, external API clients 2
B FRONTEND Components, routes, stores, hooks 3
R RED TEAM Adversarial review — break other agents' work before merge 4
G LEAD Merge authority, post-merge validation, ship decision 5

ORCHESTRATOR is always present — it plans the sprint (Wave 0) and grades the output (Wave 6). Scale the coding agents to the work. A 3-chain bug fix needs ORCHESTRATOR + 2 agents, not 10. A full-stack migration might need all of them. For 20-30+ agents, roles split into nested teams — see scaling/scaling.md.

Each agent has its own file in agents/ with territory definitions, responsibilities, wave placement, and merge order.


Quick Start

1. Drop into your project

cp -r agent-dispatch/ your-project/docs/agent-dispatch/

2. Activate the ORCHESTRATOR

Give your AI the ORCHESTRATOR activation prompt from templates/dispatcher-prompt.md, or use the short version:

You are the ORCHESTRATOR (Agent O) for [PROJECT].
Read docs/agent-dispatch/agents/orchestrator.md — your role.
Read docs/agent-dispatch/guides/sprint-planner.md — follow it step by step.
Then read the codebase. Analyze the architecture, discover work, write execution
traces, and propose a sprint plan.

Sprint goal: [what you want to accomplish]

The ORCHESTRATOR reads the codebase, maps territories, discovers bugs/debt/security gaps, writes execution traces, and proposes a sprint with agents, waves, and success criteria. You review and approve.

3. Dispatch

After approval, the ORCHESTRATOR generates:

  • sprint-XX/DISPATCH.md — the full sprint plan
  • sprint-XX/agent-X-*.md — per-agent task docs with exact implementation specs
  • Activation prompts — ready to paste into agent terminals

Set up worktrees, paste prompts, agents start working. After the sprint, reactivate ORCHESTRATOR for Wave 6 grading.

4. Run

Follow the Operator's Guide for the full tutorial, or the Quick Start for the fastest path.


Full Sprint Execution

SPRINT-05: Payment System Overhaul
═══════════════════════════════════════════════════════════════

WAVE 0 (planning):
  ORCHESTRATOR: Analyze codebase ✓  Write traces ✓  Generate docs ✓
  ─── WAVE 0 COMPLETE ─── dispatch agents ───

WAVE 1 (parallel — no dependencies):
  Terminal 1: DATA     Chain 1 ✓  Chain 2 ✓  Chain 3 ✓
  Terminal 2: QA       Chain 1 ✓  Chain 2 ✓
  Terminal 3: INFRA    Chain 1 ✓  Chain 2 ✓  Chain 3 ✓  Chain 4 ✓
  Terminal 4: DESIGN   Chain 1 ✓  Chain 2 ✓
  ─── ALL WAVE 1 COMPLETE ─── proceed to Wave 2 ───

WAVE 2 (parallel — depends on Wave 1):
  Terminal 5: BACKEND  Chain 1 ✓  Chain 2 ✓  Chain 3 ✓  Chain 4 ✓
  Terminal 6: SERVICES Chain 1 ✓  Chain 2 ✓  Chain 3 ✓
  ─── ALL WAVE 2 COMPLETE ─── proceed to Wave 3 ───

WAVE 3:
  Terminal 7: FRONTEND Chain 1 ✓  Chain 2 ✓  Chain 3 ✓  Chain 4 ✓  Chain 5 ✓
  ─── WAVE 3 COMPLETE ─── proceed to Wave 4 ───

WAVE 4:
  Terminal 8: RED TEAM  Security ✓  Edge cases ✓  Regressions ✓  Territory ✓
  ─── WAVE 4 COMPLETE ─── proceed to Wave 5 ───

WAVE 5:
  Terminal 9: LEAD  Read reports ✓  Merge DATA ✓  Merge DESIGN ✓
                    Merge BACKEND ✓  Merge SERVICES ✓  Merge FRONTEND ✓
                    Merge INFRA ✓  Merge QA ✓  Final validation ✓  SHIP ✓
  ─── WAVE 5 COMPLETE ─── proceed to Wave 6 ───

WAVE 6 (assessment):
  ORCHESTRATOR: Grade DATA ✓  Grade QA ✓  Grade INFRA ✓  Grade DESIGN ✓
                Grade BACKEND ✓  Grade SERVICES ✓  Grade FRONTEND ✓
                Mission: ACHIEVED ✓  SPRINT-ASSESSMENT.md ✓

