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mikejsmith1985

task-classification

@mikejsmith1985/task-classification
mikejsmith1985
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Updated 4/1/2026
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Classifies tasks by complexity pattern for smart routing. Auto-invoked for all implementation requests.

Installation

$npx agent-skills-cli install @mikejsmith1985/task-classification
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Details

Path.github/skills/task-classification/SKILL.md
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Scoped Name@mikejsmith1985/task-classification

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

npx agent-skills-cli list

Skill Instructions


name: task-classification description: Classifies tasks by complexity pattern for smart routing. Auto-invoked for all implementation requests.

Task Classification Guidelines

Fast Pattern Detection (No LLM Needed)

Classify tasks based on prompt keywords + file count for smart routing.

Pattern Definitions

1. Architecture (Complexity: 9-10)

Keywords: "design", "architecture", "system", "integrate", "plan"

Indicators:

  • Multiple new components needed
  • Cross-cutting changes across layers
  • Requires design phase before implementation
  • Affects multiple subsystems

Example: "Design smart routing system with DB + UI + backend"

File Count: Usually 8+ files


2. Multi-File Refactor (Complexity: 7-8)

Keywords: "refactor", "restructure", "reorganize", "rename across"

Indicators:

  • 5+ files mentioned with @ syntax
  • Moving logic between components
  • Changing interfaces/contracts
  • Preserving existing behavior

Example: "Refactor routing logic across CFO, SLM, and Task Dashboard"

File Count: 5-10 files


3. Feature Implementation (Complexity: 5-7)

Keywords: "add", "create", "implement", "build"

Indicators:

  • New functionality (not refactoring existing)
  • 2-5 files involved
  • Both backend and frontend changes
  • Requires tests

Example: "Add model recommendation panel to Task Dashboard"

File Count: 2-5 files


4. Bugfix (Complexity: 4-6)

Keywords: "fix", "bug", "broken", "not working", "issue"

Indicators:

  • Something currently broken
  • 1-3 files targeted
  • Root cause investigation needed
  • Tests should reproduce bug first

Example: "Fix tour dismissal not persisting in localStorage"

File Count: 1-3 files


5. Testing (Complexity: 3-5)

Keywords: "test", "validate", "spec", "e2e", "playwright"

Indicators:

  • Writing test coverage only
  • No production code changes
  • Test files only involved
  • May need test fixtures/helpers

Example: "Write Playwright tests for routing UI"

File Count: 1-3 test files


6. Documentation (Complexity: 1-3)

Keywords: "document", "readme", "guide", "comment"

Indicators:

  • Markdown files only
  • No code changes
  • Explaining existing functionality
  • Quick turnaround

Example: "Update README with smart routing usage"

File Count: 1-2 markdown files


Classification Output Format

{
  "pattern": "multi-file-refactor",
  "complexity": 8,
  "file_count": 7,
  "reasoning": "Restructuring routing across CFO + SLM + Dashboard",
  "recommended_model": "opus",
  "estimated_prompts": 2
}

Detection Logic (Pseudocode)

function classifyTask(prompt, mentionedFiles) {
  const lower = prompt.toLowerCase();
  const fileCount = mentionedFiles.length;
  
  // Check keywords in order of specificity
  if (containsAny(lower, ['design', 'architecture', 'integrate'])) {
    return { pattern: 'architecture', complexity: 9, fileCount };
  }
  
  if (contains(lower, 'refactor') && fileCount >= 5) {
    return { pattern: 'multi-file-refactor', complexity: 8, fileCount };
  }
  
  if (containsAny(lower, ['fix', 'bug', 'broken'])) {
    return { pattern: 'bugfix', complexity: 5, fileCount };
  }
  
  if (containsAny(lower, ['add', 'create', 'implement'])) {
    return { pattern: 'feature', complexity: 6, fileCount };
  }
  
  if (containsAny(lower, ['test', 'spec', 'playwright'])) {
    return { pattern: 'testing', complexity: 4, fileCount };
  }
  
  if (containsAny(lower, ['document', 'readme'])) {
    return { pattern: 'documentation', complexity: 2, fileCount };
  }
  
  // Default
  return { pattern: 'unknown', complexity: 5, fileCount };
}

Integration with Smart Router

  1. User submits prompt
  2. Fast classification runs (no LLM call needed)
  3. Pattern β†’ query effectiveness log
  4. Historical data β†’ recommend best model
  5. Show recommendation to user

Model Recommendations by Pattern

Based on typical complexity:

  • Architecture: Opus (needs creativity + planning)
  • Multi-file refactor: Opus or Sonnet (depends on complexity)
  • Feature: Sonnet (balanced speed/quality)
  • Bugfix: Sonnet or Haiku (depends on investigation needed)
  • Testing: Sonnet (needs understanding of code)
  • Documentation: Haiku (fast, straightforward)

These are DEFAULTS - actual recommendations come from effectiveness tracking.