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aerospace-expert航空航天专家

Agent Skill

用于辅助前端页面、组件、样式和交互逻辑的开发与维护。它适合让 Agent 生成或审查 React、Next.js、Vue、Tailwind、CSS 等相关代码,整理组件结构,或定位布局和性能问题。使用时需要结合项目现有设计系统、路由和构建方式,避免只生成孤立片段;涉及页面改动时,应配合本地预览和构建检查确认视觉效果。

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GitHub Stars

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aerospace-expert(航空航天专家)
来源仓库:https://github.com/personamanagmentlayer/pcl
仓库路径:skills/aerospace-expert
安装命令:
npx skills add https://github.com/personamanagmentlayer/pcl --skill aerospace-expert
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/personamanagmentlayer/pcl --skill aerospace-expert

简介

aerospace-expert 提供航空航天系统、飞行管理、航电设备、空管系统及适航法规的专业指导与开发支持。

  • 覆盖 FMS、MRO、ATC、ACARS、ADS-B 等技术模块,适用于航空软件开发与安全合规设计。
  • 可协助构建飞机健康监控、FOQA、地面保障等子系统,支持 FAA/EASA 标准落地实施。
  • 使用时需明确业务场景(商用/军用/航天)、产品层级(OEM/Tier1)及认证要求边界。
  • 建议配合具体项目架构评估技术可行性,避免直接套用孤立代码片段。

SKILL.md

Aerospace Expert

Expert guidance for aerospace systems, flight management, maintenance tracking, aviation safety, air traffic control systems, and aerospace software development.

Core Concepts

Aerospace Systems

  • Flight Management Systems (FMS)
  • Maintenance, Repair, and Overhaul (MRO)
  • Air Traffic Control (ATC) systems
  • Aircraft Health Monitoring
  • Flight Operations Quality Assurance (FOQA)
  • Crew resource management
  • Ground handling systems

Aviation Technologies

  • Avionics systems
  • ACARS (Aircraft Communications Addressing and Reporting System)
  • ADS-B (Automatic Dependent Surveillance-Broadcast)
  • Flight data recorders (black boxes)
  • Weather radar systems
  • Autopilot and fly-by-wire
  • Satellite communications

Standards and Regulations

  • FAA regulations (Federal Aviation Administration)
  • EASA standards (European Union Aviation Safety Agency)
  • ICAO standards (International Civil Aviation Organization)
  • DO-178C (software airworthiness)
  • DO-254 (hardware airworthiness)
  • SPEC-42 (maintenance tracking)
  • ATA chapters (maintenance organization)

Flight Management System

from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import List, Optional, Tuple
from decimal import Decimal
from enum import Enum
import numpy as np

class FlightPhase(Enum):
    PRE_FLIGHT = "pre_flight"
    TAXI = "taxi"
    TAKEOFF = "takeoff"
    CLIMB = "climb"
    CRUISE = "cruise"
    DESCENT = "descent"
    APPROACH = "approach"
    LANDING = "landing"
    COMPLETED = "completed"

class FlightStatus(Enum):
    SCHEDULED = "scheduled"
    BOARDING = "boarding"
    DEPARTED = "departed"
    EN_ROUTE = "en_route"
    DELAYED = "delayed"
    ARRIVED = "arrived"
    CANCELLED = "cancelled"

@dataclass
class Waypoint:
    """Navigation waypoint"""
    name: str
    latitude: float
    longitude: float
    altitude_ft: int
    estimated_time: datetime

@dataclass
class Flight:
    """Flight information"""
    flight_number: str
    aircraft_id: str
    aircraft_type: str
    departure_airport: str
    arrival_airport: str
    scheduled_departure: datetime
    scheduled_arrival: datetime
    actual_departure: Optional[datetime]
    actual_arrival: Optional[datetime]
    status: FlightStatus
    route: List[Waypoint]
    crew_members: List[str]
    passenger_count: int
    cargo_weight_kg: float

