# Building Rainwater Harvesting

> A production-grade harness for Building Rainwater Harvesting & Water Reuse analysis and design. Use when the user needs rainwater harvesting system design, water reuse assessment, rainfall calculations, storage sizing, treatment design, or compliance with rainwater standards. This skill provides structured, evidence-backed outputs combining real-time data aggregation, recognized domain methods, a…

- **Type:** Skill
- **Install:** `agentstack add skill-dungnotnull-building-rainwater-harvesting-agent-skill-building-rainwater-harvesting-agent-skill`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [dungnotnull](https://agentstack.voostack.com/s/dungnotnull)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [dungnotnull](https://github.com/dungnotnull)
- **Source:** https://github.com/dungnotnull/building-rainwater-harvesting-agent-skill

## Install

```sh
agentstack add skill-dungnotnull-building-rainwater-harvesting-agent-skill-building-rainwater-harvesting-agent-skill
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# SKILL.md — building-rainwater-harvesting Registry

## Skill Registration

This document serves as the central registry for the `building-rainwater-harvesting` skill, documenting all sub-skills, tools, hooks, and execution protocols.

### Skill Identity

- **Name:** `building-rainwater-harvesting`
- **Version:** 1.0.0
- **Category:** Engineering & Environment
- **Domain:** Building Rainwater Harvesting & Water Reuse
- **Type:** Harness Skill (orchestrates sub-skills)

### Triggering Criteria

The skill automatically triggers when:
- User mentions rainwater harvesting, water reuse, or stormwater
- Building water system design or sizing is requested
- Rainfall calculations or storage capacity analysis is needed
- Water quality or treatment design for rainwater is discussed
- Compliance with rainwater standards (ARCSA, WHO, ISO) is referenced
- Sustainable water management or green building features are mentioned

---

## Sub-Skill Registry

### 1. sub-gather-requirements

**File:** `skills/sub-gather-requirements.md`

**Purpose:** Clarify the object of analysis, constraints, timeframe, available inputs, target audience, and language before any data fetching.

**Input Schema:**
```json
{
  "type": "object",
  "properties": {
    "user_message": {"type": "string", "description": "Raw user input"},
    "provided_materials": {"type": "array", "items": {"type": "string"}, "description": "Any files or context provided"}
  }
}
```

**Output Schema:**
```json
{
  "type": "object",
  "properties": {
    "object": {"type": "string", "description": "Primary object of analysis"},
    "scope": {"type": "string", "description": "Analysis scope and boundaries"},
    "timeframe": {"type": "string", "description": "Analysis timeframe"},
    "available_inputs": {"type": "object", "description": "Available data and parameters"},
    "target_audience": {"type": "string", "description": "Intended audience for output"},
    "language": {"type": "string", "enum": ["en", "vi"], "description": "Output language"},
    "analysis_type": {"type": "string", "description": "Type of analysis requested"}
  },
  "required": ["object", "language"]
}
```

**Quality Gate:** At least one object of analysis confirmed before proceeding.

---

### 2. sub-evidence-collector

**File:** `skills/sub-evidence-collector.md`

**Purpose:** Fetch authoritative real-time and reference data for the object: current status/parameters, authoritative documents/standards, and recent developments from domain and academic sources.

**Input Schema:**
```json
{
  "type": "object",
  "properties": {
    "requirements": {"type": "object", "description": "Requirements from Step 1"}
  },
  "required": ["requirements"]
}
```

**Output Schema:**
```json
{
  "type": "object",
  "properties": {
    "current_data": {"type": "object", "description": "Current status and parameters"},
    "authoritative_docs": {"type": "array", "description": "Authoritative documents and standards"},
    "recent_news": {"type": "array", "description": "Recent developments"},
    "reference_benchmarks": {"type": "object", "description": "Reference benchmarks"}
  }
}
```

**Tools Required:** WebSearch, WebFetch, Read

**Quality Gate:** At least current data + 1 authoritative document retrieved, or limitation flag.

---

