edd — ai-orchestration multi-agent-ralph-loop, community, ai-orchestration, ide skills, bats-testing, claude-code, code-quality, codex-cli, dynamic-contexts, eval-driven-development, Claude Code

v1.0.0

このスキルについて

Perfect for AI Agents needing comprehensive content analysis and quality-first development with model-agnostic orchestration Orchestration system for Claude Code with memory-driven planning, multi-agent coordination, Agent Teams integration, automatic learning, and comprehensive security validation (Grade A-). v2.94.0

# Core Topics

alfredolopez80 alfredolopez80
[107]
[18]
Updated: 3/29/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 9/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
9/11
Quality Score
61
Canonical Locale
en
Detected Body Locale
en

Perfect for AI Agents needing comprehensive content analysis and quality-first development with model-agnostic orchestration Orchestration system for Claude Code with memory-driven planning, multi-agent coordination, Agent Teams integration, automatic learning, and comprehensive security validation (Grade A-). v2.94.0

このスキルを使用する理由

Empowers agents to define, implement, and verify features using a structured eval-driven development workflow, leveraging model-agnostic configurations via ~/.claude/settings.json and env vars like ANTHROPIC_DEFAULT_*_MODEL, ensuring flexible integration with models like GLM-5, Claude, and Minimax

おすすめ

Perfect for AI Agents needing comprehensive content analysis and quality-first development with model-agnostic orchestration

実現可能なユースケース for edd

Defining and verifying feature capabilities using Capability Checks (CC-)
Validating expected behaviors and responses with Behavior Checks (BC-)
Ensuring performance, security, and maintainability through Non-Functional Checks (NFC-)
Integrating with orchestrator workflows for quality-first development and swarm mode for parallel evaluation

! セキュリティと制限

  • Requires configuration of model settings via ~/.claude/settings.json or env vars
  • Dependent on CLI/env vars for default model selection
  • Needs eval definitions directory ~/.claude/evals/ for storing eval specifications

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is edd?

Perfect for AI Agents needing comprehensive content analysis and quality-first development with model-agnostic orchestration Orchestration system for Claude Code with memory-driven planning, multi-agent coordination, Agent Teams integration, automatic learning, and comprehensive security validation (Grade A-). v2.94.0

How do I install edd?

Run the command: npx killer-skills add alfredolopez80/multi-agent-ralph-loop/edd. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for edd?

Key use cases include: Defining and verifying feature capabilities using Capability Checks (CC-), Validating expected behaviors and responses with Behavior Checks (BC-), Ensuring performance, security, and maintainability through Non-Functional Checks (NFC-), Integrating with orchestrator workflows for quality-first development and swarm mode for parallel evaluation.

Which IDEs are compatible with edd?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for edd?

Requires configuration of model settings via ~/.claude/settings.json or env vars. Dependent on CLI/env vars for default model selection. Needs eval definitions directory ~/.claude/evals/ for storing eval specifications.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add alfredolopez80/multi-agent-ralph-loop/edd. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use edd immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

edd

Install edd, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
Supporting Evidence

EDD (Eval-Driven Development) Framework v2.64

Eval-Driven Development is a quality-first development pattern that enforces define-before-implement workflow with structured evaluations.

v2.88 Key Changes (MODEL-AGNOSTIC)

  • Model-agnostic: Uses model configured in ~/.claude/settings.json or CLI/env vars
  • No flags required: Works with the configured default model
  • Flexible: Works with GLM-5, Claude, Minimax, or any configured model
  • Settings-driven: Model selection via ANTHROPIC_DEFAULT_*_MODEL env vars

What is EDD?

EDD provides a systematic approach to software development with three phases:

  1. DEFINE - Create structured eval specifications using TEMPLATE.md
  2. IMPLEMENT - Build features according to eval definitions
  3. VERIFY - Validate implementation against eval criteria

Check Types

PrefixTypePurpose
CC-Capability ChecksFeature capabilities and functionality
BC-Behavior ChecksExpected behaviors and responses
NFC-Non-Functional ChecksPerformance, security, maintainability

Usage

bash
1# Invoke EDD workflow 2/edd "Define memory-search feature" 3 4# CLI script (if available) 5ralph edd define memory-search 6ralph edd check memory-search

Components

  • TEMPLATE.md: Template for creating eval definitions
  • edd.sh: CLI script for eval management
  • /edd skill: Skill invocation from Claude Code
  • ~/.claude/evals/: Directory for eval definitions

Template Structure

Each eval definition includes:

  1. Capability Checks (CC-) - What the feature can do
  2. Behavior Checks (BC-) - How the feature behaves
  3. Non-Functional Checks (NFC-) - Performance, security, etc.
  4. Implementation Notes - Technical guidance
  5. Verification Evidence - Test results

Example: memory-search.md

markdown
1# Memory Search Eval 2 3**Status**: DRAFT 4**Created**: 2026-01-30 5 6## Capability Checks 7- [ ] CC-1: Search across semantic memory 8- [ ] CC-2: Support filtering by type 9 10## Behavior Checks 11- [ ] BC-1: Returns ranked results 12- [ ] BC-2: Handles empty queries gracefully 13 14## Non-Functional Checks 15- [ ] NFC-1: Search completes in <2s 16- [ ] NFC-2: Memory usage <100MB 17 18## Implementation Notes 19- Use parallel search for performance 20- Cache frequent queries 21 22## Verification Evidence 23- Test results attached

Integration with Orchestrator

EDD integrates with the orchestrator workflow to ensure quality-first development:

  1. Clarify phase - Define evals
  2. Plan phase - Review eval requirements
  3. Implement phase - Build to eval specs
  4. Validate phase - Verify against evals

Swarm Mode Integration (v2.81.1)

EDD framework now supports swarm mode for parallel evaluation across multiple check types.

