Token导航 LogoToken导航TokenDH.com
研究检索需要联网github未标认证来源可访问clear审计通过

planning-code-goal规划代码目标

Agent Skill

planning-code-goal 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

509

周安装

21

GitHub Stars

8

下载量

166
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:planning-code-goal(规划代码目标)
来源仓库:https://github.com/vamseeachanta/workspace-hub
仓库路径:skills/planning-code-goal
安装命令:
npx skills add https://github.com/vamseeachanta/workspace-hub --skill planning-code-goal
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/vamseeachanta/workspace-hub --skill planning-code-goal

简介

planning-code-goal 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于根据关键词、任务场景或来源线索进行信息检索与筛选的场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。
  • 安装前建议确认权限范围、维护状态及是否触发联网或文件操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Code-Centric Goal-Oriented Action Planning

SPARC-integrated planning for software development objectives with measurable outcomes

Quick Start

# Define code goal
Goal: Implement OAuth2 authentication

# SPARC-GOAP generates phased plan:
Phase 1 (Specification): Define requirements, acceptance criteria
Phase 2 (Pseudocode): Design algorithms, state machines
Phase 3 (Architecture): Design components, API contracts
Phase 4 (Refinement): TDD implementation cycles
Phase 5 (Completion): Integration, validation, deployment

# Execute with SPARC commands

When to Use

  • Feature implementation requiring systematic breakdown
  • Performance optimization with measurable targets
  • Testing strategy development with coverage goals
  • API development with clear contract definitions
  • Database evolution with migration planning
  • Technical debt reduction with incremental milestones

Prerequisites

  • Understanding of SPARC methodology phases
  • Clear definition of desired outcome
  • Access to codebase for state analysis
  • Measurable success criteria

Core Concepts

SPARC Phases in Goal Planning

PhaseGOAP RoleDeliverables
SpecificationDefine goal stateRequirements, acceptance criteria
PseudocodePlan actionsAlgorithms, state transitions
ArchitectureStructure solutionComponents, interfaces
RefinementIterate with TDDTests, implementation
CompletionValidate goalDeployment, metrics

Code State Analysis

current_state = {
  test_coverage: 45,
  performance_score: 'C',
  tech_debt_hours: 120,
  features_complete: ['auth', 'user-mgmt'],
  bugs_open: 23
}

goal_state = {
  test_coverage: 80,
  performance_score: 'A',
  tech_debt_hours: 40,
  features_complete: [...current, 'payments', 'notifications'],
  bugs_open: 5
}

Milestone Definition

interface CodeMilestone {
  id: string;
  description: string;
  sparc_phase: 'specification' | 'pseudocode' | 'architecture' | 'refinement' | 'completion';
  preconditions: string[];
  deliverables: string[];
  success_criteria: Metric[];
  estimated_hours: number;
  dependencies: string[];
}

Implementation Pattern

class SPARCGoalPlanner {
  async achieveGoal(goal: CodeGoal): Promise<GoalResult> {
    // 1. SPECIFICATION: Define goal state
    const spec = await this.specifyGoal(goal);

    // 2. PSEUDOCODE: Plan action sequence
    const actionPlan = await this.planActions(spec);

    // 3. ARCHITECTURE: Structure solution
    const architecture = await this.designArchitecture(actionPlan);

    // 4. REFINEMENT: Iterate with TDD
    const implementation = await this.refineWithTDD(architecture);

    // 5. COMPLETION: Validate and deploy
    return await this.completeGoal(implementation, spec);
  }

  async findOptimalPath(
    currentState: CodeState,
    goalState: CodeState
  ): Promise<ActionPlan> {
    const actions = this.getAvailableSPARCActions();
    return this.aStarSearch(currentState, goalState, actions);
  }
}

Configuration

sparc_goap_config:
  phases:
    specification:
      timeout_minutes: 30

    architecture:
      timeout_minutes: 45

    refinement:
      timeout_minutes: 120

    completion:
      timeout_minutes: 60

  metrics:
    test_coverage_target: 80
    performance_target: "A"
    max_tech_debt_hours: 40

  risk_assessment:
    technical_weight: 0.3
    timeline_weight: 0.3
    quality_weight: 0.2
    security_weight: 0.2

Usage Examples

Example 1: Feature Implementation Plan

goal: implement_payment_processing_with_sparc

sparc_phases:
  specification:
    deliverables:
      - requirements_doc
      - acceptance_criteria
      - test_scenarios
    success_criteria:
      - all_payment_types_defined
      - security_requirements_clear
      - compliance_standards_identified

  pseudocode:
    deliverables:
      - payment_flow_logic
      - error_handling_patterns
      - state_machine_design

  architecture:
    deliverables:
      - system_components
      - api_contracts
      - database_schema

  refinement:
    deliverables:
      - unit_tests
      - integration_tests
      - implemented_features
    success_criteria:
      - test_coverage_80_percent
      - all_tests_passing

  completion:
    deliverables:
      - deployed_system
      - documentation
      - monitoring_setup

goap_milestones:
  - setup_payment_provider:
      sparc_phase: specification
      preconditions: [api_keys_configured]
      deliverables: [provider_client, test_environment]
      success_criteria: [can_create_test_charge]

