NAME

README · Architecture · Agents · Skills & Commands · Plugins

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TypeScript + Bash orchestration that runs AI agents — Ollama for code generation, Claude for planning and triage — in parallel, in dependency order.

How it works

/implement triggers a multi-step pipeline. Claude handles triage and planning; the TypeScript orchestrator runs Ollama agents in dependency order; Claude applies the generated output.

Step 0   Triage      Claude reads graph.json (BFS depth=2), writes triage_ts.md
Step 1   Plan        Parallel Claude planners write task_context_<domain>.md
Step 1.5 Orchestrate npm start runs Ollama agents in dependency order,
                     writes ollama_output_<domain>.md
Step 2   Code        Parallel Claude coders apply ollama_output_<domain>.md,
                     write coder_output_<domain>.md
Step 2.5 Pre-review  Standards compliance check
Step 3   Build       npx tsc --noEmit
Step 4   Review      Fast review per file; deep review for flagged files
Step 5   Fix loop    Max 3 rounds, circuit breaker on repeat errors
Step 6   Finalize    git diff + track savings

Agents communicate through files in .claude/context/. Each step reads file paths from the previous step, not the full content.

Source layout

src/
  types/index.ts        AgentDomain, KNOWN_DOMAINS, Role, AgentTask,
                        AgentResult (done|skipped|failed|blocked), TriageResult
  agents/
    AgentRunner.ts      Wraps call_ollama.sh via spawn; 5 min timeout; 10 MB output limit
    TriageAgent.ts      BFS depth=2 on graph.json; writes triage_ts.md; CLI via import.meta.url
  core/
    DependencyGraph.ts  Kahn topological sort; duplicate domain detection
    Orchestrator.ts     Reads task_context_<domain>.md; circuit breaker for failed deps;
                        reviews ollama_output_<domain>.md after all domains complete
  index.ts              CLI entry point

Domain dependencies

Domain	Depends on
coder	(none)
unit-tester	coder
doc-writer	coder
devops	coder, unit-tester, doc-writer

Domains within the same dependency level run concurrently. If a domain fails, its dependents are marked blocked and skipped.

Requirements

• Node.js 20+ with tsx
• Claude Code CLI
• Ollama installed and running
• jq
• Python 3 with graphify package (optional, for knowledge graph updates)

Installation

git clone https://github.com/Mybono/ai-orchestrator ~/Projects/ai-orchestrator
cd ~/Projects/ai-orchestrator
./scripts/install.sh

Or with curl:

curl -sSL https://raw.githubusercontent.com/Mybono/ai-orchestrator/main/scripts/install.sh | bash

install.sh creates symlinks from ~/.claude/ into the repo. A git pull in the repo directory updates all tooling immediately.

Configuration

Model routing is controlled by llm-config.json in the repo root:

{
  "models": {
    "coder":        "hf.co/bartowski/Qwen2.5-Coder-14B-Instruct-GGUF:IQ4_XS",
    "reviewer":     "qwen2.5-coder:7b",
    "pre-reviewer": "qwen2.5-coder:7b",
    "quick-coder":  "qwen2.5-coder:7b",
    "commit":       "qwen2.5-coder:7b",
    "triage":       "llama3.1:8b",
    "embedding":    "mxbai-embed-large"
  }
}

Changing a model name takes effect immediately — no restart needed. See Architecture for details.

Development

npm run build                                    # compile TypeScript
npm run typecheck                                # tsc --noEmit, no output files
npm start "coder,unit-tester"                    # run TS orchestrator for given domains
npx tsx src/agents/TriageAgent.ts "<task>"       # run triage standalone

local-commit generates a commit message via Ollama and calls scripts/graphify-update.sh before staging, so the updated graph.json is included in the same commit.

License

MIT

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README · Architecture · Agents · Skills & Commands · Plugins