Agent助手
- 作者仓库星标 54,444
- 作者更新于 实时读取
- 作者仓库 ruflo
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @ruvnet · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- macOS · Linux · Windows
- 底层运行要求
- Node.js
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agent-issue-tracker
description: Agent skill for issue-tracker - invoke with $agent-issue-tracker name: issue-tracker description…
category: AI 智能
runtime: Node.js
---
# agent-issue-tracker 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Purpose / Capabilities / Tools Available”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Purpose / Capabilities / Tools Available”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令。
先用一个小任务确认它会围绕“Purpose / Capabilities / Tools Available”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: agent-issue-tracker
description: Agent skill for issue-tracker - invoke with $agent-issue-tracker name: issue-tracker description…
category: AI 智能
source: ruvnet/ruflo
---
# agent-issue-tracker
## 什么时候使用
- 把 AI / Agent方向的常用动作沉淀成 Agent 可调用的技能 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Purpose / Capabilities / Tools Available」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "agent-issue-tracker" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Purpose / Capabilities / Tools Available
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Node.js | 读取文件、写入/修改文件、执行终端命令 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} name: issue-tracker description: Intelligent issue management and project coordination with automated tracking, progress monitoring, and team coordination tools: mcp__claude-flow__swarm_init, mcp__claude-flow__agent_spawn, mcp__claude-flow__task_orchestrate, mcp__claude-flow__memory_usage, Bash, TodoWrite, Read, Write color: green type: development capabilities:
- Automated issue creation with smart templates
- Progress tracking with swarm coordination
- Multi-agent collaboration on complex issues
- Project milestone coordination
- Cross-repository issue synchronization
- Intelligent labeling and organization priority: medium hooks: pre: | echo "Starting issue-tracker..." echo "Initializing issue management swarm" gh auth status || (echo "GitHub CLI not authenticated" && exit 1) echo "Setting up issue coordination environment" post: | echo "Completed issue-tracker" echo "Issues created and coordinated" echo "Progress tracking initialized" echo "Swarm memory updated with issue state"
GitHub Issue Tracker
Purpose
Intelligent issue management and project coordination with ruv-swarm integration for automated tracking, progress monitoring, and team coordination.
Capabilities
- Automated issue creation with smart templates and labeling
- Progress tracking with swarm-coordinated updates
- Multi-agent collaboration on complex issues
- Project milestone coordination with integrated workflows
- Cross-repository issue synchronization for monorepo management
Tools Available
mcp__github__create_issuemcp__github__list_issuesmcp__github__get_issuemcp__github__update_issuemcp__github__add_issue_commentmcp__github__search_issuesmcp__claude-flow__*(all swarm coordination tools)TodoWrite,TodoRead,Task,Bash,Read,Write
Usage Patterns
1. Create Coordinated Issue with Swarm Tracking
// Initialize issue management swarm
mcp__claude-flow__swarm_init { topology: "star", maxAgents: 3 }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "Issue Coordinator" }
mcp__claude-flow__agent_spawn { type: "researcher", name: "Requirements Analyst" }
mcp__claude-flow__agent_spawn { type: "coder", name: "Implementation Planner" }
// Create comprehensive issue
mcp__github__create_issue {
owner: "ruvnet",
repo: "ruv-FANN",
title: "Integration Review: claude-code-flow and ruv-swarm complete integration",
body: `## 🔄 Integration Review
### Overview
Comprehensive review and integration between packages.
### Objectives
- [ ] Verify dependencies and imports
- [ ] Ensure MCP tools integration
- [ ] Check hook system integration
- [ ] Validate memory systems alignment
### Swarm Coordination
This issue will be managed by coordinated swarm agents for optimal progress tracking.`,
labels: ["integration", "review", "enhancement"],
assignees: ["ruvnet"]
}
// Set up automated tracking
mcp__claude-flow__task_orchestrate {
task: "Monitor and coordinate issue progress with automated updates",
strategy: "adaptive",
priority: "medium"
}
2. Automated Progress Updates
// Update issue with progress from swarm memory
mcp__claude-flow__memory_usage {
action: "retrieve",
key: "issue/54$progress"
}
// Add coordinated progress comment
mcp__github__add_issue_comment {
owner: "ruvnet",
repo: "ruv-FANN",
issue_number: 54,
body: `## 🚀 Progress Update
### Completed Tasks
- ✅ Architecture review completed (agent-1751574161764)
- ✅ Dependency analysis finished (agent-1751574162044)
- ✅ Integration testing verified (agent-1751574162300)
### Current Status
- 🔄 Documentation review in progress
- 📊 Integration score: 89% (Excellent)
### Next Steps
- Final validation and merge preparation
---
🤖 Generated with Claude Code using ruv-swarm coordination`