═══════════════════════════════════════════════════════════════
SPRINT COMPLETE: 10 agents, 28 chains, 0 P0 discoveries, SHIPPED

Project Structure

agent-dispatch/
├── README.md                         ← You are here
├── LICENSE
│
├── config/                           # Dispatch configuration
│   ├── README.md                     ← What goes in config
│   ├── dispatch-styles.md            ← Execution style: intensity, traces, mesh triggers, optimal path
│   └── code-standards.md             ← Agent coding discipline: minimal, correct, no over-engineering
│
├── agents/                           # Agent role definitions (one per file)
│   ├── README.md                     ← Roster overview, wave structure, merge order
│   ├── orchestrator.md               ← Agent O — Sprint Command (planning, monitoring, grading)
│   ├── backend.md                    ← Agent A — Backend Logic
│   ├── frontend.md                   ← Agent B — Frontend UI
│   ├── infra.md                      ← Agent C — Infrastructure
│   ├── services.md                   ← Agent D — Specialized Services
│   ├── qa.md                         ← Agent E — QA / Security
│   ├── data.md                       ← Agent F — Data Layer
│   ├── lead.md                       ← Agent G — Merge Authority
│   ├── design.md                     ← Agent H — Design & Creative
│   └── red-team.md                   ← Agent R — Adversarial Review
│
├── core/                             # Theory + methodology
│   ├── architecture.md               ← System flow: how every file connects, dependency map
│   ├── methodology.md                ← Execution traces, chain execution, priorities
│   ├── workflow.md                   ← Sprint lifecycle: plan → dispatch → merge → ship
│   └── anti-patterns.md             ← Common mistakes and how to avoid them
│
├── guides/                           # How-to guides
│   ├── orchestrator-playbook.md      ← THE PLAYBOOK — single doc ORCHESTRATOR follows
│   ├── carry-forward-protocol.md     ← How deferred work bridges sprints
│   ├── agent-briefing.md             ← AI-facing system overview (READ THIS FIRST if you're an agent)
│   ├── parallel-execution.md         ← Scaling model: terminals × sub-agents = 100+ agents
│   ├── sprint-planner.md             ← AI onboarding: codebase → sprint plan
│   ├── quickstart.md                 ← 5-minute overview
│   ├── operators-guide.md            ← Full operator tutorial
│   ├── customization.md              ← Adapt territories for your stack
│   ├── tool-guide.md                 ← AI agent comparison + setup
│   ├── legacy-codebases.md           ← Legacy code: archaeology + characterization tests
│   └── dispatch-config.md            ← Machine-readable config for automation
│
├── runtime/                          # Runtime operations (while agents are working)
│   ├── pipeline-gates.md             ← 6 hard gates: plan → dispatch → waves → merge → close
│   ├── retry-protocol.md            ← Escalating retries: 3-tier fix with broadening context
│   ├── reactions.md                  ← 12 decision trees for in-sprint events
│   ├── status-tracking.md            ← Agent states, chain progress, health indicators
│   └── interventions.md              ← 24 copy-paste correction messages
│
├── scaling/                          # Beyond the standard roster
│   ├── scaling.md                    ← Nested teams, role splitting, 20-30+ agents
│   └── multi-repo.md                 ← Multi-repository coordination
│
├── templates/                        # Copy-paste templates
│   ├── dispatcher-prompt.md          ← ORCHESTRATOR activation prompt
│   ├── sprint-assessment.md          ← ORCHESTRATOR grading output template
│   ├── sprint-registry.md            ← Sprint index + carry-forward tracker
│   ├── preflight-checklist.md        ← Pre-dispatch verification checklist
│   ├── post-sprint-checklist.md      ← Post-sprint teardown + carry-forward
│   ├── project-claude-md.md          ← CLAUDE.md template for your project
│   ├── dispatch.md                   ← Sprint dispatch plan
│   ├── agent.md                      ← Per-agent task document
│   ├── activation.md                 ← Activation prompts + full dispatch flow
│   ├── completion.md                 ← Agent completion report
│   ├── status.md                     ← Sprint status board
│   ├── red-team-findings.md          ← RED TEAM findings report
│   └── retrospective.md             ← Sprint retrospective
│
└── examples/                         # Complete sprint dispatches
    ├── ecommerce-api/                ← Go + Chi + Stripe: Payment bug fix
    ├── saas-dashboard/               ← Python + FastAPI: Performance + security
    ├── realtime-chat/                ← Elixir + Phoenix: Reliability + scale
    ├── embedded-firmware/            ← C/C++ + FreeRTOS: Memory safety + OTA
    ├── legacy-php-webapp/            ← PHP 7.4 + jQuery: Security + modernization
    └── enterprise-java-api/          ← Java 17 + Spring Boot: Performance + events