@dataclass
class FlightPlan:
    """Filed flight plan"""
    flight_plan_id: str
    flight_number: str
    aircraft_id: str
    departure: str
    destination: str
    alternate_airports: List[str]
    route_string: str
    cruise_altitude_ft: int
    cruise_speed_kts: int
    estimated_flight_time: timedelta
    fuel_required_kg: float
    filed_at: datetime

class FlightManagementSystem:
    """Flight planning and management"""

    def __init__(self):
        self.flights = {}
        self.flight_plans = {}
        self.aircraft_positions = {}

    def create_flight_plan(self, flight_data: dict) -> FlightPlan:
        """Create and file flight plan"""
        flight_plan_id = self._generate_flight_plan_id()

        # Calculate route
        route = self._calculate_optimal_route(
            flight_data['departure'],
            flight_data['destination'],
            flight_data['aircraft_type']
        )

        # Calculate fuel requirements
        fuel_required = self._calculate_fuel_requirements(
            route['distance_nm'],
            flight_data['aircraft_type'],
            flight_data.get('passenger_count', 0),
            flight_data.get('cargo_weight_kg', 0)
        )

        flight_plan = FlightPlan(
            flight_plan_id=flight_plan_id,
            flight_number=flight_data['flight_number'],
            aircraft_id=flight_data['aircraft_id'],
            departure=flight_data['departure'],
            destination=flight_data['destination'],
            alternate_airports=flight_data.get('alternates', []),
            route_string=route['route_string'],
            cruise_altitude_ft=route['cruise_altitude'],
            cruise_speed_kts=route['cruise_speed'],
            estimated_flight_time=route['estimated_time'],
            fuel_required_kg=fuel_required,
            filed_at=datetime.now()
        )

        self.flight_plans[flight_plan_id] = flight_plan

        # File with ATC
        self._file_with_atc(flight_plan)

        return flight_plan

    def _calculate_optimal_route(self,
                                 departure: str,
                                 destination: str,
                                 aircraft_type: str) -> dict:
        """Calculate optimal flight route"""
        # Get airport coordinates
        dep_coords = self._get_airport_coordinates(departure)
        dest_coords = self._get_airport_coordinates(destination)

        # Calculate great circle distance
        distance_nm = self._calculate_distance(dep_coords, dest_coords)

        # Determine cruise altitude based on distance and aircraft
        if distance_nm < 500:
            cruise_altitude = 25000  # FL250
        elif distance_nm < 1500:
            cruise_altitude = 35000  # FL350
        else:
            cruise_altitude = 39000  # FL390

        # Determine cruise speed based on aircraft type
        cruise_speeds = {
            'B737': 450,   # knots
            'B777': 490,
            'A320': 450,
            'A350': 490
        }
        cruise_speed = cruise_speeds.get(aircraft_type, 450)

        # Calculate flight time
        flight_time_hours = distance_nm / cruise_speed
        estimated_time = timedelta(hours=flight_time_hours)

        # Generate route string (simplified)
        route_string = f"{departure} DCT {destination}"

        return {
            'distance_nm': distance_nm,
            'cruise_altitude': cruise_altitude,
            'cruise_speed': cruise_speed,
            'estimated_time': estimated_time,
            'route_string': route_string
        }

    def _calculate_fuel_requirements(self,
                                    distance_nm: float,
                                    aircraft_type: str,
                                    passengers: int,
                                    cargo_kg: float) -> float:
        """Calculate required fuel for flight"""
        # Fuel consumption rates (kg per nm)
        fuel_rates = {
            'B737': 3.5,
            'B777': 8.0,
            'A320': 3.2,
            'A350': 7.5
        }

        base_rate = fuel_rates.get(aircraft_type, 4.0)

        # Calculate trip fuel
        trip_fuel = distance_nm * base_rate

        # Add weight penalty (simplified)
        weight_penalty = (passengers * 100 + cargo_kg) / 10000 * trip_fuel * 0.1

        # Reserve fuel (45 minutes at cruise)
        reserve_fuel = base_rate * 45 * 7.5  # 7.5 nm per minute

        # Contingency fuel (5% of trip fuel)
        contingency_fuel = trip_fuel * 0.05

        # Alternate fuel (for diversion)
        alternate_fuel = 100 * base_rate  # 100 nm

        total_fuel = trip_fuel + weight_penalty + reserve_fuel + contingency_fuel + alternate_fuel

        return total_fuel

    def track_flight_progress(self, flight_number: str) -> dict:
        """Track real-time flight progress"""
        flight = self.flights.get(flight_number)
        if not flight:
            return {'error': 'Flight not found'}