  - implement_checkout_flow:
      sparc_phase: refinement
      preconditions: [payment_provider_ready, ui_framework_setup]
      deliverables: [checkout_component, payment_form]
      success_criteria: [form_validation_works, ui_responsive]

  - add_webhook_handling:
      sparc_phase: completion
      preconditions: [server_endpoints_available]
      deliverables: [webhook_endpoint, event_processor]
      success_criteria: [handles_all_event_types, idempotent_processing]

Example 2: Performance Optimization Goal

goal: reduce_api_latency_50_percent

analysis:
  - profile_current_performance:
      tools: [profiler, APM, database_explain]
      metrics: [p50_latency, p99_latency, throughput]

optimizations:
  - database_query_optimization:
      sparc_phase: refinement
      actions: [add_indexes, optimize_joins, implement_pagination]
      expected_improvement: 30%
      success_metric: "p99 < 100ms"

  - implement_caching_layer:
      sparc_phase: architecture
      actions: [redis_setup, cache_warming, invalidation_strategy]
      expected_improvement: 25%

  - code_optimization:
      sparc_phase: refinement
      actions: [algorithm_improvements, parallel_processing, batch_operations]
      expected_improvement: 15%

Example 3: Testing Strategy Goal

goal: achieve_80_percent_coverage
current_coverage: 45

test_pyramid:
  unit_tests:
    target: 60%
    sparc_phase: refinement
    focus: [business_logic, utilities, validators]

  integration_tests:
    target: 25%
    sparc_phase: completion
    focus: [api_endpoints, database_operations, external_services]

  e2e_tests:
    target: 15%
    sparc_phase: completion
    focus: [critical_user_journeys, payment_flow, authentication]

milestones:
  - milestone_55:
      actions: [add_unit_tests_for_core_services]
      deadline: "week 1"

  - milestone_65:
      actions: [add_integration_tests_for_api]
      deadline: "week 2"

  - milestone_80:
      actions: [add_e2e_tests, increase_unit_coverage]
      deadline: "week 3"

Execution Checklist

  • Analyze current code state (coverage, performance, debt)
  • Define goal state with measurable criteria
  • Map goal to SPARC phases
  • Generate GOAP milestones for each phase
  • Estimate effort and dependencies
  • Execute SPARC commands for each phase
  • Track metrics throughout execution
  • Validate goal achievement with success criteria
  • Document patterns for future goals

Best Practices

  • Measurable Goals: Every goal needs quantifiable success criteria
  • Phase Alignment: Map GOAP actions to appropriate SPARC phases
  • TDD Integration: Use refinement phase for test-first development
  • Incremental Progress: Track metrics at each milestone
  • Risk Assessment: Evaluate technical, timeline, quality, security risks
  • Pattern Learning: Store successful plans for reuse

Error Handling

Goal Infeasibility

// Goal cannot be achieved with available resources
if (!canAchieveGoal(currentState, goalState, constraints)) {
  // Suggest achievable subset
  const achievableGoal = findMaximalAchievableSubset(goalState);
  console.log(`Full goal not achievable. Suggested: ${achievableGoal}`);

  // Identify blocking constraints
  const blockers = identifyBlockers(goalState);
  console.log(`Blocked by: ${blockers}`);
}

Phase Failures

// SPARC phase did not complete successfully
if (phaseResult.failed) {
  // Identify specific failures
  const failures = phaseResult.failedCriteria;

  // Attempt retry with adjusted parameters
  if (canRetry(failures)) {
    await retryPhase(phase, adjustedConfig);
  } else {
    // Replan from current state
    await replanFromPhase(phase);
  }
}

Metrics & Success Criteria

Code Quality Metrics

MetricTargetMeasurement
Cyclomatic Complexity< 10Per function
Code Duplication< 3%Codebase-wide
Test Coverage> 80%Line coverage
Technical Debt Ratio< 5%SonarQube

Performance Metrics

MetricTargetMeasurement
Response Time (p99)< 200msAPM
Throughput> 1000 req/sLoad test
Error Rate< 0.1%Monitoring
Availability> 99.9%Uptime

Delivery Metrics

MetricTargetMeasurement
Lead Time< 1 dayDeploy tracking
Deploy Frequency> 1/dayCI/CD
MTTR< 1 hourIncident tracking
Change Failure Rate< 5%Rollback rate

Integration Points

MCP Tools

// Initialize SPARC-enhanced swarm
  topology: "hierarchical",
  maxAgents: 5
});

// Spawn SPARC-specific agents
  type: "sparc-coder",
  capabilities: ["specification", "pseudocode", "architecture", "refinement", "completion"]
});

// Orchestrate development tasks
  task: "implement_oauth_system",
  strategy: "adaptive",
  priority: "high"
});

// Store successful patterns
  action: "store",
  namespace: "code-patterns",
  key: "oauth_implementation_plan",
  value: JSON.stringify(successfulPlan)
});

SPARC Commands

# Full SPARC-GOAP workflow

# Batch processing

Related Skills

References

Version History

  • 1.0.0 (2026-01-02): Initial release - converted from code-goal-planner agent

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

31%
按下载量换算51

OpenCode

23.79%
按下载量换算39

Gemini CLI

17.59%
按下载量换算29

windsurf

11.64%
按下载量换算19

trae

8.46%
按下载量换算14

Cursor

3.49%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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