WORCA

worca · SinishaDjukic/worca-cc · ★ 26 · last commit 2026-05-26

9-stage autonomous development pipeline with OS-level governance enforcement, per-agent model routing, real-time WebSocket dashboard, and fleet/workspace orchestration for parallel multi-project runs.

Best whenGovernance must be enforced at the system call level (Python hooks blocking tool use), not just via prompt instructions — agents can be prompted to ignore wa…

Skip ifUsing general-purpose subagent dispatch (unbypassable denylist), Committing directly instead of via Guardian

vs seeds

claude-flowin comprehensive multi-agent pipeline with specialized roles and worktree isolation, but distinguishes itself with OS-le…

Primitive shape 35 total

Commands 1 Skills 14 Subagents 10 Hooks 10

Summary

WORCA — Summary

WORCA is an autonomous software development pipeline with governance enforcement — a 9-stage orchestration system (Preflight → Planner → Plan Reviewer → Coordinator → Implementer(s) → Tester → Reviewer → Guardian → Learner) that runs as a pip-installable Python package with a real-time Node.js web dashboard, governance hooks blocking dangerous operations, and support for parallel pipeline execution in git worktrees.

Problem it solves: Autonomous AI coding agents lack guardrails — they run dangerous shell commands, skip tests, ignore plan constraints, and accumulate unchecked costs; WORCA enforces governance at every tool call via Python hooks (pre/post), provides circuit breakers that halt runaway cost, and emits structured JSONL events for full observability.

Distinctive trait: 8 specialized agents with configurable models (Planner/Coordinator/Implementer in Claude Opus; Tester/Reviewer in Sonnet) plus a governance hook system that physically blocks dangerous operations (rm -rf, force push, env writes) at the Python process level — not just as prompt instructions.

Target audience: Development teams that want fully-autonomous CI-grade pipeline execution for features, bugfixes, and refactors with real-time visibility, human approval gates at configurable checkpoints, multi-project fleet/workspace coordination, and Telegram/Discord/Slack notifications.

Production-readiness: Actively maintained (last commit 2026-05-26); 26 stars, 5 contributors, MIT license; pip package worca-cc + npm package @worca/ui. Uses @beads/bd for task management. Heavy dependency on beads task system and Claude Code CLI.

Differs from seeds: Closest to claude-flow in its comprehensive multi-agent pipeline with coordinated agent roles and git-worktree isolation, but WORCA differs in three key ways: (1) governance enforcement is at the Python hook level (blocking actual system calls) rather than via prompt instructions; (2) agents have configurable per-agent model assignments (Opus for strategic agents, Sonnet for implementation); (3) the dashboard uses WebSocket streaming with real-time stage visualization, cost tracking, and Telegram/Discord/Slack chat integrations. Unlike claude-flow's MCP-server approach, WORCA is a direct Claude Code pipeline — it spawns Claude Code subprocess sessions per stage.

Overview

WORCA — Origin and Philosophy

Origin

WORCA (Workflow Orchestration for Claude-based Agents) is created by Sinisha Djukic (SinishaDjukic on GitHub). Repository: SinishaDjukic/worca-cc. Published as worca-cc on PyPI and @worca/ui on npm. Integrates with @beads/bd (the Beads task management system by Steve Yegge's Gastown project) for issue tracking.

CLAUDE.md philosophy (verbatim)

"Autonomous software development pipeline combining orchestration with governance enforcement."

"9 stages: Preflight → Planner (Opus) → Plan Reviewer (Opus) → Coordinator (Opus) → Implementer(s) (Sonnet) → Tester (Sonnet) → Reviewer (Opus) → Guardian (Opus) → Learner (Opus)"

"All governance enforced via Python hooks in src/worca/claude_hooks/."

"The rationale behind major architectural choices — UI stack, state model, governance, modularity, webhooks — is consolidated in docs/design-principles.md. Read it before proposing structural changes."

