CtrlK
BlogDocsLog inGet started
Tessl Logo

issue-discover

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".

79

Quality

75%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./.codex/skills/issue-discover/SKILL.md
SKILL.md
Quality
Evals
Security

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

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 = 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"
};

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({
  targets: [agentId],
  timeout_ms: 600000  // 10 minutes
})

if (result.timed_out) {
  // Handle timeout - can use assign_task to prompt completion
}

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

assign_task

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

assign_task({
  target: agentId,
  items: [{ type: "text", text: `
## CLARIFICATION ANSWERS
${answers}

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

close_agent

Clean up subagent resources (irreversible).

close_agent({ id: 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 detailsccw issue status <id> --jsonRead('issues.jsonl')
Create issueecho '...' | ccw issue createDirect file write
Update statusccw issue update <id> --status ...Direct file edit

ALWAYS use CLI commands for CRUD operations. NEVER read entire issues.jsonl directly.

Error Handling

ErrorResolution
No action detectedShow request_user_input with all 3 options
Invalid action typeShow available actions, re-prompt
Phase execution failsReport error, suggest manual intervention
No files matched (discover)Check target pattern, verify path exists
Gemini planning failed (discover-by-prompt)Retry with qwen fallback
Agent lifecycle errorsEnsure close_agent in error paths to prevent resource leaks

Post-Phase Next Steps

After successful phase execution, recommend next action:

// After Create New (issue created)
request_user_input({
  questions: [{
    header: "Next Step",
    id: "next_after_create",
    question: "Issue created. What next?",
    options: [
      { label: "Plan Solution (Recommended)", description: "Generate solution via issue-resolve" },
      { label: "Create Another", description: "Create more issues" },
      { label: "Done", description: "Exit workflow" }
    ]
  }]
});  // BLOCKS (wait for user response)
// answer.answers.next_after_create.answers[0] → selected label

// After Discover / Discover by Prompt (discoveries generated)
request_user_input({
  questions: [{
    header: "Next Step",
    id: "next_after_discover",
    question: `Discovery complete: ${findings.length} findings, ${executableFindings.length} executable. What next?`,
    options: [
      { label: "Quick Plan & Execute (Recommended)", description: `Fix ${executableFindings.length} high-confidence findings directly` },
      { label: "Export to Issues", description: "Convert discoveries to issues" },
      { label: "Done", description: "Exit workflow" }
    ]
  }]
});  // BLOCKS (wait for user response)
// answer.answers.next_after_discover.answers[0] → selected label
// If "Quick Plan & Execute (Recommended)" → Read phases/04-quick-execute.md, execute

Related Skills & Commands

  • issue-resolve - Plan solutions, convert artifacts, form queues, from brainstorm
  • issue-manage - Interactive issue CRUD operations
  • /issue:execute - Execute queue with DAG-based parallel orchestration
  • ccw issue list - List all issues
  • ccw issue status <id> - View issue details
Repository
catlog22/Claude-Code-Workflow
Last updated
Created

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.