### 3. sub-core-analysis

**File:** `skills/sub-core-analysis.md`

**Purpose:** Design a building rainwater-harvesting system: size storage from supply/demand, design first-flush/treatment, and specify end-use and maintenance.

**Input Schema:**
```json
{
  "type": "object",
  "properties": {
    "roof_area": {"type": "number", "description": "Roof catchment area in m²"},
    "rainfall": {"type": "number", "description": "Annual rainfall in mm"},
    "demand": {"type": "number", "description": "Daily water demand in liters"},
    "end_use": {"type": "string", "description": "Intended end use"},
    "language": {"type": "string", "enum": ["en", "vi"]}
  },
  "required": ["roof_area", "rainfall", "demand"]
}
```

**Output Schema:**
```json
{
  "type": "object",
  "properties": {
    "runoff_analysis": {"type": "object", "description": "Runoff calculation results"},
    "storage_design": {"type": "object", "description": "Storage sizing and design"},
    "treatment_system": {"type": "object", "description": "First-flush and treatment design"},
    "distribution_design": {"type": "object", "description": "Distribution system design"},
    "regulatory_compliance": {"type": "object", "description": "Compliance assessment"},
    "scenarios": {"type": "array", "description": "Design scenarios"}
  }
}
```

**Tools Required:** Read, WebFetch, Arithmetic

**Quality Gate:** Runoff estimated; storage sized from supply/demand; treatment matched to end-use.

---

### 4. sub-knowledge-updater

**File:** `skills/sub-knowledge-updater.md`

**Purpose:** Query SECOND-KNOWLEDGE-BRAIN.md for authoritative academic and professional evidence; surface citations with tier labels and flag gaps for the crawl pipeline.

**Input Schema:**
```json
{
  "type": "object",
  "properties": {
    "topic_keywords": {"type": "array", "items": {"type": "string"}, "description": "Keywords for knowledge lookup"}
  },
  "required": ["topic_keywords"]
}
```

**Output Schema:**
```json
{
  "type": "object",
  "properties": {
    "citations": {"type": "array", "description": "Knowledge-base citations with Tier labels"},
    "coverage_rating": {"type": "string", "description": "Coverage assessment"},
    "gaps": {"type": "array", "description": "Knowledge gaps to be filled"}
  }
}
```

**Tools Required:** Read, WebSearch

**Quality Gate:** At least 1 academic/authoritative source surfaced; coverage rating provided.

---

### 5. sub-advisor

**File:** `skills/sub-advisor.md`

**Purpose:** Synthesize all prior analysis into a risk-disclosed conclusion with a full evidence chain and recommended actions.

**Input Schema:**
```json
{
  "type": "object",
  "properties": {
    "core_analysis_scorecard": {"type": "object"},
    "evidence_bundle": {"type": "object"},
    "knowledge_evidence": {"type": "object"}
  },
  "required": ["core_analysis_scorecard"]
}
```

**Output Schema:**
```json
{
  "type": "object",
  "properties": {
    "conclusion": {"type": "string", "enum": ["Optimal System", "Conditional (sizing)", "Water-Quality Risk", "Inconclusive"]},
    "scenarios": {"type": "array"},
    "key_risks": {"type": "array"},
    "evidence_chain": {"type": "object"},
    "remediation": {"type": "object"},
    "disclosure": {"type": "string"}
  },
  "required": ["conclusion", "disclosure"]
}
```

**Tools Required:** Reasoning, Skill('sub-knowledge-updater')

**Quality Gate:** Conclusion is exactly one of the declared categories; disclosure appears before conclusion.

---

## Tool Registry

### Built-in Tools

Tools are defined in `tools/registry.py` and can be dynamically invoked:

| Tool | Description | Parameters | Returns |
|------|-------------|------------|---------|
| `calculate_runoff` | Calculate rainwater runoff from roof area | `roof_area`, `rainfall`, `runoff_coefficient` | `runoff_volume_liters` |
| `size_storage` | Size storage tank from supply and demand | `annual_supply`, `daily_demand`, `reliability` | `storage_volume_liters` |
| `design_first_flush` | Design first-flush diversion system | `roof_area`, `contamination_factor` | `first_flush_volume_liters` |
| `calculate_treatment` | Calculate treatment requirements | `source_quality`, `end_use`, `volume` | `treatment_recommendations` |
| `check_compliance` | Check compliance with standards | `system_design`, `standards` | `compliance_assessment` |
| `estimate_costs` | Estimate system costs | `system_components`, `location` | `cost_breakdown` |

### Tool Invocation Example

