gathering-requirements

name	gathering-requirements
description	5-layer requirements elicitation for Cursor agent system generation Use when this capability is needed.
metadata	{"author":"gitwalter"}

Requirements Gathering

5-layer requirements elicitation for Cursor agent system generation with axioms, purpose, and methodology

Executes a structured multi-phase questionnaire implementing the 5-layer architecture to capture all requirements for generating a new Cursor agent development system.

Philosophy

This skill guides users from foundational axioms through purpose, principles, methodology, and technical implementation - ensuring generated systems are grounded in clear values and purpose.

Process

1. Review the task requirements.
2. Apply the skill's methodology.
3. Validate the output against the defined criteria.

Step 1: Axiom Configuration (Layer 0)

Select core axioms (A1-A5) and optional axioms (A6-A10) that will govern the agent system. Axiom 0 (Love, Truth, and Beauty) is always included.

Step 2: Purpose Definition (Layer 1)

Define mission statement, identify primary stakeholders, and establish measurable success criteria.

Step 3: Depth Selection

Choose Quick Start, Standard, or Comprehensive depth level. This determines which subsequent layers will be configured.

Step 4: Principles Selection (Layer 2, if Standard+)

Define ethical boundaries, quality standards, and failure handling approaches.

Step 5: Methodology Selection (Layer 3, if Standard+)

Choose development methodology (Agile Scrum, Kanban, R&D, Enterprise) and configure team size and workflow patterns.

Step 6: Enforcement & Practices (if Comprehensive)

Select enforcement patterns for quality, safety, and integrity, plus daily/craft/alignment practices.

Step 7: Technical Configuration (Layer 4)

Gather project context, technology stack, workflow triggers, knowledge domain, and agent capabilities.

Step 8: Validation & Generation

Validate completeness, confirm target directory, generate summary, and create all artifacts.

Complete Phase Structure

┌─────────────────────────────────────────────────────────────────┐
│ PRE-PHASE: Layer 0 - Axiom Configuration                        │
│   Select core (A1-A5) and optional (A6-A10) axioms              │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 0: Layer 1 - Purpose Definition                           │
│   Mission, Stakeholders, Success Criteria                        │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 0.5: Depth Selection                                       │
│   Quick Start / Standard / Comprehensive                         │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 0.6: Layer 2 - Principles (if Standard+)                   │
│   Ethical boundaries, quality standards, failure handling        │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 0.7: Layer 3 - Methodology (if Standard+)                  │
│   Agile/Kanban/R&D/Enterprise selection and configuration        │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 0.8: Enforcement Selection (if Comprehensive)              │
│   Quality, Safety, Integrity enforcement patterns                │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 0.9: Practice Selection (if Comprehensive)                 │
│   Daily, Craft, Alignment practices                              │
├─────────────────────────────────────────────────────────────────┤
│ PHASE 1-5: Layer 4 - Technical Configuration                     │
│   Stack, Agents, Skills, Knowledge, Integrations                 │
└─────────────────────────────────────────────────────────────────┘

PRE-PHASE: Layer 0 - Axiom Configuration

Skill Reference: {directories.skills}/axiom-selection/SKILL.md

Introduction

Before we begin, let's ground ourselves in the foundation of foundations:

Axiom 0: Love, Truth, and Beauty
"All being and doing is grounded in love, truth, and beauty."

This axiom is always included and cannot be removed. From this foundation,
we derive the core axioms that govern agent behavior.

Foundation Axiom (Always Included)

ID	Axiom	Statement
A0	Love, Truth, and Beauty	All being and doing is grounded in love, truth, and beauty

Core Axioms (Always Included)

ID	Axiom	Statement
A1	Verifiability	All agent outputs must be verifiable against source
A2	User Primacy	User intent takes precedence over agent convenience
A3	Transparency	Agent reasoning must be explainable on request
A4	Non-Harm	No action may knowingly cause harm
A5	Consistency	No rule may contradict these axioms

Optional Axioms

ID	Axiom	Use When
A6	Minimalism	Maintenance and understandability are priorities
A7	Reversibility	Safety and recoverability are paramount
A8	Privacy	Handling sensitive user data
A9	Performance	Performance-critical applications
A10	Learning	AI/ML, R&D, continuous improvement culture

Output

layer0:
  foundationAxiom: "A0"  # Love, Truth, and Beauty - always included
  coreAxioms: ["A1", "A2", "A3", "A4", "A5"]
  optionalAxioms: ["A6", "A7"]  # User selected
  customAxioms: []  # Domain-specific additions

