# Water Rescue Drone Design > Water-Rescue Drone Design & Testing — A production-grade AI agent harness for Search-and-Rescue Drone Engineering. Use when user asks about drone design, water rescue operations, UAV specifications, search-and-rescue planning, maritime drone testing, or life-saving drone equipment. This skill provides evidence-backed analysis using real-time data aggregation, domain methods (energy budget, search… - **Type:** Skill - **Install:** `agentstack add skill-dungnotnull-water-rescue-drone-design-agent-skill-water-rescue-drone-design-agent-skill` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [dungnotnull](https://agentstack.voostack.com/s/dungnotnull) - **Installs:** 0 - **Category:** [Search](https://agentstack.voostack.com/c/search) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [dungnotnull](https://github.com/dungnotnull) - **Source:** https://github.com/dungnotnull/water-rescue-drone-design-agent-skill ## Install ```sh agentstack add skill-dungnotnull-water-rescue-drone-design-agent-skill-water-rescue-drone-design-agent-skill ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Water Rescue Drone Design — Skill Registry ## Overview The `water-rescue-drone-design` skill is a **production-grade AI agent harness** that transforms LLMs into domain experts for Search-and-Rescue Drone Engineering for Water. It orchestrates a multi-step pipeline that combines real-time data aggregation, recognized engineering methods, and academic research into evidence-backed, risk-disclosed outputs. ## Skill Registration ### Registration Pattern Skills are registered in the harness via the `SkillRegistry` class in `water_rescue_drone/skills/__init__.py`: ```python from water_rescue_drone.skills import SkillRegistry from water_rescue_drone.skills.gather_requirements import GatherRequirementsSkill registry = SkillRegistry() registry.register("gather_requirements", GatherRequirementsSkill) ``` ### Skill Resolution The agent resolves skills by: 1. Loading the skill's markdown template from `skills/.md` 2. Instantiating the corresponding Python class from `water_rescue_drone/skills/` 3. Passing the `AgentConfig` and `LLMProvider` to the skill constructor 4. Executing the skill via the `BaseSkill.run(ctx)` method ### Skill Execution Flow ``` 1. Load Template → 2. Build Prompt → 3. LLM Call → 4. Parse JSON → 5. Apply to Context ``` Each skill: - Loads its persona and workflow from the markdown template - Builds a structured prompt from the current `AgentContext` - Calls the LLM provider with JSON mode enabled - Parses and validates the structured response against a schema - Merges the result back into the context - Records a `StepRecord` for auditability ## Registered Skills ### 1. gather_requirements **Purpose:** Clarify object/scope/timeframe/inputs/language before fetching. **Input Schema:** ```json { "type": "object", "properties": { "user_input": {"type": "string"}, "context": {"$ref": "#/definitions/AgentContext"} }, "required": ["user_input"] } ``` **Output Schema:** ```json { "type": "object", "properties": { "object": {"type": "string"}, "scope": {"type": "string"}, "timeframe": {"type": "string"}, "available_inputs": {"type": "array", "items": {"type": "string"}}, "target_audience": {"type": "string"}, "language": {"type": "string", "enum": ["en", "vi"]}, "analysis_type": {"type": "string"} }, "required": ["object", "language"] } ``` ### 2. evidence_collector **Purpose:** Fetch authoritative real-time + reference data. **Input Schema:** ```json { "type": "object", "properties": { "requirements": {"$ref": "#/definitions/Requirements"}, "context": {"$ref": "#/definitions/AgentContext"} } } ``` **Output Schema:** ```json { "type": "object", "properties": { "evidence_items": { "type": "array", "items": { "type": "object", "properties": { "source": {"type": "string"}, "date": {"type": "string"}, "tier": {"type": "string", "enum": ["1", "2", "3", "4"]}, "content": {"type": "string"}, "url": {"type": "string"} } } } } } ``` ### 3. core_analysis **Purpose:** Design payload/sensors/endurance/path/reliability + scenarios. **Input Schema:** ```json { "type": "object", "properties": { "requirements": {"$ref": "#/definitions/Requirements"}, "evidence": {"$ref": "#/definitions/Evidence"} } } ``` **Output Schema:** ```json { "type": "object", "properties": { "drone_type": {"type": "string"}, "payload": {"type": "object"}, "drop_mechanism": {"type": "string"}, "sensors": {"type": "array"}, "endurance": {"type": "object"}, "wind_resistance": {"type": "number"}, "water_ingress": {"type": "string"}, "search_path": {"type": "string"}, "reliability": {"type": "number"}, "certification": {"type": "array"}, "scenarios": {"type": "array"}, "metrics": {"type": "object"} } } ``` ### 4. knowledge_updater **Purpose:** Surface academic citations with tiers; flag gaps. **Input Schema:** ```json { "type": "object", "properties": { "query": {"type": "string"}, "context": {"$ref": "#/definitions/AgentContext"} } } ``` **Output Schema:** ```json { "type": "object", "properties": { "citations": { "type": "array", "items": { "type": "object", "properties": { "authors": {"type": "array", "items": {"type": "string"}}, "title": {"type": "string"}, "year": {"type": "number"}, "doi": {"type": "string"}, "tier": {"type": "string"}, "relevance": {"type": "number"} } } }, "gaps": {"type": "array", "items": {"type": "string"}}, "coverage_rating": {"type": "number"} } } ``` ### 5. advisor **Purpose:** Synthesize risk-disclosed conclusion + evidence chain. **Input Schema:** ```json { "type": "object", "properties": { "analysis": {"$ref": "#/definitions/CoreAnalysis"}, "knowledge": {"$ref": "#/definitions/KnowledgeCitations"}, "context": {"$ref": "#/definitions/AgentContext"} } } ``` **Output