        # Get current position
        current_position = self.aircraft_positions.get(flight.aircraft_id)

        if not current_position:
            return {
                'flight_number': flight_number,
                'status': flight.status.value,
                'message': 'No position data available'
            }

        # Calculate progress
        total_distance = self._calculate_distance(
            self._get_airport_coordinates(flight.departure_airport),
            self._get_airport_coordinates(flight.arrival_airport)
        )

        distance_from_origin = self._calculate_distance(
            self._get_airport_coordinates(flight.departure_airport),
            (current_position['latitude'], current_position['longitude'])
        )

        progress_percent = (distance_from_origin / total_distance) * 100

        # Calculate ETA
        if current_position.get('ground_speed', 0) > 0:
            distance_remaining = total_distance - distance_from_origin
            time_remaining_hours = distance_remaining / current_position['ground_speed']
            eta = datetime.now() + timedelta(hours=time_remaining_hours)
        else:
            eta = flight.scheduled_arrival

        return {
            'flight_number': flight_number,
            'status': flight.status.value,
            'current_position': {
                'latitude': current_position['latitude'],
                'longitude': current_position['longitude'],
                'altitude_ft': current_position['altitude_ft'],
                'ground_speed_kts': current_position['ground_speed']
            },
            'progress_percent': progress_percent,
            'distance_remaining_nm': total_distance - distance_from_origin,
            'estimated_arrival': eta.isoformat(),
            'on_time': eta <= flight.scheduled_arrival
        }

    def calculate_landing_performance(self,
                                     aircraft_type: str,
                                     runway_length_ft: int,
                                     wind_speed_kts: int,
                                     wind_direction: int,
                                     runway_heading: int,
                                     temperature_c: float,
                                     altitude_ft: int) -> dict:
        """Calculate landing performance requirements"""
        # Base landing distance for aircraft type
        base_distances = {
            'B737': 5000,  # feet
            'B777': 7000,
            'A320': 4800,
            'A350': 6500
        }

        base_distance = base_distances.get(aircraft_type, 5500)

        # Wind component calculation
        wind_angle = abs(wind_direction - runway_heading)
        headwind = wind_speed_kts * np.cos(np.radians(wind_angle))
        crosswind = wind_speed_kts * np.sin(np.radians(wind_angle))

        # Adjust for headwind/tailwind
        # Headwind: reduce distance by 10% per 10 knots
        # Tailwind: increase distance by 20% per 10 knots
        if headwind > 0:  # Headwind
            distance_adjustment = -0.1 * (headwind / 10)
        else:  # Tailwind
            distance_adjustment = 0.2 * (abs(headwind) / 10)

        # Adjust for temperature (density altitude)
        isa_temp = 15 - (altitude_ft / 1000 * 2)  # ISA standard
        temp_deviation = temperature_c - isa_temp
        temp_adjustment = temp_deviation * 0.01  # 1% per degree

        # Calculate required landing distance
        adjustments = 1 + distance_adjustment + temp_adjustment
        required_distance = base_distance * adjustments

        # Safety margin (typical 1.67 for dry runway)
        safety_factor = 1.67
        required_distance_with_margin = required_distance * safety_factor

        # Check if runway is adequate
        runway_adequate = runway_length_ft >= required_distance_with_margin

        return {
            'aircraft_type': aircraft_type,
            'required_landing_distance_ft': int(required_distance_with_margin),
            'available_runway_ft': runway_length_ft,
            'runway_adequate': runway_adequate,
            'margin_ft': runway_length_ft - required_distance_with_margin,
            'conditions': {
                'headwind_kts': headwind,
                'crosswind_kts': crosswind,
                'temperature_c': temperature_c,
                'altitude_ft': altitude_ft
            }
        }

    def _calculate_distance(self, point1: Tuple[float, float], point2: Tuple[float, float]) -> float:
        """Calculate great circle distance in nautical miles"""
        from math import radians, sin, cos, sqrt, atan2