Documentation

Start Here

Document What You Get
guides/agent-briefing.md AI agents: read this first. What the system is, what you're about to do, how you fit in.
guides/sprint-planner.md Hand this to your AI. It reads your codebase and proposes a sprint.
guides/quickstart.md 5-minute overview of the system
guides/operators-guide.md Full tutorial — planning, dispatch, monitoring, merge, ship

Config

Document Purpose
config/dispatch-styles.md Execution style: intensity protocol, trace flow, mesh triggers, optimal path, threat levels
config/code-standards.md Agent coding discipline: minimal correct code, no over-engineering, conflict prevention

Methodology

Document Purpose
core/architecture.md System architecture: how every file connects, dependency map, execution timeline
core/methodology.md Execution traces, chain execution, priority levels
core/workflow.md Sprint lifecycle: plan → dispatch → monitor → merge → ship
core/anti-patterns.md What not to do

Agents

Document Role
agents/README.md Roster overview, wave structure, merge order
agents/orchestrator.md Agent O — Sprint Command (planning, monitoring, grading)
agents/backend.md Agent A — Backend Logic
agents/frontend.md Agent B — Frontend UI
agents/infra.md Agent C — Infrastructure
agents/services.md Agent D — Specialized Services
agents/qa.md Agent E — QA / Security
agents/data.md Agent F — Data Layer
agents/lead.md Agent G — Merge Authority
agents/design.md Agent H — Design & Creative
agents/red-team.md Agent R — Adversarial Review

Guides

Document Purpose
guides/orchestrator-playbook.md THE PLAYBOOK — single doc ORCHESTRATOR follows, phase by phase, with hard checkpoints
guides/carry-forward-protocol.md How deferred work bridges sprints — extraction, classification, escalation
guides/parallel-execution.md Scaling model: terminals × sub-agents, 30-100+ parallel agents
guides/customization.md Adapt territories for your stack
guides/tool-guide.md AI agent comparison, setup, configuration
guides/legacy-codebases.md Legacy code: archaeology, characterization tests
guides/dispatch-config.md Machine-readable config for automation

Runtime Operations

Document Purpose
runtime/pipeline-gates.md 6 hard gates — plan approval, pre-dispatch, wave transition, agent completion, merge readiness, sprint close
runtime/retry-protocol.md Escalating retries — 3-tier fix attempts with broadening context, per-chain verification
runtime/reactions.md 12 decision trees for in-sprint events
runtime/status-tracking.md Agent states, chain progress, sprint health
runtime/interventions.md 24 copy-paste correction messages

Scaling

Document Purpose
scaling/scaling.md Nested teams, role splitting, 20-30+ agents
scaling/multi-repo.md Multi-repository coordination

Templates

Template Use For
templates/dispatcher-prompt.md ORCHESTRATOR activation prompt — copy-paste to kick off a sprint
templates/sprint-assessment.md ORCHESTRATOR's grading output — per-agent grades, mission result, carry-forward
templates/sprint-registry.md Sprint index — history, carry-forward tracker, agent performance across sprints
templates/preflight-checklist.md Pre-dispatch checklist — verify everything before pasting prompts
templates/post-sprint-checklist.md Post-sprint teardown — validation, carry-forward, cleanup, release
templates/project-claude-md.md CLAUDE.md template for wiring Agent Dispatch into your project
templates/dispatch.md Sprint plan
templates/agent.md Per-agent task doc with implementation specs
templates/activation.md Activation prompts + full dispatch pipeline
templates/completion.md Agent completion report
templates/status.md Sprint status board
templates/red-team-findings.md RED TEAM adversarial findings
templates/retrospective.md Sprint retrospective