Schema:** ```json { "type": "object", "properties": { "verdict": { "type": "string", "enum": ["RECOMMENDED", "CONDITIONALLY_RECOMMENDED", "NOT_RECOMMENDED", "INSUFFICIENT_DATA"] }, "scenarios": {"type": "array"}, "risks": {"type": "array"}, "evidence_chain": {"type": "array"}, "remediation": {"type": "string"}, "disclosure": {"type": "string"} } } ``` ## Quality Gates The skill enforces quality gates at two levels: ### Universal Gates (U1-U6) - **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 declared output template - **U6:** Every claim traceable to ≥1 cited source OR flagged as judgment ### Domain Gates (G1-G4) - **G1:** Payload capacity validated against drop mechanism - **G2:** Endurance calculation accounts for weather/wind - **G3:** Sensor coverage adequate for target area - **G4:** Reliability estimate includes redundancy analysis ### Gate Enforcement ```python from water_rescue_drone.gates import QualityGateRunner runner = QualityGateRunner(config) results = runner.evaluate_all(context) failed = runner.summary(results)["failed"] if config.strict_gates and failed > 0: raise GateFailure(f"{failed} gates failed") ``` ## Tool Definitions The skill uses the following tools with their respective schemas: ### WebSearch Tool **Purpose:** Search for real-time domain data. **Input Schema:** ```json { "type": "object", "properties": { "query": {"type": "string"}, "max_results": {"type": "number", "default": 10} }, "required": ["query"] } ``` **Output Schema:** ```json { "type": "array", "items": { "type": "object", "properties": { "title": {"type": "string"}, "url": {"type": "string"}, "snippet": {"type": "string"}, "date": {"type": "string"} } } } ``` ### WebFetch Tool **Purpose:** Fetch and parse web content. **Input Schema:** ```json { "type": "object", "properties": { "url": {"type": "string"}, "format": {"type": "string", "enum": ["markdown", "text"], "default": "markdown"} }, "required": ["url"] } ``` ### Read Tool **Purpose:** Read local files (knowledge base). **Input Schema:** ```json { "type": "object", "properties": { "file_path": {"type": "string"}, "offset": {"type": "number"}, "limit": {"type": "number"} }, "required": ["file_path"] } ``` ## Hooks System ### Pre-Skill Hook ```python @hook("pre_skill") def before_skill(skill_name: str, context: AgentContext): # Log skill start, validate prerequisites pass ``` ### Post-Skill Hook ```python @hook("post_skill") def after_skill(skill_name: str, result: SkillResult, context: AgentContext): # Record metrics, update analytics pass ``` ### Error Hook ```python @hook("on_error") def handle_error(skill_name: str, error: Exception, context: AgentContext): # Implement custom error handling, fallbacks pass ``` ## Graceful Degradation The skill implements 5 degradation levels (0–4): | Level | Description | Banner | |-------|-------------|--------| | 0 | Full operation | None | | 1 | Minor fallbacks | "LIMITATION: Some secondary features unavailable" | | 2 | Primary failures | "LIMITATION: Operating with reduced capability" | | 3 | Knowledge-only mode | "LIMITATION: Knowledge base only, live data unavailable" | | 4 | Critical degradation | "LIMITATION: Critical failures - review required" | ## Language Support The skill automatically detects and supports: - **English (en)** — Default - **Vietnamese (vi)** — Full localization Language detection uses keyword matching and can be overridden via `WRD_LANGUAGE` environment variable. ## CLI Usage ```bash # Run with default deterministic provider (offline) python -m water_rescue_drone "design a coastal SAR drone for 1 km range" # Run with OpenAI provider WRD_LLM_PROVIDER=openai WRD_LLM_MODEL=gpt-4 python -m water_rescue_drone "analyze UAV for lake rescue" # Run with Anthropic provider WRD_LLM_PROVIDER=anthropic WRD_LLM_MODEL=claude-3-opus python -m water_rescue_drone "design river rescue drone" # Strict mode (raise on gate failures) WRD_STRICT_GATES=true python -m water_rescue_drone "evaluate search drone" ``` ## Development ### Project Structure ``` water-rescue-drone-design/ ├── water_rescue_drone/ # Runnable Python package │ ├── agent.py # Main orchestrator │ ├── config.py # Configuration management │ ├── context.py # Typed context │ ├── errors.py # Error types │ ├── gates.py # Quality gates │ ├── knowledge.py # Knowledge integration │ ├── cli.py # CLI entry point │ ├── llm/ # Provider abstraction │ └── skills/ # Sub-skills ├── skills/ # Markdown templates │ ├── main.md # Harness specification │ └── sub-*.md # Sub-skill specifications ├── tools/ # Utilities │ ├── knowledge_updater.py # Knowledge crawl │ ├── run_test_scenarios.py # E2E validator │ └── validate_project.py # Contract validator ├── config/ # Configuration files ├── references/ # Domain knowledge ├── assets/ # Static resources ├── scripts/ # Automation scripts ├── hooks/ # Lifecycle hooks ├── SECOND-KNOWLEDGE-BRAIN.md # Knowledge base └── SKILL.md # This file ``` ### Testing ```bash # Run unit tests pytest -q # Run E2E scenarios python tools/run_test_scenarios.py # Validate project contract python tools/validate_project.py ``` ## License MIT License — See `LICENSE` file for details. ## Version History - **1.2.0** (2026-07-27) — Enhanced architecture: hooks system, modular directories, structured logging, tool schemas, configuration management, domain references - **1.1.0** (2026-07-13) — Initial production release with core harness and quality gates ## 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/water-rescue-drone-design-agent-skill](https://github.com/dungnotnull/water-rescue-drone-design-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-water-rescue-drone-design-agent-skill-water-rescue-drone-design-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%.