        lat1, lon1 = radians(point1[0]), radians(point1[1])
        lat2, lon2 = radians(point2[0]), radians(point2[1])

        dlat = lat2 - lat1
        dlon = lon2 - lon1

        a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
        c = 2 * atan2(sqrt(a), sqrt(1-a))

        distance_km = 6371 * c  # Earth radius in km
        distance_nm = distance_km * 0.539957  # Convert to nautical miles

        return distance_nm

    def _get_airport_coordinates(self, icao_code: str) -> Tuple[float, float]:
        """Get airport coordinates"""
        # Would query airport database
        airports = {
            'KJFK': (40.6413, -73.7781),  # JFK
            'KLAX': (33.9416, -118.4085),  # LAX
            'EGLL': (51.4700, -0.4543),    # Heathrow
            'LFPG': (49.0097, 2.5479)      # Charles de Gaulle
        }
        return airports.get(icao_code, (0.0, 0.0))

    def _file_with_atc(self, flight_plan: FlightPlan):
        """File flight plan with ATC"""
        # Implementation would submit to ATC systems
        pass

    def _generate_flight_plan_id(self) -> str:
        import uuid
        return f"FPL-{uuid.uuid4().hex[:10].upper()}"

Aircraft Maintenance System

from enum import Enum

class MaintenanceType(Enum):
    A_CHECK = "a_check"  # Every 400-600 flight hours
    B_CHECK = "b_check"  # Every 6-8 months
    C_CHECK = "c_check"  # Every 18-24 months
    D_CHECK = "d_check"  # Every 6-10 years
    LINE_MAINTENANCE = "line_maintenance"
    UNSCHEDULED = "unscheduled"

@dataclass
class Aircraft:
    """Aircraft information"""
    aircraft_id: str
    registration: str
    aircraft_type: str
    manufacturer: str
    model: str
    serial_number: str
    manufacture_date: datetime
    total_flight_hours: float
    total_cycles: int  # Takeoff/landing cycles
    last_a_check: datetime
    last_c_check: datetime
    airworthiness_certificate: str
    next_major_inspection: datetime

@dataclass
class MaintenanceRecord:
    """Maintenance work record"""
    record_id: str
    aircraft_id: str
    maintenance_type: MaintenanceType
    work_performed: str
    components_replaced: List[str]
    performed_by: str
    performed_at: datetime
    flight_hours_at_maintenance: float
    cycles_at_maintenance: int
    next_due_hours: Optional[float]
    next_due_date: Optional[datetime]

class AircraftMaintenanceSystem:
    """MRO (Maintenance, Repair, Overhaul) system"""

    def __init__(self):
        self.aircraft = {}
        self.maintenance_records = []
        self.component_tracking = {}

    def check_maintenance_due(self, aircraft_id: str) -> dict:
        """Check if maintenance is due for aircraft"""
        aircraft = self.aircraft.get(aircraft_id)
        if not aircraft:
            return {'error': 'Aircraft not found'}

        due_items = []

        # Check A-check (every 500 hours)
        hours_since_a_check = aircraft.total_flight_hours - self._get_last_check_hours(
            aircraft_id, MaintenanceType.A_CHECK
        )

        if hours_since_a_check >= 500:
            due_items.append({
                'type': 'A-check',
                'urgency': 'high' if hours_since_a_check >= 550 else 'medium',
                'hours_overdue': max(0, hours_since_a_check - 500)
            })

        # Check calendar-based C-check
        days_since_c_check = (datetime.now() - aircraft.last_c_check).days

        if days_since_c_check >= 540:  # 18 months
            due_items.append({
                'type': 'C-check',
                'urgency': 'critical' if days_since_c_check >= 600 else 'high',
                'days_overdue': max(0, days_since_c_check - 540)
            })