}
// Store progress in swarm memory
mcp__claude-flow__memory_usage {
action: "store",
key: "issue/54$latest_update",
value: { timestamp: Date.now(), progress: "89%", status: "near_completion" }
}
3. Multi-Issue Project Coordination
// Search and coordinate related issues
mcp__github__search_issues {
q: "repo:ruvnet$ruv-FANN label:integration state:open",
sort: "created",
order: "desc"
}
// Create coordinated issue updates
mcp__github__update_issue {
owner: "ruvnet",
repo: "ruv-FANN",
issue_number: 54,
state: "open",
labels: ["integration", "review", "enhancement", "in-progress"],
milestone: 1
}
Batch Operations Example
Complete Issue Management Workflow:
[Single Message - Issue Lifecycle Management]:
// Initialize issue coordination swarm
mcp__claude-flow__swarm_init { topology: "mesh", maxAgents: 4 }
mcp__claude-flow__agent_spawn { type: "coordinator", name: "Issue Manager" }
mcp__claude-flow__agent_spawn { type: "analyst", name: "Progress Tracker" }
mcp__claude-flow__agent_spawn { type: "researcher", name: "Context Gatherer" }
// Create multiple related issues using gh CLI
Bash(`gh issue create \
--repo :owner/:repo \
--title "Feature: Advanced GitHub Integration" \
--body "Implement comprehensive GitHub workflow automation..." \
--label "feature,github,high-priority"`)
Bash(`gh issue create \
--repo :owner/:repo \
--title "Bug: PR merge conflicts in integration branch" \
--body "Resolve merge conflicts in integration$claude-code-flow-ruv-swarm..." \
--label "bug,integration,urgent"`)
Bash(`gh issue create \
--repo :owner/:repo \
--title "Documentation: Update integration guides" \
--body "Update all documentation to reflect new GitHub workflows..." \
--label "documentation,integration"`)
// Set up coordinated tracking
TodoWrite { todos: [
{ id: "github-feature", content: "Implement GitHub integration", status: "pending", priority: "high" },
{ id: "merge-conflicts", content: "Resolve PR conflicts", status: "pending", priority: "critical" },
{ id: "docs-update", content: "Update documentation", status: "pending", priority: "medium" }
]}
// Store initial coordination state
mcp__claude-flow__memory_usage {
action: "store",
key: "project$github_integration$issues",
value: { created: Date.now(), total_issues: 3, status: "initialized" }
}
Smart Issue Templates
Integration Issue Template:
## 🔄 Integration Task
### Overview
[Brief description of integration requirements]
### Objectives
- [ ] Component A integration
- [ ] Component B validation
- [ ] Testing and verification
- [ ] Documentation updates
### Integration Areas
#### Dependencies
- [ ] Package.json updates
- [ ] Version compatibility
- [ ] Import statements
#### Functionality
- [ ] Core feature integration
- [ ] API compatibility
- [ ] Performance validation
#### Testing
- [ ] Unit tests
- [ ] Integration tests
- [ ] End-to-end validation
### Swarm Coordination
- **Coordinator**: Overall progress tracking
- **Analyst**: Technical validation
- **Tester**: Quality assurance
- **Documenter**: Documentation updates
### Progress Tracking
Updates will be posted automatically by swarm agents during implementation.
---
🤖 Generated with Claude Code
Bug Report Template:
## 🐛 Bug Report
### Problem Description
[Clear description of the issue]
### Expected Behavior
[What should happen]
### Actual Behavior
[What actually happens]
### Reproduction Steps
1. [Step 1]
2. [Step 2]
3. [Step 3]
### Environment
- Package: [package name and version]
- Node.js: [version]
- OS: [operating system]
### Investigation Plan
- [ ] Root cause analysis
- [ ] Fix implementation
- [ ] Testing and validation
- [ ] Regression testing
### Swarm Assignment
- **Debugger**: Issue investigation
- **Coder**: Fix implementation
- **Tester**: Validation and testing
---
🤖 Generated with Claude Code
Best Practices
1. Swarm-Coordinated Issue Management
- Always initialize swarm for complex issues
- Assign specialized agents based on issue type
- Use memory for progress coordination
2. Automated Progress Tracking
- Regular automated updates with swarm coordination
- Progress metrics and completion tracking
- Cross-issue dependency management
3. Smart Labeling and Organization
- Consistent labeling strategy across repositories
- Priority-based issue sorting and assignment
- Milestone integration for project coordination
4. Batch Issue Operations
- Create multiple related issues simultaneously
- Bulk updates for project-wide changes
- Coordinated cross-repository issue management
Integration with Other Modes
Seamless integration with:
$github pr-manager- Link issues to pull requests$github release-manager- Coordinate release issues$sparc orchestrator- Complex project coordination$sparc tester- Automated testing workflows
Metrics and Analytics
Automatic tracking of:
- Issue creation and resolution times
- Agent productivity metrics
- Project milestone progress
- Cross-repository coordination efficiency
Reporting features:
- Weekly progress summaries
- Agent performance analytics
- Project health metrics
- Integration success rates
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核