agent-issue-tracker
- Repo stars 54,444
- Author updated Live
- Author repo ruflo
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @ruvnet · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- macOS · Linux · Windows
- Runtime requirements
- Node.js
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 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
runtime: Node.js
---
# agent-issue-tracker output preview
## PART A: Task fit
- Use case: Agent skill for issue-tracker - invoke with $agent-issue-tracker name: issue-tracker description: Intelligent issue management and project coordination with automated tracking, progress monitoring, and team coordination tools: mcpclaude-flowswarminit, mcpclaude-flowagentspawn, mcpclaude-flowtaskorchestrate, mcpclaude-flowmemoryusage, Bash, TodoWrite, Read….
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Purpose / Capabilities / Tools Available” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Agent skill for issue-tracker - invoke with $agent-issue-tracker name: issue-tracker description: Intelligent issue management and project coordination with automated tracking, progress monitoring, and team coordination tools: mcpclaude-flowswarminit, mcpclaude-flowagentspawn, mcpclaude-flowtaskorchestrate, mcpclaude-flowmemoryusage, Bash, TodoWrite, Read…”.
- **02** When the source has headings, the agent prioritizes “Purpose / Capabilities / Tools Available” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Start with a small task and check whether the result follows “Purpose / Capabilities / Tools Available”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: agent-issue-tracker
description: Agent skill for issue-tracker - invoke with $agent-issue-tracker name: issue-tracker description…
category: ai
source: ruvnet/ruflo
---
# agent-issue-tracker
## When to use
- Agent skill for issue-tracker - invoke with $agent-issue-tracker name: issue-tracker description: Intelligent issue ma…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Purpose / Capabilities / Tools Available” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "agent-issue-tracker" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Purpose / Capabilities / Tools Available
rules -> SKILL.md triggers / order / output contract
runtime -> Node.js | read files, write/modify files, run shell commands | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} 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
Decide Fit First
Design Intent
How To Use It
Boundaries And Review