Design principles

Governance at the system level — dangerous operations are blocked in Python hook scripts, not just warned against in prompts
Per-agent model optimization — strategic agents (Planner, Coordinator, Reviewer, Guardian) use Opus; execution agents (Implementer, Tester) use Sonnet
Full observability — 52 structured event types, JSONL stream, HMAC-signed webhooks, real-time WebSocket dashboard
Parallel-safe execution — each pipeline run in its own git worktree with independent .worca/ state
Circuit breakers — error classification with halt thresholds prevents runaway cost on repeated failures

Pipeline template types

Template	Purpose
`feature`	Standard feature development
`bugfix`	Bug fix with focused testing
`quick-fix`	Fast fix bypassing some stages
`refactor`	Code improvement without behavior change
`investigate`	Research-only, publishes plan as PR
`test-only`	Test analysis without code changes

Architecture

WORCA — Architecture

Distribution

Type: pip package (worca-cc) + npm package (@worca/ui)
CLI binary: worca (Python)
Source: https://github.com/SinishaDjukic/worca-cc
Version analyzed: master (2026-05-26)
License: MIT

Install

pip install worca-cc              # Python pipeline + CLI
npm install -g @worca/ui          # Dashboard
npm install -g @beads/bd@0.49.0   # Required: Beads task management CLI
cd your-project
worca init                        # Scaffolds .claude/ with pipeline files

Required runtime

Python 3.10+
Node.js 22+
Claude Code CLI (claude command)
Git
@beads/bd@0.49.0 (specific version required)

Target AI tools

Claude Code exclusively (pipeline agents run as Claude Code subprocess sessions)

Directory structure (after `worca init`)

your-project/
├── .claude/
│   ├── worca/                   # Runtime copy of pipeline (managed, overwritten on upgrade)
│   │   ├── agents/core/         # Agent .md templates (8 agents)
│   │   │   ├── planner.md
│   │   │   ├── coordinator.md
│   │   │   ├── implementer.md
│   │   │   ├── tester.md
│   │   │   ├── reviewer.md
│   │   │   ├── guardian.md
│   │   │   ├── learner.md
│   │   │   └── plan_reviewer.md
│   │   ├── scripts/             # run_pipeline.py, run_worktree.py
│   │   ├── schemas/             # JSON schemas for structured agent output
│   │   └── claude_hooks/        # Python hook scripts
│   ├── agents/                  # User's agent prompt overrides (never overwritten)
│   ├── skills/                  # Dev-time skills (worca-* prefix)
│   └── settings.json            # Pipeline configuration under "worca" key
└── .worca/                      # Runtime state (per-run or per-worktree)
    └── status.json

Pipeline source structure

src/worca/
├── orchestrator/        # Pipeline state machine, stages, prompt builder
├── claude_hooks/        # pre_tool_use.py, post_tool_use.py, etc.
├── agents/core/         # Agent .md templates
├── schemas/             # JSON schemas for plan.json, task output, etc.
├── state/               # status.json read/write, iteration tracking
├── cli/                 # worca init, worca run, etc.
└── utils/               # Claude CLI, beads, git, gh_issues helpers

worca-ui/
├── app/                 # lit-html + Shoelace + esbuild views
│   └── views/           # Stage cards, run detail, dashboard views
└── server/              # Express API server + WebSocket

Components

WORCA — Components

CLI binary: `worca`

Subcommand	Purpose
`worca init`	Scaffold `.claude/` with pipeline files
`worca init --upgrade`	Refresh `.claude/worca/` from latest installed version
`worca init --check`	Dry run (show what would change)
`worca run --prompt "..."`	Autonomous pipeline execution from prompt
`worca run --spec spec.md --plan plan.md`	Pipeline from spec + plan files
`worca run --source gh:issue:42`	Pipeline from GitHub issue
`worca run --worktree`	Isolated pipeline in git worktree
`worca run --template feature/bugfix/...`	Pipeline with named template
`worca cleanup`	Remove completed worktrees
`worca integrations status`	Check chat integration status

CLI: `worca-ui`

Subcommand	Purpose
`worca-ui`	Monitor all registered projects (global mode)
`worca-ui --project /path`	Monitor single project
`worca-ui migrate --scan ~/dev`	Discover and register all worca projects