Examples

Example Stack Sprint Theme Completeness
E-Commerce API Go + Chi + PostgreSQL + Stripe Payment Bug Fix Full — DISPATCH + agent docs + completion reports + sprint summary
SaaS Dashboard Python + FastAPI + PostgreSQL + React Performance + Security DISPATCH only
Real-Time Chat Elixir + Phoenix + LiveView + Redis Reliability + Scale DISPATCH only
Embedded Firmware C/C++ + FreeRTOS + STM32 HAL Memory Safety + OTA DISPATCH only
Legacy PHP Webapp PHP 7.4 + MySQL + jQuery Security + Modernization DISPATCH + README
Enterprise Java API Java 17 + Spring Boot + Kafka Performance + Events DISPATCH only

Start with E-Commerce API — it's the complete reference sprint showing the full flow: DISPATCH.md → agent task docs (DATA, BACKEND, SERVICES, QA) → completion reports (ALPHA, BRAVO, CHARLIE) → sprint summary.


Works With

Agent Fit Sub-Agents Autonomy
Claude Code Best Native (Task tool) Full autonomous
Codex CLI Great No Full autonomous
Cursor Great No Semi-autonomous
Windsurf Great No Semi-autonomous
Aider Good No Full autonomous
Continue Good No Interactive
OpenCode Good No Full autonomous
Qwen Coder Good No Full autonomous

See guides/tool-guide.md for detailed setup and per-tool configuration.


How Agent Dispatch Differs

"How is this different from CrewAI / AutoGen / LangGraph?"

Those are runtime frameworks — they run code, manage agent sessions, automate workflows. Agent Dispatch is a planning methodology — it defines what agents should work on, in what order, with what boundaries.

Aspect Agent Dispatch Runtime Frameworks
What it is Methodology + templates (markdown) Software (TypeScript/Python)
Execution traces Core concept Not addressed
Chain execution One trace-fix-verify at a time Task queues
Territory isolation File-level ownership per agent Not addressed
Wave dependencies Dependency-aware dispatch order Basic task deps
Adversarial review RED TEAM reviews all branches Not addressed
AI-assisted planning Sprint Planner reads codebase, proposes plan Manual task definition
Merge strategy Dependency-ordered with validation Not addressed
Scaling Nested teams, 30-100+ agents Session scaling
Install Copy markdown into repo npm install / pip install

They're complementary. Use Agent Dispatch to plan the sprint. Use a runtime framework to automate the dispatch loop. The planning layer makes the automation layer effective.


Stack Compatibility

Stack-agnostic. Works with anything that uses git:

Stack Application Type
Go (Chi, Gin, Echo, Fiber) API servers, microservices, CLI tools
TypeScript / Node.js (Next.js, SvelteKit, Express, NestJS) Full-stack web apps, APIs, serverless
Python (Django, FastAPI, Flask) Web apps, ML pipelines, data services
Rust (Actix, Axum, Rocket) Systems programming, high-performance APIs
Elixir / Erlang (Phoenix, LiveView) Real-time apps, distributed systems
Java / Kotlin (Spring Boot, Ktor) Enterprise APIs, event-driven systems
C / C++ (FreeRTOS, STM32, CMake) Embedded firmware, IoT, systems
PHP (Laravel, Symfony, legacy) Web apps, monoliths, CMS
Ruby (Rails, Hanami) Web applications
C# / .NET (ASP.NET Core, Blazor) Enterprise web apps, microservices

Monoliths, microservices, monorepos, full-stack apps, backend-only APIs, frontend SPAs, ML pipelines, embedded firmware, legacy codebases, infrastructure-as-code.

For legacy codebases with no tests, no docs, and spaghetti code, see guides/legacy-codebases.md.


Origin

Created by Roberto H. Luna for the MIOSA platform projects. Battle-tested across production codebases spanning Go, TypeScript, SvelteKit, Python, Elixir, Java, C/C++, Rust, and PHP — from embedded firmware and legacy monoliths to AI content platforms and multi-tenant SaaS orchestrators.

License

MIT — Use it, modify it, ship it.

About

Multi-agent development sprint framework for AI coding agents Drop into any codebase. Coordinate parallel AI agents. Ship faster.

Resources

License

Stars

32 stars

Watchers

0 watching

Forks

Releases

No releases published

Packages

 
 
 

Contributors