agent-issue-tracker
Skill1 starsChanged 7 months agoMITView on GitHub
Agent skill for issue-tracker - invoke with $agent-issue-tracker
5 other projects use a version of this, 5 of them edited.
Adopted by
Most recently taken up by
- ruvnet/rufloedited, first seen Oct 21, 2026
- ruvnet/claude-flowedited, first seen Oct 8, 2026
- Soulcynics404/AgentForgeedited, first seen Aug 24, 2026
- jpoindexter/theft-kitedited, first seen May 20, 2026
- Zekiog/rufloedited, first seen Apr 8, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 5
- ruvnet/claude-flow★ 80k91% same
- ruvnet/ruflo★ 79k93% same
- Zekiog/ruflo★ 293% same
- jpoindexter/theft-kit★ 193% same
- Soulcynics404/AgentForge★ 193% same
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository175 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .claude/commands/monitoring/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- v2/CLAUDE.mdCLAUDE.md
- v3/CLAUDE.mdCLAUDE.md
- agent-adaptive-coordinatorSkill
- agent-agentic-paymentsSkill
- agent-agentSkill
- agent-analyze-code-qualitySkill
- agent-app-storeSkill
- agent-architectureSkill
- agent-arch-system-designSkill
- agent-authenticationSkill
- agent-automation-smart-agentSkill
- agent-base-template-generatorSkill
- agent-benchmark-suiteSkill
- agent-byzantine-coordinatorSkill
- agent-challengesSkill
- agent-code-analyzerSkill
- agent-code-goal-plannerSkill
- agent-code-review-swarmSkill
- agent-coderSkill
- agent-collective-intelligence-coordinatorSkill
- agent-consensus-coordinatorSkill
- agent-coordinationSkill
- agent-coordinator-swarm-initSkill
- agent-crdt-synchronizerSkill
- agent-data-ml-modelSkill
- AgentDB Advanced FeaturesSkill
- AgentDB Learning PluginsSkill
- AgentDB Memory PatternsSkill
- AgentDB Performance OptimizationSkill
- AgentDB Vector SearchSkill
- agent-dev-backend-apiSkill
- agent-docs-api-openapiSkill
- agent-github-modesSkill
- agent-github-pr-managerSkill
- agent-goal-plannerSkill
- agent-gossip-coordinatorSkill
- agent-hierarchical-coordinatorSkill
- agentic-jujutsuSkill
- agent-implementer-sparc-coderSkill
- agent-load-balancerSkill
- agent-matrix-optimizerSkill
- agent-memory-coordinatorSkill
- agent-mesh-coordinatorSkill
- agent-migration-planSkill
- agent-multi-repo-swarmSkill
- agent-neural-networkSkill
- agent-ops-cicd-githubSkill
- agent-orchestrator-taskSkill
- agent-pagerank-analyzerSkill
- agent-paymentsSkill
- agent-performance-analyzerSkill
- agent-performance-benchmarkerSkill
- agent-performance-monitorSkill
- agent-performance-optimizerSkill
- agent-plannerSkill
- agent-pr-managerSkill
- agent-production-validatorSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
3 rules. 3 are common, 0 are distinctive, and 0 are very specific to this project.
3
Common
Most of the 5 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Common: line 285
Always initialize swarm for complex issues
- Common: line 287
Use memory for progress coordination
- Common: line 300
Create multiple related issues simultaneously
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
name: issue-tracker description: Intelligent issue management and project coordination with automated tracking, progress monitoring, and team coordination tools: mcp__fidgetflo__swarm_init, mcp__fidgetflo__agent_spawn, mcp__fidgetflo__task_orchestrate, mcp__fidgetflo__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__fidgetflo__*(all swarm coordination tools)TodoWrite,TodoRead,Task,Bash,Read,Write
Usage Patterns
1. Create Coordinated Issue with Swarm Tracking
// Initialize issue management swarm
mcp__fidgetflo__swarm_init { topology: "star", maxAgents: 3 }
mcp__fidgetflo__agent_spawn { type: "coordinator", name: "Issue Coordinator" }
mcp__fidgetflo__agent_spawn { type: "researcher", name: "Requirements Analyst" }
mcp__fidgetflo__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__fidgetflo__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__fidgetflo__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__fidgetflo__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__fidgetflo__swarm_init { topology: "mesh", maxAgents: 4 }
mcp__fidgetflo__agent_spawn { type: "coordinator", name: "Issue Manager" }
mcp__fidgetflo__agent_spawn { type: "analyst", name: "Progress Tracker" }
mcp__fidgetflo__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$claude-code-flow-ruv-swarm..." \
--label "bug,integration,urgent"`)
Bash(`gh issue create \
--repo :owner/:repo \
--title "Documentation: Update integration guides" \
--body "Update all documentation to reflect new GitHub workflows..." \
--label "documentation,integration"`)
// Set up coordinated tracking
TodoWrite { todos: [
{ id: "github-feature", content: "Implement GitHub integration", status: "pending", priority: "high" },
{ id: "merge-conflicts", content: "Resolve PR conflicts", status: "pending", priority: "critical" },
{ id: "docs-update", content: "Update documentation", status: "pending", priority: "medium" }
]}
// Store initial coordination state
mcp__fidgetflo__memory_usage {
action: "store",
key: "project$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 CodeBug 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 CodeBest 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
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