IS

issue-discover

A central tool to discover, analyze, and create software issues using GitHub data and custom prompts.

Install

mkdir -p .claude/skills/issue-discover && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6849" && unzip -o skill.zip -d .claude/skills/issue-discover && rm skill.zip

Installs to .claude/skills/issue-discover

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Unified issue discovery and creation. Create issues from GitHub/text, discover issues via multi-perspective analysis, or prompt-driven iterative exploration. Triggers on \"issue:new\", \"issue:discover\", \"issue:discover-by-prompt\", \"create issue\", \"discover issues\", \"find issues\".
290 charsno explicit “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Intermediate

Key capabilities

  • Create GitHub issues from text or URLs
  • Perform multi-perspective issue discovery
  • Execute prompt-driven iterative exploration
  • Manage subagent lifecycle for issue tasks
  • Route actions based on input auto-detection

How it works

The orchestrator parses input to select a phase, then uses request_user_input or auto-detection to route to specific phase documents. It manages subagents to perform CRUD operations via the ccw issue CLI.

Inputs & outputs

You give it
GitHub URL, path pattern, or descriptive text
You get back
Registered GitHub issue or structured discovery findings

When to use issue-discover

  • Create new GitHub issues from text descriptions
  • Discover hidden project issues through analysis
  • Iterative exploration of technical debt
  • Generate structured issue reports from conversation

About this skill

Issue Discover

Unified issue discovery and creation skill covering three entry points: manual issue creation, perspective-based discovery, and prompt-driven exploration.

Architecture Overview

┌─────────────────────────────────────────────────────────────────┐
│  Issue Discover Orchestrator (SKILL.md)                          │
│  → Action selection → Route to phase → Execute → Summary         │
└───────────────┬─────────────────────────────────────────────────┘
                │
                ├─ request_user_input: Select action
                │
    ┌───────────┼───────────┬───────────┐
    ↓           ↓           ↓           │
┌─────────┐ ┌─────────┐ ┌─────────┐   │
│ Phase 1 │ │ Phase 2 │ │ Phase 3 │   │
│  Create │ │Discover │ │Discover │   │
│   New   │ │  Multi  │ │by Prompt│   │
└─────────┘ └─────────┘ └─────────┘   │
     ↓           ↓           ↓          │
  Issue      Discoveries  Discoveries   │
(registered)  (export)    (export)      │
     │           │           │          │
     │           ├───────────┤          │
     │           ↓                      │
     │     ┌───────────┐               │
     │     │  Phase 4  │               │
     │     │Quick Plan │               │
     │     │& Execute  │               │
     │     └─────┬─────┘               │
     │           ↓                      │
     │     .task/*.json                 │
     │           ↓                      │
     │     Direct Execution             │
     │           │                      │
     └───────────┴──────────────────────┘
                  ↓ (fallback/remaining)
          issue-resolve (plan/queue)
                  ↓
            /issue:execute

Key Design Principles

  1. Action-Driven Routing: request_user_input selects action, then load single phase
  2. Progressive Phase Loading: Only read the selected phase document
  3. CLI-First Data Access: All issue CRUD via ccw issue CLI commands
  4. Auto Mode Support: -y flag skips action selection with auto-detection
  5. Subagent Lifecycle: Explicit lifecycle management with spawn_agent → wait_agent → close_agent
  6. Role Path Loading: Subagent roles loaded via path reference in MANDATORY FIRST STEPS

Auto Mode

When --yes or -y: Skip action selection, auto-detect action from input type.

Usage

issue-discover <input>
issue-discover [FLAGS] "<input>"

# Flags
-y, --yes              Skip all confirmations (auto mode)
--action <type>        Pre-select action: new|discover|discover-by-prompt

# Phase-specific flags
--priority <1-5>       Issue priority (new mode)
--perspectives <list>  Comma-separated perspectives (discover mode)
--external             Enable Exa research (discover mode)
--scope <pattern>      File scope (discover/discover-by-prompt mode)
--depth <level>        standard|deep (discover-by-prompt mode)
--max-iterations <n>   Max exploration iterations (discover-by-prompt mode)

# Examples
issue-discover https://github.com/org/repo/issues/42                              # Create from GitHub
issue-discover "Login fails with special chars"                                    # Create from text
issue-discover --action discover src/auth/**                                       # Multi-perspective discovery
issue-discover --action discover src/api/** --perspectives=security,bug            # Focused discovery
issue-discover --action discover-by-prompt "Check API contracts"                   # Prompt-driven discovery
issue-discover -y "auth broken"                                                    # Auto mode create

Execution Flow

Input Parsing:
   └─ Parse flags (--action, -y, --perspectives, etc.) and positional args

Action Selection:
   ├─ --action flag provided → Route directly
   ├─ Auto-detect from input:
   │   ├─ GitHub URL or #number → Create New (Phase 1)
   │   ├─ Path pattern (src/**, *.ts) → Discover (Phase 2)
   │   ├─ Short text (< 80 chars) → Create New (Phase 1)
   │   └─ Long descriptive text (≥ 80 chars) → Discover by Prompt (Phase 3)
   └─ Otherwise → request_user_input to select action
   └─ Initialize progress tracking: functions.update_plan([...phases])

Phase Execution (load one phase):
   ├─ Phase 1: Create New          → phases/01-issue-new.md
   ├─ Phase 2: Discover            → phases/02-discover.md
   └─ Phase 3: Discover by Prompt  → phases/03-discover-by-prompt.md

