Agent skill

Issue Discover

by catlog22 in catlog22/Claude-Code-Workflow

Unified issue discovery and creation. An agent skill from catlog22/Claude-Code-Workflow.

MITAuto-check: notes

Install Issue Discover

skills CLI
$ npx skills add catlog22/Claude-Code-Workflow --skill issue-discover -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install catlog22/Claude-Code-Workflow issue-discover --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/catlog22/Claude-Code-Workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/issue-discover .claude/skills/issue-discover && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
issue-discover
GitHub stars
2.1k
Token cost
~3.3k tokens
SKILL.md length
509 words
Files
5
Skills in repo
82
Repo updated
First seen
Licence
MIT

At a glance

Unified issue discovery and creation. An agent skill from catlog22/Claude-Code-Workflow.

  • Works in 6 steps: Action-Driven Routing:… → Progressive Phase Loading: Only read the… → CLI-First Data Access: All issue CRUD… → …
  • Issue:discover-by-prompt
  • SKILL.md covers Architecture Overview, Key Design Principles, Auto Mode and Usage, plus 9 more sections
  • Reaches github.com

What it does

Issue Discover is an agent skill from catlog22/Claude-Code-Workflow. 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".

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `phases/01-issue-new.md`, `phases/02-discover.md` and `phases/03-discover-by-prompt.md`).

It works with GitHub. The repository describes itself as: JSON-driven multi-agent cadence-team development framework with intelligent CLI orchestration (Gemini/Qwen/Codex), context-first architecture, and automated workflow execution. The licence is MIT.

When your agent uses it

  • Issue:discover-by-prompt
  • Discover issues

Example prompts

  • “issue:new”
  • “issue:discover”
  • “issue:discover-by-prompt”
  • “/issue-discover”

Requirements

  • Pre-approved tools (allowed-tools): spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, Edit, Bash, Glob, Grep, mcp__ace-tool__search_context, mcp__exa__search

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit 07491b0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • spawn_agent
    • wait_agent
    • send_message
    • followup_task
    • close_agent
    • request_user_input
    • Read
    • Write
    • Edit
    • Bash

    …and 4 more on the same allowed-tools line.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are javascript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Issue Discover loads about 3.3k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 509 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, 

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from catlog22/Claude-Code-Workflow at commit 07491b0, republished under its MIT licence (© catlog22). 509 words, ~3,322 tokens.

Download SKILL.mdSave it as .claude/skills/issue-discover/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
issue-discover
description
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".
allowed-tools
spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, Edit, Bash, Glob, Grep, mcp__ace-tool__search_context, mcp__exa__search

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
javascript
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)
javascript
// 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.

javascript
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).

javascript
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;
}
Show full SKILL.md (199 more words)Show less
followup_task

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

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

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

Clean up subagent resources (irreversible).

javascript
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 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

Progress: functions.update_plan([{id: "phase-exec", status: "completed"}, {id: "post-phase", status: "in_progress"}])

After successful phase execution, recommend next action:

javascript
// After Create New (issue created)
functions.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)
functions.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

// Mark workflow complete
functions.update_plan([{ id: "post-phase", status: "completed" }])
  • 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

© catlog22, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in .codex/skills/issue-discover of catlog22/Claude-Code-Workflow.

  • SKILL.md
  • phases/01-issue-new.md
  • phases/02-discover.md
  • phases/03-discover-by-prompt.md
  • phases/04-quick-execute.md

Open the folder on GitHubat commit 07491b0

Compare with similar skills

Issue Discover next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Issue Discover compared with similar skills
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Issue Discover this skillcatlog22/Claude-Code-Workflow2.1k—~3.3kAutomated safety check: NotesMIT
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Diagnosing Superpowers Sessionsobra/superpowers296k3 repos~1.7kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow83k5 repos~1.3kAutomated safety check: PassMIT
Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT
Update V8 Versionopeninterpreter/openinterpreter69k2 repos~845Automated safety check: PassApache-2.0

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Works with

Questions about Issue Discover

What does Issue Discover do?

Unified issue discovery and creation. An agent skill from catlog22/Claude-Code-Workflow. Issue Discover is an agent skill from catlog22/Claude-Code-Workflow. Unified issue discovery and creation.

When should I use Issue Discover?

Issue Discover fits situations like: issue:discover-by-prompt; discover issues.

How do I install Issue Discover in Claude Code?

Run `npx skills add catlog22/Claude-Code-Workflow --skill issue-discover -a claude-code`. Or copy the skill folder (.codex/skills/issue-discover in catlog22/Claude-Code-Workflow) into .claude/skills/issue-discover in your project. Claude Code loads it when a task matches its description.

How do I install Issue Discover in Codex?

Run `npx skills add catlog22/Claude-Code-Workflow --skill issue-discover -a codex`. Or copy the skill folder (.codex/skills/issue-discover in catlog22/Claude-Code-Workflow) into .agents/skills/issue-discover in your project. Codex loads it when a task matches its description.

Can I use Issue Discover in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add catlog22/Claude-Code-Workflow --skill issue-discover -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/issue-discover, .gemini/skills/issue-discover, .github/skills/issue-discover and .opencode/skills/issue-discover in your project.

What does Issue Discover need to run?

SKILL.md names no scripts, command-line tools or credentials: Issue Discover is instructions for the agent only. Its frontmatter pre-approves these tools: spawn_agent, wait_agent, send_message, followup_task, close_agent, request_user_input, Read, Write, Edit, Bash, Glob, Grep, mcp__ace-tool__search_context, mcp__exa__search.

Does Issue Discover access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Issue Discover safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Issue Discover use?

Issue Discover is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Issue Discover use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Issue Discover?

Skills that share tags, products or a category with Issue Discover: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 296k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars) and Greploop (onyx-dot-app/onyx, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Issue Discover?

catlog22 (a GitHub user) maintains it in catlog22/Claude-Code-Workflow, which has 2,130 GitHub stars. The repository holds 82 skills in this directory. The repository was last updated on June 18, 2026.

Source: catlog22/Claude-Code-Workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.