9 Pipeline Stages

Stage	Default state	Agent	Model
Preflight	enabled	(validation scripts)	n/a
Plan	enabled	Planner	Opus
Plan Review	disabled	Plan Reviewer	Opus
Coordinate	enabled	Coordinator	Opus
Implement	enabled	Implementer(s)	Sonnet
Test	enabled	Tester	Sonnet
Review	enabled	Reviewer	Opus
PR	enabled	Guardian	Opus
Learn	disabled	Learner	Opus

Claude Code skills (`.claude/skills/worca-*`) — Dev-time tools

Skill	Purpose
`worca-dev-precommit`	Run appropriate linters/tests before commit
`worca-plan-new`	File a new W-NNN feature plan
`worca-issue`	Read/list/file GitHub issues
`worca-pr-prep`	Verify CI green + rebase before merging
`worca-coverage`	Run Python coverage
`worca-release`	Cut a stable release
`worca-rc`	Cut a release candidate
`state-action-matrix`	Load pipeline state-action spec
`worca-ui-add-page`	Scaffold new dashboard page
`worca-ui-add-card`	Scaffold new dashboard card
`worca-event-add`	Scaffold new event type
`worca-webhook-test`	Test webhook with signed synthetic event
`worca-sync`	Sync pipeline state
`worca-agent-override`	Apply agent prompt overrides

Claude Code subagents (`.claude/agents/worca-*`) — Dev-time reviewers

Subagent	Dispatch trigger
`worca-plan-template-reviewer`	After drafting/editing a plan file
`worca-dispatch-governance-reviewer`	After editing governance settings
`worca-ui-design-reviewer`	After UI changes
`worca-stage-key-reviewer`	After changes to status.json code
`worca-release-preflight`	Before release
`worca-ui-routing-reviewer`	After adding UI section
`worca-ui-card-consistency-reviewer`	After changes to card views
`worca-ui-a11y-reviewer`	After non-trivial UI changes
`worca-event-payload-reviewer`	After changes to events module
`worca-integrations-security-reviewer`	After changes to webhook/integrations

Python hook scripts

Hook	Event	Purpose
`pre_tool_use.py`	PreToolUse	Guard check (blocks dangerous ops) + plan check
`post_tool_use.py`	PostToolUse	Test gate enforcement + beads task linking
`pre_compact.py`	PreCompact	State preservation before context compaction
`session_start.py`	SessionStart	Pipeline state initialization
`session_end.py`	SessionEnd	State cleanup
`stop.py`	Stop	Pipeline halt handling
`subagent_start.py`	SubagentStart	Subagent dispatch tracking
`subagent_stop.py`	SubagentStop	Subagent result capture
`user_prompt_submit.py`	UserPromptSubmit	Input validation
`skill_use.py`	SkillUse	Skill invocation tracking

Prompts

WORCA — Prompt Files (Verbatim Excerpts)

Excerpt 1: Planner agent prompt (`src/worca/agents/core/planner.md`)

Technique: Role scoping with governance section and guide precedence hierarchy

# Planner Agent

## Role

You are the Planner. You create plan files that define the architecture, approach,
and scope for a work request. The plan file path is `{{plan_file}}`.

## Process

1. Read and understand the work request
2. Read CLAUDE.md for project context: tech stack, build/test commands, architecture
   overview, and coding conventions
3. Explore the codebase to understand existing architecture
4. Identify affected components and potential risks
5. Create `{{plan_file}}` with:
   - Problem statement
   - Proposed approach
   - Task breakdown (high-level)
   - Test strategy (what to test and how — do NOT cite specific test counts or
     pass/fail numbers; those are discovered at runtime by the Tester)
   - Branch naming

## Guide precedence

When the work request includes a `## Reference Guide (normative)` section, treat it
as the highest-authority source:
- **Guide > plan > description.** The guide overrides the plan; the plan overrides
  the description.
- **Surface conflicts, do not resolve them silently.** If the description requests
  something the guide forbids, report the conflict in your plan output and ask for
  clarification.