        # Check component life limits
        component_items = self._check_component_life_limits(aircraft_id)
        due_items.extend(component_items)

        return {
            'aircraft_id': aircraft_id,
            'registration': aircraft.registration,
            'maintenance_required': len(due_items) > 0,
            'due_items': due_items,
            'airworthy': len([item for item in due_items if item['urgency'] == 'critical']) == 0
        }

    def _get_last_check_hours(self, aircraft_id: str, check_type: MaintenanceType) -> float:
        """Get flight hours at last check"""
        records = [
            r for r in self.maintenance_records
            if r.aircraft_id == aircraft_id and r.maintenance_type == check_type
        ]

        if records:
            latest = max(records, key=lambda r: r.performed_at)
            return latest.flight_hours_at_maintenance

        return 0.0

    def _check_component_life_limits(self, aircraft_id: str) -> List[dict]:
        """Check component life limits"""
        due_items = []

        components = self.component_tracking.get(aircraft_id, {})

        for component_name, component_data in components.items():
            if component_data['life_limit_hours']:
                hours_used = component_data['hours_since_new']
                life_limit = component_data['life_limit_hours']

                if hours_used >= life_limit * 0.9:  # Within 90% of life limit
                    due_items.append({
                        'type': 'component_replacement',
                        'component': component_name,
                        'urgency': 'critical' if hours_used >= life_limit else 'high',
                        'hours_remaining': max(0, life_limit - hours_used)
                    })

        return due_items

    def record_maintenance(self,
                          aircraft_id: str,
                          maintenance_data: dict) -> MaintenanceRecord:
        """Record completed maintenance"""
        aircraft = self.aircraft.get(aircraft_id)
        if not aircraft:
            raise ValueError("Aircraft not found")

        record = MaintenanceRecord(
            record_id=self._generate_record_id(),
            aircraft_id=aircraft_id,
            maintenance_type=MaintenanceType(maintenance_data['type']),
            work_performed=maintenance_data['work_performed'],
            components_replaced=maintenance_data.get('components_replaced', []),
            performed_by=maintenance_data['technician_id'],
            performed_at=datetime.now(),
            flight_hours_at_maintenance=aircraft.total_flight_hours,
            cycles_at_maintenance=aircraft.total_cycles,
            next_due_hours=maintenance_data.get('next_due_hours'),
            next_due_date=maintenance_data.get('next_due_date')
        )

        self.maintenance_records.append(record)

        # Update aircraft maintenance dates
        if record.maintenance_type == MaintenanceType.A_CHECK:
            aircraft.last_a_check = datetime.now()
        elif record.maintenance_type == MaintenanceType.C_CHECK:
            aircraft.last_c_check = datetime.now()

        return record

    def predict_maintenance_cost(self,
                                aircraft_type: str,
                                flight_hours_per_year: float) -> dict:
        """Predict annual maintenance costs"""
        # Base maintenance costs per aircraft type
        base_costs = {
            'B737': {
                'hourly_rate': 800,  # $ per flight hour
                'a_check': 25000,
                'c_check': 500000,
                'd_check': 5000000
            },
            'B777': {
                'hourly_rate': 1500,
                'a_check': 50000,
                'c_check': 1000000,
                'd_check': 10000000
            }
        }

        costs = base_costs.get(aircraft_type, base_costs['B737'])

        # Calculate annual costs
        hourly_maintenance = flight_hours_per_year * costs['hourly_rate']

        # A-checks (assume 2 per year for 1000 hours/year)
        a_checks_per_year = flight_hours_per_year / 500
        a_check_costs = a_checks_per_year * costs['a_check']

        # C-check (amortized over 18 months)
        c_check_annual = costs['c_check'] / 1.5

        # D-check (amortized over 8 years)
        d_check_annual = costs['d_check'] / 8

        total_annual = hourly_maintenance + a_check_costs + c_check_annual + d_check_annual

        return {
            'aircraft_type': aircraft_type,
            'flight_hours_per_year': flight_hours_per_year,
            'maintenance_costs': {
                'hourly_maintenance': hourly_maintenance,
                'a_checks': a_check_costs,
                'c_check_amortized': c_check_annual,
                'd_check_amortized': d_check_annual,
                'total_annual': total_annual
            },
            'cost_per_flight_hour': total_annual / flight_hours_per_year
        }

    def _generate_record_id(self) -> str:
        import uuid
        return f"MX-{uuid.uuid4().hex[:10].upper()}"