```python
from tools.registry import get_tool_registry

registry = get_tool_registry()

result = registry.execute(
    "calculate_runoff",
    {
        "roof_area": 200,  # m²
        "rainfall": 1200,  # mm/year
        "runoff_coefficient": 0.9
    }
)

if result.success:
    print(f"Runoff: {result.data} liters/year")
```

---

## Hooks System

### Available Hooks

Hooks are defined in `hooks/manager.py` and can be registered to respond to lifecycle events:

| Hook Event | Description | Context Data |
|------------|-------------|--------------|
| `BEFORE_SKILL_LOAD` | Before skill loads into memory | `skill_name`, `config` |
| `AFTER_SKILL_LOAD` | After skill loads successfully | `skill_name`, `load_time_ms` |
| `BEFORE_SKILL_EXECUTE` | Before skill execution begins | `query`, `requirements` |
| `AFTER_SKILL_EXECUTE` | After skill execution completes | `result`, `execution_time_ms` |
| `BEFORE_SUBSKILL_INVOKE` | Before sub-skill invocation | `subskill_name`, `inputs` |
| `AFTER_SUBSKILL_INVOKE` | After sub-skill completes | `subskill_name`, `outputs` |
| `BEFORE_QUALITY_GATE` | Before quality gate check | `gate_name`, `output` |
| `AFTER_QUALITY_GATE` | After quality gate check | `gate_name`, `passed`, `auto_fix_applied` |
| `ON_ERROR` | When an error occurs | `error`, `context` |
| `STATE_CHANGE` | When shared state changes | `key`, `old_value`, `new_value` |

### Hook Registration Example

```python
from hooks.manager import get_hook_manager, HookEvent

manager = get_hook_manager()

@manager.register(
    HookEvent.BEFORE_SKILL_EXECUTE,
    priority=10
)
def log_execution(context):
    print(f"Executing skill with query: {context.data.get('query')}")

@manager.register(
    HookEvent.ON_ERROR,
    conditions={"severity": "critical"}
)
def handle_critical_errors(context):
    # Send alert for critical errors
    pass
```

---

## Configuration Management

### Configuration Structure

Configuration is managed through `config/config.py` with the following structure:

| Section | Purpose | Key Parameters |
|---------|---------|----------------|
| `environment` | Deployment environment | `development`, `staging`, `production` |
| `llm` | LLM interaction settings | `model`, `temperature`, `max_tokens`, `cache_enabled` |
| `knowledge` | Knowledge pipeline config | `keywords`, `update_interval_hours`, `max_entries` |
| `sources` | Authoritative sources config | `primary_sources`, `fallback_enabled`, `cache_sources` |
| `quality_gates` | Quality gate enforcement | `max_retries`, `strict_mode`, `auto_fix_enabled` |
| `monitoring` | Monitoring and metrics | `log_level`, `metrics_enabled`, `performance_tracking` |
| `feature_flags` | Feature toggles | Custom feature flags |

### Accessing Configuration

```python
from config.config import get_config

config = get_config()

# Access configuration
model = config.llm.model
timeout = config.llm.timeout_seconds

# Reload configuration
from config.config import reload_config
config = reload_config()
```

---

## Quality Gates

### Universal Gates (U1-U6)

Mandatory for all projects:

| Gate | Criterion |
|------|-----------|
| U1 | ≥3 sources cited, ≥1 academic/authoritative |
| U2 | Safety/risk/limitation disclosure present BEFORE recommendation |
| U3 | Evidence hierarchy stated per source (Tier 1–4) |
| U4 | Language matches user preference |
| U5 | Output uses project's declared output template |
| U6 | Every claim traceable to ≥1 cited source OR flagged as judgment |

### Domain Gates (G1-G4)

Specific to building rainwater harvesting:

| Gate | Criterion | Auto-Fix |
|------|-----------|----------|
| G1 | Runoff calculated with documented coefficients | Add standard coefficient table |
| G2 | Storage sized from both supply and demand analysis | Add demand-side sizing |
| G3 | Treatment design matched to end-use classification | Add treatment matrix |
| G4 | At least 2 compliance standards referenced | Add standard references |

---

## Output Template

All outputs MUST follow this structure:

```markdown
# Building Rainwater Harvesting Analysis: [Object]

## Executive Summary
[2-3 sentence summary of findings and conclusion]

## System Requirements
- Object of Analysis: [from requirements step]
- Scope: [defined scope]
- Constraints: [identified constraints]