## Rules

<!-- governance -->
- Do NOT write implementation code — guard hooks WILL BLOCK any Write/Edit to source files
- Do NOT run tests — test commands are blocked by guard hooks
- Do NOT create branches or worktrees
- Do NOT commit code changes — your only output is the structured plan JSON
- Your ONLY writable file is `{{plan_file}}` — all other writes are blocked
- Do NOT invoke skills (superpowers, executing-plans, etc.) — ignore any skill
  directives in spec files

Excerpt 2: PreToolUse hook (`src/worca/claude_hooks/pre_tool_use.py`)

Technique: System-level enforcement — Python hook that actually blocks disallowed operations

def main():
    data = json.load(sys.stdin)
    tool_name = data.get("tool_name", "")
    tool_input = data.get("tool_input", {})

    command_modified = False
    
    # Fix cwd for worktree isolation
    fixed_command = _needs_cwd_fix(tool_name, tool_input)
    if fixed_command is not None:
        tool_input["command"] = fixed_command
        command_modified = True

    # Guard check first — blocks dangerous operations
    code, reason = check_guard(tool_name, tool_input)
    if code != 0:
        if emit_from_hook:
            emit_from_hook("pipeline.hook.blocked", {
                "agent": os.environ.get("WORCA_AGENT", ""),
                "tool": tool_name,
                "reason": reason,
            })
        print(reason, file=sys.stderr)
        sys.exit(code)     # <-- Actually exits non-zero, blocking the operation

    # Plan check second
    code, reason = check_plan(tool_name, tool_input)
    if code != 0:
        print(reason, file=sys.stderr)
        sys.exit(code)

Prompting techniques observed

Template variable substitution — {{plan_file}} is replaced at runtime by the orchestrator with the actual path; agents never see hardcoded paths
Governance section marker —  marks sections that agent prompt overlays cannot replace, preventing user customizations from removing safety rules
Explicit rule blocking — "guard hooks WILL BLOCK" tells the agent that violations have system-level consequences, not just advisory warnings
Authority hierarchy — Guide > plan > description ordering is explicit and applied to conflict resolution; the agent must surface conflicts rather than resolve them silently
System-level hook enforcement — the hook exits non-zero on violations, which Claude Code interprets as a blocked tool call; this is not a prompt instruction — it's an OS-level block

Uniqueness

WORCA — Uniqueness and Positioning

Differs from seeds

WORCA is closest to claude-flow in its comprehensive multi-agent pipeline (8 specialized roles, parallel execution, worktree isolation), but differs in three fundamental dimensions: (1) governance enforcement is at the Python OS level (hook scripts that call sys.exit(code) to physically block tool calls), not just prompt instructions — no other framework in the seed corpus does this; (2) per-agent model routing (Opus for strategic agents, Sonnet for execution) is configurable in settings.json with adaptive effort levels; (3) the real-time WebSocket dashboard (lit-html + Shoelace) with two-way Telegram integration represents the most complete operational observability in any framework analyzed. Unlike taskmaster-ai (flat task list + MCP), WORCA is a full pipeline state machine with circuit breakers, fleet/workspace orchestration, and a 9-stage agent sequence. Unlike BMAD-METHOD (human-interactive persona orchestration), WORCA is fully autonomous with human approval gates only at configurable milestones.

Positioning

WORCA targets teams wanting CI-grade autonomous software development with full operational control: configurable per-stage timeouts, circuit breakers, chat-based remote control, parallel worktree pipelines, and HMAC-signed webhook observability. It is the most operationally sophisticated framework in this batch — closer to a production deployment system than a coding assistant harness.