PHASE 0: Layer 1 - Purpose Definition

Skill Reference: {directories.skills}/purpose-definition/SKILL.md

Questions

| # | Question | Variable | Validation | ||-|-|| | 1 | In ONE sentence, why should this agent system exist? | {MISSION_STATEMENT} | Verifiable outcome (A1) | | 2 | Who are the primary users or beneficiaries? | {PRIMARY_STAKEHOLDERS} | Specific humans (A2) | | 3 | What is the single most important outcome? | {SUCCESS_CRITERIA} | Measurable (A1) |

Output

layer1:
  mission: "{MISSION_STATEMENT}"
  stakeholders: "{PRIMARY_STAKEHOLDERS}"
  successCriteria: "{SUCCESS_CRITERIA}"

Generated Artifact: PURPOSE.md

PHASE 0.5: Depth Selection

Question

How deep should we define the remaining layers?

A) Quick Start - Use defaults, go straight to technical configuration
B) Standard - Define principles and select methodology template
C) Comprehensive - Define all layers including enforcement and practices

Routing

| Selection | Next Phase | |--|| | Quick Start | Phase 1 (Technical) | | Standard | Phase 0.6 (Principles) | | Comprehensive | Phase 0.6 (Principles) |

PHASE 0.6: Layer 2 - Principles (Standard & Comprehensive)

Questions

| # | Question | Variable | Reference | ||-|-|--| | 1 | What actions should agents NEVER take? | {ETHICAL_BOUNDARIES} | {directories.patterns}/principles/ethical-boundaries.json | | 2 | What quality bar must all outputs meet? | {QUALITY_STANDARDS} | {directories.patterns}/principles/quality-standards.json | | 3 | How should failures be handled? | {FAILURE_HANDLING} | {directories.patterns}/principles/failure-handling.json |

Output

layer2:
  ethicalBoundaries: ["EB1", "EB2", "EB3", "EB4", "EB5"]
  qualityStandards: ["QS1", "QS2", "QS3", "QS4", "QS5"]
  failureHandling: ["FH1", "FH2", "FH3"]

PHASE 0.7: Layer 3 - Methodology (Standard & Comprehensive)

Skill Reference: {directories.skills}/methodology-selection/SKILL.md

Questions

| # | Question | Variable | Options | ||-|-|| | 1 | What development methodology fits your team? | {METHODOLOGY} | Agile Scrum, Kanban, R&D, Enterprise | | 2 | Team size? | {TEAM_SIZE} | 1-3, 4-6, 7-10, 10+ |

Methodology Options

| Methodology | Best For | Pattern | |-|-|| | Agile Scrum | Product development, feature teams | domain_expert_swarm + peer_collaboration | | Kanban | Support, maintenance, ops | continuous_flow + pull_based | | R&D | AI/ML, innovation, research | knowledge_mesh + adaptive_learning | | Enterprise | Large-scale, compliance-driven | hierarchical_command + pipeline |

Output

layer3:
  methodology: "agile-scrum"
  teamSize: "4-6"
  pattern: "domain_expert_swarm + peer_collaboration"

Generated Artifact: {directories.workflows}/methodology.yaml

PHASE 0.8: Enforcement Selection (Comprehensive Only)

Skill Reference: {directories.skills}/enforcement-selection/SKILL.md

Question

Select enforcement patterns to ensure values are lived:

Quality Enforcement:
[x] E1: Test Coverage Gate
[x] E2: Peer Review Gate
[ ] E3: Documentation Completeness
[x] E4: Style Consistency

Safety Enforcement:
[x] E5: Destructive Action Confirmation
[ ] E6: Backup Before Modification
[ ] E7: Security Vulnerability Check
[ ] E8: Production Safeguard

Integrity Enforcement:
[x] E9: Axiom Compliance Check
[ ] E10: Purpose Alignment Check
[ ] E11: Transparency Log

Output

enforcement:
  quality: ["E1", "E2", "E4"]
  safety: ["E5"]
  integrity: ["E9"]

Generated Artifact: enforcement.yaml

PHASE 0.9: Practice Selection (Comprehensive Only)

Skill Reference: {directories.skills}/practice-selection/SKILL.md

Question

Select practices to maintain excellence and alignment:

Daily Practices:
[ ] P1: Morning Intention Setting
[ ] P2: Evening Reflection
[x] P3: Focused Stand-up

Craft Practices:
[x] P4: Code as Craft Review
[x] P5: Thoughtful Code Review
[ ] P6: Continuous Refactoring