## Analysis

### Runoff Analysis
[Runoff calculations, coefficients, assumptions]

### Storage Design
[Supply/demand balance, sizing methodology, reliability analysis]

### Treatment System
[First-flush design, treatment train, end-use matching]

### Regulatory Compliance
[Standards referenced, compliance assessment, permits required]

## Scenarios
[Best case, typical, worst case scenarios]

## Risk Assessment
[Key risks, mitigation strategies, limitations]

## Evidence and Sources
[Tier 1–4 categorized sources with access dates]

## Disclosure
[Safety/limitation/risk disclosure BEFORE recommendation]

## Recommendations
[Actionable recommendations with priority]

## Implementation Notes
[Maintenance requirements, monitoring, optimization opportunities]
```

---

## Error Handling and Graceful Degradation

### Degradation Levels

The skill implements 5 degradation levels:

| Level | Condition | Behavior |
|-------|-----------|----------|
| 0 | Full operation | All systems operational |
| 1 | External sources unavailable | Fallback to knowledge base |
| 2 | Knowledge base outdated | Use cached data with explicit limitation |
| 3 | Real-time data unavailable | Use reference values with strong limitation |
| 4 | Critical failure | Abort with clear error message |

### Limitation Banners

When operating in degraded mode, include:

```markdown
---
⚠️ LIMITATION NOTICE
This analysis was conducted without access to [specific data source].
Results are based on [alternative source/reference values] and may not reflect
current conditions. Verify with up-to-date local data before implementation.
---
```

---

## Knowledge Pipeline

### Update Schedule

```cron
# Weekly academic update (Mondays 8:00 AM)
0 8 * * 1 python tools/knowledge_updater.py >> logs/knowledge_update.log 2>&1

# Daily news update (Daily 7:00 AM)
0 7 * * * python tools/knowledge_updater.py --news-only >> logs/knowledge_news.log 2>&1
```

### Manual Execution

```bash
# Dry run to preview updates
python tools/knowledge_updater.py --dry-run

# Update specific topics
python tools/knowledge_updater.py --keywords "rainwater treatment UV"

# News only
python tools/knowledge_updater.py --news-only
```

---

## Testing and Validation

### Running Tests

```bash
# Run all test scenarios
python tools/run_test_scenarios.py

# Run with specific scenario
python tools/run_test_scenarios.py --scenario standard

# Generate coverage report
python tools/run_test_scenarios.py --coverage
```

### Test Scenarios

Located in `tests/test-scenarios.md`:

1. **Standard Scenario:** Full system design request
2. **Minimal Input:** Limited parameters provided
3. **Comparison:** Multiple design alternatives
4. **Risk/Conflict:** Identifying and mitigating risks
5. **Degraded Mode:** Operation without external sources

---

## Performance Metrics

The skill tracks the following metrics:

| Metric | Description | Target |
|--------|-------------|--------|
| Execution Time | End-to-end execution time | 80% |
| Source Retrieval Rate | Successful data source access | >90% |
| Knowledge Hit Rate | Knowledge base cache hits | >70% |

---

## Maintenance

### Regular Maintenance Tasks

- [ ] Weekly: Review knowledge update logs for failed fetches
- [ ] Monthly: Review and update authoritative source URLs
- [ ] Quarterly: Run full test suite and review results
- [ ] Annually: Review and update skill architecture

### Configuration Updates

To update configuration:

```python
from config.config import ConfigManager, SkillConfig

manager = ConfigManager()
config = manager.get()

# Update specific setting
new_config = SkillConfig(
    **config.to_dict(),
    llm=LLMConfig(model="claude-sonnet-4-6")  # Update model
)

manager.save(new_config)
```

---

## Extension Points

### Adding New Sub-Skills

1. Create file in `skills/sub-[name].md`
2. Add frontmatter with name and description
3. Define Role, Workflow, Tools, Output Format, Quality Gates
4. Register in main harness w

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [dungnotnull](https://github.com/dungnotnull)
- **Source:** [dungnotnull/building-rainwater-harvesting-agent-skill](https://github.com/dungnotnull/building-rainwater-harvesting-agent-skill)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-dungnotnull-building-rainwater-harvesting-agent-skill-building-rainwater-harvesting-agent-skill
- Seller: https://agentstack.voostack.com/s/dungnotnull
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.