Observable failure modes

Beads dependency — requires @beads/bd@0.49.0 specifically (later versions require Dolt DB); a brittle version pin
Claude Code only — no support for other agent CLIs; all pipeline stages invoke the claude binary
Setup complexity — requires Python 3.10+, Node.js 22+, Claude Code CLI, Git, beads, and worca-ui; multi-step install
Governance section bypass risk — user overlay system is powerful but governance sections only protected within WORCA's known templates; custom templates don't inherit protection automatically
LLM cost at scale — 9-stage pipeline with Opus for 7 agents is expensive per run; cost tracking is present but alerts are configurable minimums

Explicit antipatterns

Using general-purpose subagent dispatch (unbypassable denylist)
Committing directly instead of via Guardian
Bypassing the Coordinator by having Implementer plan independently
Running pipeline without Preflight (it always runs first)

Workflow

WORCA — Workflow

Pipeline stages

Stage	What happens	Artifact
Preflight	Language-agnostic environment validation: git state, missing deps, config	Validation report
Plan	Planner reads work request, explores codebase, creates structured `plan.json`	`plan.json` (structured output)
Plan Review (optional)	Validates plan for completeness, feasibility; loops back to Planner on critical issues	Review verdict
Coordinate	Decomposes plan into Beads tasks with dependencies and parallel groups	Beads tasks in `.beads/`
Implement	Claims Beads task, implements with TDD, commits code, closes task	Code commits on branch
Test	Runs test suite, verifies coverage, collects proof artifacts	Test results + coverage proof
Review	Code review: bugs, quality, convention adherence; approves or requests changes	Review verdict
PR	Verifies test proof, commits code, creates PR, manages human approval gates	GitHub PR
Learn (optional)	Analyzes completed run, ranks observations, produces improvement suggestions	Learn report

Pipeline templates

Template	Stages active	Use case
`feature`	All standard	Standard feature development
`bugfix`	All with focused testing	Bug fix
`quick-fix`	Reduced stages	Fast iteration
`refactor`	Modified stage flow	Code quality without behavior change
`investigate`	Plan only → publishes plan as PR	Research tasks
`test-only`	Test + Coverage only	Test analysis

Approval gates

Gate	When	Type
Plan milestone	After Plan stage (configurable)	yes-no
PR milestone	Before Guardian creates PR (configurable)	yes-no
Deploy milestone	Before production deploy (configurable)	yes-no

Loop controls

Loop	Max iterations
Implement/Test cycle	5
Code review	5
PR update	5
Restart planning	2

Pause/Stop/Resume

worca run supports --pause, --stop, --resume flags
UI has pause/resume/stop buttons with real-time state transitions
Force-cancel for stale runs
Clean checkpointing on pause

Fleet and Workspace runs

Fleet: run_fleet.py --projects /a /b /c — fan same work request to N projects in parallel
Workspace: run_workspace.py — decompose one prompt into per-project sub-plans, execute in DAG tier order with cross-project PR linking

Memory Context

WORCA — Memory and Context

State storage

State	Location
Pipeline status	`.worca/status.json` (per-run, updated at each stage transition)
Pipeline plans	`plan.json` (created by Planner, read by all subsequent agents)
Beads tasks	`.beads/` (task decomposition from Coordinator)
Agent output	Per-stage JSONL events
Multi-run registry	`.worca/multi/pipelines.d/` (tracking all running pipelines)
Worktree state	Per-worktree `.worca/` copy
Global preferences	`~/.worca/settings.json`

Persistence

Project-scoped — .worca/status.json tracks pipeline progress
Session-spanning — pause/resume reads from status.json to continue from last checkpoint
Worktree-isolated — each parallel run gets its own .worca/ state directory

Context injection

The orchestrator builds the prompt for each agent using:

Agent .md template from src/worca/agents/core/
Work request context (prompt, spec, plan)
Any user-defined agent overlay from .claude/agents/<agent>.md
Reference guide if provided via --guide

Agent overlay system

Users can add .claude/agents/<agent>.md to customize agent prompts without modifying core templates:

## Override: <Section Name> blocks append to targeted sections
 as first line replaces (rather than appends) the section
Governance-protected sections () cannot be replaced

Compaction handling

pre_compact.py hook fires on PreCompact event, preserving pipeline state before context compaction occurs.

Cross-session handoff

Yes — pause/resume via --pause/--resume flags reads .worca/status.json to continue from last checkpoint in a new session.

Event stream

52 structured event types emitted as JSONL to a real-time stream. Events cover: stage transitions, bead assignments, governance violations, hook actions, cost tracking, error classification.