Auto-Spawn Configuration

When invoked via /edd, the framework automatically spawns a specialized evaluation team:

yaml
1Task: 2 subagent_type: "general-purpose" 3 model: "sonnet" 4 team_name: "edd-evaluation-team" 5 name: "edd-coordinator" 6 mode: "delegate" 7 run_in_background: true 8 prompt: | 9 Execute Eval-Driven Development workflow for: $ARGUMENTS 10 11 EDD Pattern: 12 1. DEFINE - Create structured eval specifications 13 2. DISTRIBUTE - Assign check types to specialists 14 3. VERIFY - Validate against eval criteria 15 4. CONSOLIDATE - Merge findings from all evaluators

Team Composition

RolePurposeSpecialization
CoordinatorEDD workflow orchestrationManages eval lifecycle, consolidates findings
Teammate 1Capability Checks specialistCC- prefix: feature capabilities and functionality
Teammate 2Behavior Checks specialistBC- prefix: expected behaviors and responses
Teammate 3Non-Functional Checks specialistNFC- prefix: performance, security, maintainability

Swarm Mode Workflow

User invokes: /edd "Define memory-search feature"

1. Team "edd-evaluation-team" created
2. Coordinator (edd-coordinator) receives task
3. 3 Teammates spawned with check-type specializations
4. Eval definition distributed:
   - Teammate 1 → Capability Checks (CC-)
   - Teammate 2 → Behavior Checks (BC-)
   - Teammate 3 → Non-Functional Checks (NFC-)
5. Teammates work in parallel (background execution)
6. Coordinator monitors progress and gathers results
7. Findings consolidated into single eval specification
8. Final eval document returned

Parallel Evaluation Pattern

Each teammate focuses on their check type:

yaml
1# Teammate 1: Capability Checks 2CC-1: Feature can perform X 3CC-2: Feature supports Y configuration 4CC-3: Feature integrates with Z system 5 6# Teammate 2: Behavior Checks 7BC-1: Feature handles error case A gracefully 8BC-2: Feature returns expected response for B 9BC-3: Feature maintains state across C 10 11# Teammate 3: Non-Functional Checks 12NFC-1: Response time < 100ms 13NFC-2: Memory usage < 50MB 14NFC-3: Security vulnerability scan passes

Communication Between Teammates

Teammates use the built-in mailbox system:

yaml
1# Teammate sends finding to coordinator 2SendMessage: 3 type: "message" 4 recipient: "edd-coordinator" 5 content: "CC-3 defined: Feature integrates with auth system via OAuth2"

Task List Coordination

All teammates share a unified task list:

bash
1# Location: ~/.claude/tasks/edd-evaluation-team/tasks.json 2 3# Example tasks: 4[ 5 {"id": "1", "subject": "Define Capability Checks", "owner": "teammate-1"}, 6 {"id": "2", "subject": "Define Behavior Checks", "owner": "teammate-2"}, 7 {"id": "3", "subject": "Define Non-Functional Checks", "owner": "teammate-3"}, 8 {"id": "4", "subject": "Consolidate eval specification", "owner": "edd-coordinator"} 9]

Manual Override

To disable swarm mode:

bash
1/edd "Define feature X" --no-swarm

Output Location

bash
1# Evals saved to ~/.claude/evals/ 2ls ~/.claude/evals/ 3 4# View last eval 5cat ~/.claude/evals/latest.md

Testing

Test suite: tests/test_v264_edd_framework.bats (33 tests)

Run tests:

bash
1bats tests/test_v264_edd_framework.bats

Swarm Mode Tests

Additional tests for swarm mode integration:

bash
1# Test swarm team creation 2tests/edd/test-swarm-team-creation.sh 3 4# Test parallel evaluation 5tests/edd/test-parallel-evaluation.sh

Status

Current: Framework defined with swarm mode integration (v2.81.1) Note: TEMPLATE.md and evals directory structure ready for use


Version: v2.64 | Status: DRAFT | Tests: 33 passing

Action Reporting (v2.93.0)

Esta skill genera reportes automáticos completos para trazabilidad:

Reporte Automático

Cuando esta skill completa, se genera automáticamente:

  1. En la conversación de Claude: Resultados visibles
  2. En el repositorio: docs/actions/edd/{timestamp}.md
  3. Metadatos JSON: .claude/metadata/actions/edd/{timestamp}.json

Contenido del Reporte

Cada reporte incluye:

  • Summary: Descripción de la tarea ejecutada
  • Execution Details: Duración, iteraciones, archivos modificados
  • Results: Errores encontrados, recomendaciones
  • Next Steps: Próximas acciones sugeridas

Ver Reportes Anteriores

bash
1# Listar todos los reportes de esta skill 2ls -lt docs/actions/edd/ 3 4# Ver el reporte más reciente 5cat $(ls -t docs/actions/edd/*.md | head -1) 6 7# Buscar reportes fallidos 8grep -l "Status: FAILED" docs/actions/edd/*.md

Generación Manual (Opcional)

bash
1source .claude/lib/action-report-lib.sh 2start_action_report "edd" "Task description" 3# ... ejecución ... 4complete_action_report "success" "Summary" "Recommendations"

Referencias del Sistema

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