Alignment Practices:
[ ] P7: Weekly Learning Session
[x] P8: Sprint Retrospective
[ ] P9: Release Blessing
[ ] P10: Quarterly Purpose Alignment

Output

practices:
  daily: ["P3"]
  craft: ["P4", "P5"]
  alignment: ["P8"]

Generated Artifact: practices.yaml

PHASE 1: Project Context (Layer 4 - Technical)

Questions

| # | Question | Variable | Validation | ||-|-|| | 1 | What is the name of your project? | {PROJECT_NAME} | Valid directory name | | 2 | Briefly describe what this project will do | {PROJECT_DESCRIPTION} | Non-empty, < 500 chars | | 3 | What domain or industry is this for? | {DOMAIN} | Match to known domains | | 4 | Team size and experience level? | {TEAM_CONTEXT} | Optional |

Domain Options

• Web Development
• Mobile Development
• Data Science / ML
• AI Agent Development
• SAP / Enterprise
• DevOps / Infrastructure
• Game Development
• IoT / Embedded
• Custom (specify)

Output

projectContext:
  name: "{PROJECT_NAME}"
  description: "{PROJECT_DESCRIPTION}"
  domain: "{DOMAIN}"
  teamContext: "{TEAM_CONTEXT}"

PHASE 2: Technology Stack

Questions

| # | Question | Variable | Reference | ||-|-|--| | 1 | Primary programming language? | {PRIMARY_LANGUAGE} | Check blueprints | | 2 | Frameworks or libraries? | {FRAMEWORKS} | Stack-specific | | 3 | Database or storage systems? | {DATABASES} | Optional | | 4 | External APIs or services? | {EXTERNAL_APIS} | Optional |

Blueprint Matching

IF primaryLanguage == "python" AND "fastapi" IN frameworks:
    suggest blueprint: "python-fastapi"
IF primaryLanguage == "python" AND ("langchain" IN frameworks OR "langgraph" IN frameworks):
    suggest blueprint: "ai-agent-development"
IF primaryLanguage == "typescript" AND "react" IN frameworks:
    suggest blueprint: "typescript-react"

Output

technologyStack:
  primaryLanguage: "{PRIMARY_LANGUAGE}"
  frameworks: ["{FRAMEWORK_1}", "{FRAMEWORK_2}"]
  databases: ["{DATABASE_1}"]
  externalApis: ["{API_1}"]
  matchedBlueprint: "{BLUEPRINT_ID}" | null

PHASE 3: Workflow Methodology

Questions

| # | Question | Variable | Options | ||-|-|| | 1 | What triggers tasks? | {TRIGGER_SOURCES} | Jira, Confluence, GitHub, GitLab, Manual | | 2 | Output artifacts? | {OUTPUT_ARTIFACTS} | Code, Docs, Tests, Diagrams |

Trigger Source Details

| Trigger | Additional Info Needed | ||-| | Jira | Project key pattern (e.g., PROJ-###) | | Confluence | Space key | | GitHub | Repository URL pattern | | GitLab | Repository URL pattern |

Output

workflowConfig:
  triggerSources:
    - type: "jira"
      pattern: "{PROJECT_KEY}-{NUMBER}"
  outputArtifacts: ["code", "docs", "tests"]

PHASE 4: Knowledge Domain

Questions

| # | Question | Variable | Purpose | ||-|-|| | 1 | Domain-specific concepts? | {DOMAIN_CONCEPTS} | Build knowledge files | | 2 | Reference repositories/docs? | {REFERENCE_SOURCES} | DeepWiki integration | | 3 | Naming conventions? | {CONVENTIONS} | Style guide setup |

Output

knowledgeDomain:
  concepts: ["{CONCEPT_1}", "{CONCEPT_2}"]
  referenceSources:
    - type: "github"
      url: "{REPO_URL}"
  conventions:
    styleGuide: "{STYLE_GUIDE}"

PHASE 5: Agent Capabilities

Questions

| # | Question | Variable | Options | ||-|-|| | 1 | Core agents needed? | {CORE_AGENTS} | Multi-select | | 2 | Workflow skills needed? | {CORE_SKILLS} | Multi-select | | 3 | MCP server integrations? | {MCP_INTEGRATIONS} | Multi-select |

Agent Options

Agent	Description	When to Suggest
code-reviewer	Reviews code quality	Always
test-generator	Creates test cases	When tests in artifacts
documentation-agent	Generates documentation	When docs in artifacts
explorer	Searches external docs	When external APIs used