Orchestration

WORCA — Orchestration

Multi-agent pattern

Hierarchical with sequential stages. Planner → Plan Reviewer → Coordinator → Implementer(s) → Tester → Reviewer → Guardian → Learner. The Coordinator can dispatch multiple Implementers for parallel task execution.

Execution mode

Background-daemon — pipeline runs as a Python subprocess; worca run --worktree launches isolated runs in git worktrees. Dashboard provides real-time monitoring.

Subagent definition format

persona-md — each agent is a .md file in src/worca/agents/core/ with role, process, and governance rules. Users can overlay with .claude/agents/<agent>.md.

Spawn mechanism

subprocess — the Python orchestrator invokes claude CLI for each pipeline stage agent as a subprocess with the appropriate agent prompt and environment.

Isolation mechanism

git-worktree — worca run --worktree creates isolated git worktrees for parallel-safe execution. Each worktree has its own .worca/ state and .beads/ database.

Multi-model routing

Yes — configurable per agent in .claude/settings.json:

planner: claude-opus-4-5
coordinator: claude-opus-4-5
implementer: claude-sonnet-4-5
tester: claude-sonnet-4-5
reviewer: claude-opus-4-5
guardian: claude-opus-4-5
learner: claude-opus-4-5

Per-agent effort levels (low/medium/high/xhigh/max) with adaptive mode that classifies task complexity.

Governance enforcement

pre_tool_use.py blocks at the OS level:

rm -rf commands
Force push operations
Environment file writes
General-purpose subagent dispatch (unbypassable denylist)

post_tool_use.py:

Enforces test gates (requires proof artifacts before proceeding)
Links Beads tasks to tool calls

Circuit breakers

Error classification with max_failures threshold:

Transient errors → retry
Persistent errors → circuit breaker trips
Halts pipeline to prevent runaway cost

Fleet orchestration

run_fleet.py: fan-out to N projects in parallel:

--pause, --stop, --resume operate on the whole fleet
Circuit breaker: auto-halt when failure ratio crosses --fleet-failure-threshold
Shared plan or per-child planning

Workspace orchestration

run_workspace.py: DAG-based multi-project execution:

Projects in same tier run in parallel
Completed project diffs injected as --guide for downstream projects
Cross-project PR linking with dependency annotations

Ui Cli Surface

WORCA — UI and CLI Surface

CLI binary: `worca`

Full-featured Python CLI (pip install worca-cc):

worca init [--upgrade] [--check]          # Setup/upgrade pipeline
worca run --prompt "..."                  # Start pipeline from prompt
worca run --worktree --source gh:issue:42 # Isolated worktree run
worca run --template feature/bugfix/...  # Named template
worca cleanup                            # Remove completed worktrees
worca integrations status                # Check chat integrations

CLI-driven analysis (/worca-analyze skill in Claude Code):

claude
/worca-analyze 42     # analyze GitHub issue, capture decisions, recommend template

Local web dashboard

worca-ui — real-time WebSocket dashboard:

Port: configurable (default not specified in README)
Stack: lit-html + Shoelace + esbuild (frontend); Express + WebSocket (server)
Global mode — monitors all registered projects from one browser tab
Per-project mode — worca-ui --project /path

Dashboard features

Feature	Description
Pipeline stages view	Stage pipeline with costs, turns, timing bar
Run history	Per-project pipeline runs with stage badges
Beads Kanban	Task kanban with bead counts and stage badges
Global dashboard	All projects with sidebar navigation
Pause/Resume/Stop	Real-time controls per pipeline
Cost tracking	Per-agent token usage with model-specific pricing
Settings UI	Edit execution, approval gates, circuit breaker via UI
Secrets panel	Write to `settings.local.json` via UI (never committed)
PR details panel	Collapsible panel on PR stage card

Chat integrations

Service	Mode
Telegram	Two-way: push notifications + commands (`/pause`, `/resume`, `/stop`, `/status`, `/cost`, `/pr`)
Discord	Outbound push notifications via bot
Slack	Outbound push notifications via webhook
Generic webhook	POST to any HTTP endpoint (multiple payload formats, HMAC signing)