Aviation Safety Analysis

class AviationSafetySystem:
    """Flight safety and FOQA analysis"""

    def __init__(self):
        self.safety_reports = []
        self.foqa_events = []

    def analyze_flight_data(self, flight_data: dict) -> dict:
        """Analyze flight data for safety events (FOQA)"""
        events_detected = []

        # Check for hard landings
        if flight_data.get('landing_vertical_speed_fpm', 0) < -600:
            events_detected.append({
                'event_type': 'hard_landing',
                'severity': 'medium',
                'value': flight_data['landing_vertical_speed_fpm'],
                'threshold': -600
            })

        # Check for unstabilized approaches
        if flight_data.get('approach_speed_deviation_kts', 0) > 10:
            events_detected.append({
                'event_type': 'unstabilized_approach',
                'severity': 'high',
                'value': flight_data['approach_speed_deviation_kts'],
                'threshold': 10
            })

        # Check for altitude deviations
        if flight_data.get('altitude_deviation_ft', 0) > 300:
            events_detected.append({
                'event_type': 'altitude_deviation',
                'severity': 'high',
                'value': flight_data['altitude_deviation_ft'],
                'threshold': 300
            })

        # Check for excessive bank angles
        if flight_data.get('max_bank_angle_deg', 0) > 30:
            events_detected.append({
                'event_type': 'excessive_bank',
                'severity': 'medium',
                'value': flight_data['max_bank_angle_deg'],
                'threshold': 30
            })

        # Calculate overall safety score
        safety_score = 100.0 - (len(events_detected) * 10)

        return {
            'flight_number': flight_data['flight_number'],
            'events_detected': events_detected,
            'safety_score': max(0.0, safety_score),
            'requires_review': len(events_detected) > 0
        }

    def calculate_safety_metrics(self, flights_data: List[dict]) -> dict:
        """Calculate safety KPIs"""
        total_flights = len(flights_data)
        total_hours = sum(f.get('flight_hours', 0) for f in flights_data)

        # Count safety events
        safety_events = sum(
            len(self.analyze_flight_data(f)['events_detected'])
            for f in flights_data
        )

        # Event rate per 1000 flights
        event_rate = (safety_events / total_flights * 1000) if total_flights > 0 else 0

        return {
            'total_flights': total_flights,
            'total_flight_hours': total_hours,
            'safety_events': safety_events,
            'event_rate_per_1000_flights': event_rate,
            'safety_rating': 'Excellent' if event_rate < 5 else
                           'Good' if event_rate < 10 else
                           'Needs Improvement'
        }

Best Practices

Flight Operations

  • File complete and accurate flight plans
  • Conduct thorough pre-flight checks
  • Monitor fuel continuously
  • Maintain communication with ATC
  • Follow standard operating procedures (SOPs)
  • Implement crew resource management
  • Use automation appropriately

Maintenance Management

  • Follow manufacturer maintenance schedules
  • Track all component life limits
  • Maintain detailed maintenance logs
  • Use certified parts and technicians
  • Implement predictive maintenance
  • Conduct regular inspections
  • Ensure airworthiness compliance

Safety Management

  • Implement Safety Management System (SMS)
  • Encourage safety reporting culture
  • Analyze FOQA data regularly
  • Conduct regular safety audits
  • Maintain emergency procedures
  • Train crew on CRM principles
  • Track safety KPIs

Regulatory Compliance

  • Maintain current certifications
  • Follow DO-178C for software
  • Implement quality management systems
  • Conduct regular audits
  • Maintain proper documentation
  • Follow ATA chapter organization
  • Ensure ETOPS compliance (if applicable)

Anti-Patterns

❌ Delaying required maintenance ❌ Poor flight planning ❌ Inadequate fuel reserves ❌ Ignoring weather conditions ❌ Poor crew communication ❌ No safety management system ❌ Inadequate record keeping ❌ Using uncertified parts ❌ Skipping pre-flight checks

Resources

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.99%
按下载量换算218

OpenCode

23.39%
按下载量换算189

Codex

19.86%
按下载量换算160

Antigravity

14%
按下载量换算113

Gemini CLI

7.5%
按下载量换算61

windsurf

3.57%
按下载量换算29

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

继续浏览同类 Skills