# github-project-management

> /*============================================================================*/ /* SKILL SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/

- Author: DNYoussef
- Repository: DNYoussef/ruv-sparc-three-loop-system
- Version: 20260113122214
- Stars: 0
- Forks: 0
- Last Updated: 2026-02-08
- Source: https://github.com/DNYoussef/ruv-sparc-three-loop-system
- Web: https://mule.run/skillshub/@@DNYoussef/ruv-sparc-three-loop-system~github-project-management:20260113122214

---

/*============================================================================*/
/* SKILL SKILL :: VERILINGUA x VERIX EDITION                      */
/*============================================================================*/

---
name: SKILL
version: 1.0.0
description: |
  [assert|neutral] SKILL skill for operations workflows [ground:given] [conf:0.95] [state:confirmed]
category: operations
tags:
- general
author: system
cognitive_frame:
  primary: aspectual
  goal_analysis:
    first_order: "Execute SKILL workflow"
    second_order: "Ensure quality and consistency"
    third_order: "Enable systematic operations processes"
---

/*----------------------------------------------------------------------------*/
/* S0 META-IDENTITY                                                            */
/*----------------------------------------------------------------------------*/

[define|neutral] SKILL := {
  name: "SKILL",
  category: "operations",
  version: "1.0.0",
  layer: L1
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S1 COGNITIVE FRAME                                                          */
/*----------------------------------------------------------------------------*/

[define|neutral] COGNITIVE_FRAME := {
  frame: "Aspectual",
  source: "Russian",
  force: "Complete or ongoing?"
} [ground:cognitive-science] [conf:0.92] [state:confirmed]

## Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.

/*----------------------------------------------------------------------------*/
/* S2 TRIGGER CONDITIONS                                                       */
/*----------------------------------------------------------------------------*/

[define|neutral] TRIGGER_POSITIVE := {
  keywords: ["SKILL", "operations", "workflow"],
  context: "user needs SKILL capability"
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S3 CORE CONTENT                                                             */
/*----------------------------------------------------------------------------*/

# GitHub Project Management

## Kanitsal Cerceve (Evidential Frame Activation)
Kaynak dogrulama modu etkin.



## Overview

A comprehensive skill for managing GitHub projects using AI swarm coordination. This skill combines intelligent issue management, automated project board synchronization, and swarm-based coordination for efficient project delivery.

## Quick Start

### Basic Issue Creation with Swarm Coordination

```bash
# Create a coordinated issue
gh issue create \
  --title "Feature: Advanced Authentication" \
  --body "Implement OAuth2 with social login..." \
  --label "enhancement,swarm-ready"

# Initialize swarm for issue
npx claude-flow@alpha hooks pre-task --description "Feature implementation"
```

### Project Board Quick Setup

```bash
# Get project ID
PROJECT_ID=$(gh project list --owner @me --format json | \
  jq -r '.projects[0].id')

# Initialize board sync
npx ruv-swarm github board-init \
  --project-id "$PROJECT_ID" \
  --sync-mode "bidirectional"
```

---

## Core Capabilities

### 1. Issue Management & Triage

<details>
<summary><strong>Automated Issue Creation</strong></summary>

#### Single Issue with Swarm Coordination

```javascript
// 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: "org",
  repo: "repository",
  title: "Integration Review: Complete system integration",
  body: `## 🔄 Integration Review

  ### Overview
  Comprehensive review and integration between components.

  ### Objectives
  - [ ] Verify dependencies and imports
  - [ ] Ensure API integration
  - [ ] Check hook system integration
  - [ ] Validate data systems alignment

  ### Swarm Coordination
  This issue will be managed by coordinated swarm agents for optimal progress tracking.`,
  labels: ["integration", "review", "enhancement"],
  assignees: ["username"]
}

// Set up automated tracking
mcp__claude-flow__task_orchestrate {
  task: "Monitor and coordinate issue progress with automated updates",
  strategy: "adaptive",
  priority: "medium"
}
```

#### Batch Issue Creation

```bash
# Create multiple related issues using gh CLI
gh issue create \
  --title "Feature: Advanced GitHub Integration" \
  --body "Implement comprehensive GitHub workflow automation..." \
  --label "feature,github,high-priority"

gh issue create \
  --title "Bug: Merge conflicts in integration branch" \
  --body "Resolve merge conflicts..." \
  --label "bug,integration,urgent"

gh issue create \
  --title "Documentation: Update integration guides" \
  --body "Update all documentation..." \
  --label "documentation,integration"
```

</details>

<details>
<summary><strong>Issue-to-Swarm Conversion</strong></summary>

#### Transform Issues into Swarm Tasks

```bash
# Get issue details
ISSUE_DATA=$(gh issue view 456 --json title,body,labels,assignees,comments)

# Create swarm from issue
npx ruv-swarm github issue-to-swarm 456 \
  --issue-data "$ISSUE_DATA" \
  --auto-decompose \
  --assign-agents

# Batch process multiple issues
ISSUES=$(gh issue list --label "swarm-ready" --json number,title,body,labels)
npx ruv-swarm github issues-batch \
  --issues "$ISSUES" \
  --parallel

# Update issues with swarm status
echo "$ISSUES" | jq -r '.[].number' | while read -r num; do
  gh issue edit $num --add-label "swarm-processing"
done
```

#### Issue Comment Commands

Execute swarm operations via issue comments:

```markdown
<!-- In issue comment -->
/swarm analyze
/swarm decompose 5
/swarm assign @agent-coder
/swarm estimate
/swarm start
```

</details>

<details>
<summary><strong>Automated Issue Triage</strong></summary>

#### Auto-Label Based on Content

```javascript
// .github/swarm-labels.json
{
  "rules": [

/*----------------------------------------------------------------------------*/
/* S4 SUCCESS CRITERIA                                                         */
/*----------------------------------------------------------------------------*/

[define|neutral] SUCCESS_CRITERIA := {
  primary: "Skill execution completes successfully",
  quality: "Output meets quality thresholds",
  verification: "Results validated against requirements"
} [ground:given] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S5 MCP INTEGRATION                                                          */
/*----------------------------------------------------------------------------*/

[define|neutral] MCP_INTEGRATION := {
  memory_mcp: "Store execution results and patterns",
  tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"]
} [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S6 MEMORY NAMESPACE                                                         */
/*----------------------------------------------------------------------------*/

[define|neutral] MEMORY_NAMESPACE := {
  pattern: "skills/operations/SKILL/{project}/{timestamp}",
  store: ["executions", "decisions", "patterns"],
  retrieve: ["similar_tasks", "proven_patterns"]
} [ground:system-policy] [conf:1.0] [state:confirmed]

[define|neutral] MEMORY_TAGGING := {
  WHO: "SKILL-{session_id}",
  WHEN: "ISO8601_timestamp",
  PROJECT: "{project_name}",
  WHY: "skill-execution"
} [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S7 SKILL COMPLETION VERIFICATION                                            */
/*----------------------------------------------------------------------------*/

[direct|emphatic] COMPLETION_CHECKLIST := {
  agent_spawning: "Spawn agents via Task()",
  registry_validation: "Use registry agents only",
  todowrite_called: "Track progress with TodoWrite",
  work_delegation: "Delegate to specialized agents"
} [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* S8 ABSOLUTE RULES                                                           */
/*----------------------------------------------------------------------------*/

[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]

/*----------------------------------------------------------------------------*/
/* PROMISE                                                                     */
/*----------------------------------------------------------------------------*/

[commit|confident] <promise>SKILL_VERILINGUA_VERIX_COMPLIANT</promise> [ground:self-validation] [conf:0.99] [state:confirmed]