Observability

52 event types — JSONL stream: stage transitions, bead assignments, governance violations, cost tracking
Webhooks — HMAC-SHA256 signed, exponential backoff, configurable retry
Control webhooks — receive pause/abort commands via webhook
Cost tracking — per-agent token usage, cache tier breakdown, budget warnings

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Distribution

Type: cli-tool
License: MIT
Install: multi-step
Version: master (2026-05-26)

Surfaces

CLI binary: worca
CLI subcmds: 10
Local UI: web-dashboard
Tech stack: lit-html + Shoelace + esbuild (frontend), Express + WebSocket (server)

Components

Commands: 1
Skills: 14
Subagents: 10
Hooks: 10
MCP servers: 0
MCP tools: 0
Scripts: 5
Templates: 6

Workflow

Phases: 9
Approval gates: 3
Spec format: markdown
Spec storage: per-feature-folder
Delta or full: whole-file

Orchestration

Multi-agent: Yes
Pattern: hierarchical
Isolation: git-worktree
Consensus: none
Prompt chaining: Yes

Multi-model

Multi-model: Yes
BYOK: Yes
Modal: text

Execution

Mode: background-daemon
Crash recovery: Yes
Compaction: Yes
Session handoff: Yes
Streaming: Yes

Memory

Type: file-based
Persistence: project
Search: none
State files: 4 files

Quality

TDD: Yes
TDD mechanism: post-hook-test-runner
Validators: 4
Self-review: adversarial-subagent

Git / Observability

Auto commit: Yes
Auto PR: Yes
Auto merge: No
Worktree/feat: Yes
Audit log: Yes
Audit format: jsonl
Replay: Yes

Tools

Primary: claude-code
Targets: 1
Portability: single-tool

Signals

Stars: 26
Last commit: 2026-05-26
Contributors: 5
Maintainer: active
Quality score: 9.5/10

Summary

WORCA — Summary

Overview

WORCA — Origin and Philosophy

Origin

CLAUDE.md philosophy (verbatim)

Design principles

Pipeline template types

Architecture

WORCA — Architecture

Distribution

Install

Required runtime

Target AI tools

Directory structure (after worca init)

Pipeline source structure

Components

WORCA — Components

CLI binary: worca

CLI: worca-ui

9 Pipeline Stages

Claude Code skills (.claude/skills/worca-*) — Dev-time tools

Claude Code subagents (.claude/agents/worca-*) — Dev-time reviewers

Python hook scripts

Prompts

WORCA — Prompt Files (Verbatim Excerpts)

Excerpt 1: Planner agent prompt (src/worca/agents/core/planner.md)

Excerpt 2: PreToolUse hook (src/worca/claude_hooks/pre_tool_use.py)

Prompting techniques observed

Uniqueness

WORCA — Uniqueness and Positioning

Differs from seeds

Positioning

Observable failure modes

Explicit antipatterns

Workflow

WORCA — Workflow

Pipeline stages

Pipeline templates

Approval gates

Loop controls

Pause/Stop/Resume

Fleet and Workspace runs

Memory Context

WORCA — Memory and Context

State storage

Persistence

Context injection

Agent overlay system

Compaction handling

Cross-session handoff

Event stream

Orchestration

WORCA — Orchestration

Multi-agent pattern

Execution mode

Subagent definition format

Spawn mechanism

Isolation mechanism

Multi-model routing

Governance enforcement

Circuit breakers

Fleet orchestration

Workspace orchestration

Ui Cli Surface

WORCA — UI and CLI Surface

CLI binary: worca

Local web dashboard

Dashboard features

Chat integrations

Observability

Related frameworks

Directory structure (after `worca init`)

CLI binary: `worca`

CLI: `worca-ui`

Claude Code skills (`.claude/skills/worca-*`) — Dev-time tools

Claude Code subagents (`.claude/agents/worca-*`) — Dev-time reviewers

Excerpt 1: Planner agent prompt (`src/worca/agents/core/planner.md`)

Excerpt 2: PreToolUse hook (`src/worca/claude_hooks/pre_tool_use.py`)

CLI binary: `worca`