Post-Phase:
   └─ Summary + Next steps recommendation

Phase Reference Documents

PhaseDocumentLoad WhenPurpose
Phase 1phases/01-issue-new.mdAction = Create NewCreate issue from GitHub URL or text description
Phase 2phases/02-discover.mdAction = DiscoverMulti-perspective issue discovery (bug, security, test, etc.)
Phase 3phases/03-discover-by-prompt.mdAction = Discover by PromptPrompt-driven iterative exploration with Gemini planning
Phase 4phases/04-quick-execute.mdPost-Phase = Quick Plan & ExecuteConvert high-confidence findings to tasks and execute directly

Core Rules

  1. Action Selection First: Always determine action before loading any phase
  2. Single Phase Load: Only read the selected phase document, never load all phases
  3. CLI Data Access: Use ccw issue CLI for all issue operations, NEVER read files directly
  4. Content Preservation: Each phase contains complete execution logic from original commands
  5. Auto-Detect Input: Smart input parsing reduces need for explicit --action flag
  6. ⚠️ CRITICAL: DO NOT STOP: Continuous multi-phase workflow. After completing each phase, immediately proceed to next
  7. Progressive Phase Loading: Read phase docs ONLY when that phase is about to execute
  8. Explicit Lifecycle: Always close_agent after wait_agent completes to free resources

Input Processing

Auto-Detection Logic

function detectAction(input, flags) {
  // 1. Explicit --action flag
  if (flags.action) return flags.action;

  const trimmed = input.trim();

  // 2. GitHub URL → new
  if (trimmed.match(/github\.com\/[\w-]+\/[\w-]+\/issues\/\d+/) || trimmed.match(/^#\d+$/)) {
    return 'new';
  }

  // 3. Path pattern (contains **, /, or --perspectives) → discover
  if (trimmed.match(/\*\*/) || trimmed.match(/^src\//) || flags.perspectives) {
    return 'discover';
  }

  // 4. Short text (< 80 chars, no special patterns) → new
  if (trimmed.length > 0 && trimmed.length < 80 && !trimmed.includes('--')) {
    return 'new';
  }

  // 5. Long descriptive text → discover-by-prompt
  if (trimmed.length >= 80) {
    return 'discover-by-prompt';
  }

  // Cannot auto-detect → ask user
  return null;
}

Action Selection (request_user_input)

// When action cannot be auto-detected
const answer = functions.request_user_input({
  questions: [{
    header: "Action",
    id: "action",
    question: "What would you like to do?",
    options: [
      {
        label: "Create New Issue (Recommended)",
        description: "Create issue from GitHub URL, text description, or structured input"
      },
      {
        label: "Discover Issues",
        description: "Multi-perspective discovery: bug, security, test, quality, performance, etc."
      },
      {
        label: "Discover by Prompt",
        description: "Describe what to find — Gemini plans the exploration strategy iteratively"
      }
    ]
  }]
});  // BLOCKS (wait for user response)

// Route based on selection
// answer.answers.action.answers[0] → selected label
const actionMap = {
  "Create New Issue (Recommended)": "new",
  "Discover Issues": "discover",
  "Discover by Prompt": "discover-by-prompt"
};

// Initialize progress tracking (MANDATORY)
functions.update_plan([
  { id: "action-select", title: "Action Selection", status: "completed" },
  { id: "phase-exec", title: `Phase: ${selectedAction}`, status: "in_progress" },
  { id: "post-phase", title: "Post-Phase: Next Steps", status: "pending" }
])

Data Flow

User Input (URL / text / path pattern / descriptive prompt)
    ↓
[Parse Flags + Auto-Detect Action]
    ↓
[Action Selection] ← request_user_input (if needed)
    ↓
[Read Selected Phase Document]
    ↓
[Execute Phase Logic]
    ↓
[Summary + Next Steps]
    ├─ After Create → Suggest issue-resolve (plan solution)
    └─ After Discover → Suggest export to issues, then issue-resolve

Subagent API Reference

spawn_agent

Create a new subagent with task assignment.

const agentId = spawn_agent({
  agent_type: "{agent_type}",
  message: `
## TASK ASSIGNMENT

### MANDATORY FIRST STEPS (Agent Execute)
1. Execute: ccw spec load --category exploration
2. Execute: ccw spec load --category debug (known issues cross-reference)

## TASK CONTEXT
${taskContext}

## DELIVERABLES
${deliverables}
`
})

wait_agent

Get results from subagent (only way to retrieve results).

const result = wait_agent({
  timeout_ms: 1800000  // 30 minutes
})

if (result.timed_out) {
  // Handle timeout via 4-step cascade: status probe → force finalize → close
}

// Check completion status
if (result.status[agentId].completed) {
  const output = result.status[agentId].completed;
}

followup_task

Assign new work to active subagent (for clarification or follow-up).

followup_task({
  target: agentId,
  message: `
## CLARIFICATION ANSWERS
${answers}

## NEXT STEP
Continue with plan generation.
`
})

close_agent

Clean up subagent resources (irreversible).

close_agent({ target: agentId })

Core Guidelines

Data Access Principle: Issues files can grow very large. To avoid context overflow:

OperationCorrectIncorrect
List issues (brief)ccw issue list --status pending --briefRead('issues.jsonl')
Read issue details

Content truncated.

When not to use it

  • Tasks requiring direct file manipulation instead of CLI commands

Limitations

  • Requires ccw issue CLI for all data operations
  • Cannot read issues.jsonl directly due to context limits

How it compares

Unlike manual issue tracking, this skill automates the discovery and planning lifecycle using specific phase-based orchestration.

Compared to similar skills

issue-discover side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
issue-discover (this skill)13moNo flagsIntermediate
workflow03moNo flagsIntermediate
agent-swarm-issue16moReviewIntermediate
gsd-stats03moNo flagsBeginner

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