Skill Options

Skill	Description	When to Suggest
bugfix-workflow	Ticket-based bug fixes	When Jira trigger
feature-workflow	Spec-based features	When Confluence trigger
grounding	Data model verification	Data-heavy projects
tdd	Test-driven development	When tests important
prompt-engineering	LLM prompt optimization	AI agent projects
agent-coordination	Multi-agent orchestration	AI agent projects

Output

agentCapabilities:
  agents: ["code-reviewer", "test-generator"]
  skills: ["bugfix-workflow", "feature-workflow", "tdd"]
  mcpIntegrations: ["atlassian", "deepwiki"]

Final Validation & Summary

Completeness Check

• Layer 0: Axioms configured
• Layer 1: Purpose defined
• Layer 2: Principles selected (if Standard+)
• Layer 3: Methodology chosen (if Standard+)
• Layer 4: Technical stack defined
• At least one agent selected
• At least one skill selected

Target Directory

1. Ask: "Where should I create the project?"
2. Validate: Path is accessible, NOT within factory directory
3. Confirm with user

Generate Summary

## Requirements Summary

### Layer 0: Axioms
- **Core:** A1-A5 (Verifiability, User Primacy, Transparency, Non-Harm, Consistency)
- **Optional:** {SELECTED_OPTIONAL_AXIOMS}

### Layer 1: Purpose
- **Mission:** {MISSION_STATEMENT}
- **Stakeholders:** {PRIMARY_STAKEHOLDERS}
- **Success:** {SUCCESS_CRITERIA}

### Layer 2: Principles
- **Boundaries:** {ETHICAL_BOUNDARIES}
- **Standards:** {QUALITY_STANDARDS}

### Layer 3: Methodology
- **Methodology:** {METHODOLOGY}
- **Team Size:** {TEAM_SIZE}

### Layer 4: Technical
- **Project:** {PROJECT_NAME}
- **Stack:** {PRIMARY_LANGUAGE} + {FRAMEWORKS}
- **Blueprint:** {MATCHED_BLUEPRINT}
- **Agents:** {CORE_AGENTS}
- **Skills:** {CORE_SKILLS}

### Output Location
- **Target:** {TARGET_DIR}

Generated Artifacts

Layer	Artifact	Description
0-4	.cursorrules	Complete 5-layer agent rules
1	PURPOSE.md	Mission, stakeholders, success
2+	enforcement.yaml	Enforcement configuration
3	{directories.workflows}/methodology.yaml	Methodology configuration
3+	practices.yaml	Team practices
4	{directories.agents}/	Agent definitions
4	{directories.skills}/	Skill definitions
4	{directories.knowledge}/	Domain knowledge

Team Alternative

For teams of 2+ people, offer the Team Workshop Onboarding:

"Would you prefer to gather requirements:

A) Individually - I'll ask you questions now (faster, solo decision-maker)
B) As a Team - Workshop series with games and discussions (richer, collaborative)

Team workshops are grounded in Axiom 0 (Love, Truth, and Beauty) and include:
- Vision Quest: Headlines and stakeholder games
- Ethics Arena: Dilemma debates and value auctions
- Stack Safari: Trade-off games and architecture pictionary
- Agent Assembly: Trading cards and skill bingo
- Integration Celebration: Demo derby and gratitude circle"

If they choose team workshops, hand off to team-workshop-onboarding skill.

Important Rules

1. Ask one phase at a time - Don't overwhelm user
2. Explain the why - Connect questions to axioms and purpose
3. Validate inputs - Check against axioms before proceeding
4. Suggest blueprints - Match to existing blueprints
5. Confirm summary - Review before generation
6. Never assume - Ask if uncertain (A2: User Primacy)
7. Ground in A0 - Remember that love, truth, and beauty underpin all requirements

References

• {directories.patterns}/axioms/ - Axiom definitions
• {directories.patterns}/principles/ - Principle patterns
• {directories.patterns}/methodologies/ - Methodology templates
• {directories.patterns}/enforcement/ - Enforcement patterns
• {directories.patterns}/practices/ - Practice patterns
• {directories.knowledge}/ - Domain knowledge files
• {directories.blueprints}/ - Technology blueprints

When to Use

This skill should be used when strict adherence to the defined process is required.

Prerequisites

• Basic understanding of the agent factory context.
• Access to the necessary tools and resources.

Best Practices

• Always follow the established guidelines.
• Document any deviations or exceptions.
• Regularly review and update the skill documentation.

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