/ideate-new

allowed-tools: Task, Read, Bash(fd:*), Bash(rg:*), Bash(wc:*), Bash(jq:*), Bash(gdate:*), Bash(eza:*)
name: "Ideate New"
description: "Discover and propose new Claude command opportunities through systematic analysis and parallel research"
author: "wcygan"
tags: ["meta","ideate"]
version: "1.0.0"
created_at: "2025-07-14T00:00:00Z"
updated_at: "2025-07-14T00:00:00Z"

Context

• Session ID: !`gdate +%s%N 2>/dev/null || date +%s%N 2>/dev/null || echo "$(date +%s)000000"`
• Current time: !`gdate -Iseconds 2>/dev/null || date -Iseconds`
• Target focus area: $ARGUMENTS
• Existing commands count: !`fd "\.md$" claude/commands | wc -l | tr -d ' ' || echo "unknown"`
• Command categories: !`fd -t d . claude/commands -d 1 | eza --oneline 2>/dev/null | tr '\n' ', ' | sed 's/,$//' || echo "analysis, code, context, docs, git, meta, ops, scaffold, security, task, test, tool, workflow"`
• Recent command additions: !`fd "\.md$" claude/commands -x stat -f "%m %N" | sort -nr | head -3 | cut -d' ' -f2- | sed 's|^claude/commands/||' | sed 's|\.md$||' || echo "none detected"`
• Technology trend indicators: !`rg -i "(ai|ml|llm|kubernetes|docker|rust|go|deno|fresh)" claude/commands --count-matches | head -5 || echo "trend analysis needed"`

Your Task

STEP 1: Initialize command opportunity analysis session

• CREATE session state file: `/tmp/ideate-session-$SESSION_ID.json`
• DETERMINE analysis scope based on focus area from Context
• INITIALIZE tracking structures for command gaps and opportunities

STEP 2: Parallel ecosystem analysis using sub-agent delegation

TRY:

LAUNCH 6 parallel sub-agents for comprehensive command ecosystem analysis:

• **Agent 1: Command Inventory & Categorization**: Analyze existing command structure
• Count and categorize all commands in `claude/commands/` directory
• Map commands by workflow stage (planning, development, testing, deployment, ops)
• Identify command density patterns and coverage gaps
• Extract naming conventions and complexity patterns

• **Agent 2: Developer Workflow Pain Points**: Research current pain points
• Research common developer complaints and friction points
• Identify repeated manual tasks lacking automation
• Analyze complex workflows needing systematic approaches
• Survey Stack Overflow trends and GitHub issue patterns

• **Agent 3: Technology Trend Analysis**: Track emerging technology adoption
• Survey latest framework migrations (React → Next, etc.)
• Research cloud-native development complexity growth
• Identify AI/ML integration workflow gaps
• Track mobile development automation opportunities

• **Agent 4: Command Pattern Analysis**: Deep-dive existing successful patterns
• Analyze naming conventions (action-based, hyphenated, prefixed)
• Review command complexity and argument patterns
• Identify successful command structures for replication
• Map command interdependencies and workflow chains

• **Agent 5: Industry Standards Research**: Analyze competitive landscape
• Research CLI tools and command patterns in similar products
• Identify industry best practices for developer tooling
• Analyze enterprise workflow automation gaps
• Survey developer productivity enhancement opportunities

• **Agent 6: Focus Area Deep Dive**: Specialized analysis based on $ARGUMENTS
• IF focus-area specified: Deep analysis of ai-ml, frontend, cloud, mobile, database, security, or emerging
• IF no focus specified: Cross-cutting analysis of all categories
• Identify specialized command opportunities within focus domain
• Research domain-specific pain points and automation gaps

CATCH (analysis_failed):

• LOG error details to session state
• CONTINUE with available analysis results
• PROVIDE recommendations based on partial data

STEP 3: Synthesize findings and identify high-impact opportunities

FOR EACH sub-agent result:

• AGGREGATE findings into session state
• IDENTIFY overlapping pain points (indicates high-impact opportunities)
• CLASSIFY opportunities by impact level and implementation complexity
• CROSS-REFERENCE with existing command ecosystem to avoid duplication

**Opportunity Classification Framework:**

{
  "tier1_immediate": {
    "criteria": "Addresses widespread pain points, clear ROI, fits ecosystem",
    "examples": []
  },
  "tier2_strategic": {
    "criteria": "Emerging tech support, enterprise gaps, command synergy",
    "examples": []
  },
  "tier3_future": {
    "criteria": "Experimental tech, foundation building, niche value",
    "examples": []
  }
}

STEP 4: Generate command proposals with contextual intelligence

FOR EACH identified opportunity:

• DESIGN command following established patterns:
• **Name**: Action-based, hyphenated, namespace-aware
• **Usage**: `/command [optional-context]` format
• **Auto-detection**: Project structure awareness (package.json, Cargo.toml, etc.)
• **Smart defaults**: Work without arguments, progressive enhancement
• **Graceful fallback**: Interactive guidance when context unclear

• CREATE comprehensive proposal including:
• **Gap Description**: What current need is unmet
• **Value Proposition**: How it improves developer workflow
• **Context Awareness**: Detection and adaptation capabilities
• **Implementation Complexity**: Effort estimation
• **Tier Classification**: Priority level and timeline

ANALYZE findings using strategic prioritization framework:

**Tier 1 (Immediate Implementation)**

• Sort opportunities by impact × feasibility score
• Prioritize pain points affecting >50% of developers
• SELECT 3-5 highest-value command proposals

**Tier 2 (Strategic Development)**

• Identify emerging technology support needs
• Focus on enterprise workflow automation gaps
• GROUP related commands for coordinated development

**Tier 3 (Future Research)**

• Catalog experimental/niche opportunities
• BUILD foundation for next-generation capabilities
• DOCUMENT for future iteration cycles

STEP 6: Generate comprehensive outp