feat: Rename 'learn' to 'extract-skills' for clarity

CLAUDE.md

@@ -120,19 +120,19 @@ agentready assess-batch \
 
 **Feature**: Extract high-quality skills from assessments using Claude API
 
-The `learn` command analyzes assessment results to identify successful patterns and generates Claude Code skills. With `--enable-llm`, it uses Claude Sonnet 4.5 to create detailed, context-aware skill documentation.
+The `extract-skills` command analyzes assessment results to identify successful patterns and generates Claude Code skills. With `--enable-llm`, it uses Claude Sonnet 4.5 to create detailed, context-aware skill documentation.
 
 ### Basic Usage (Heuristic)
 
 ```bash
 # Extract skills using heuristic pattern extraction
-agentready learn .
+agentready extract-skills .
 
 # Generate SKILL.md files
-agentready learn . --output-format skill_md
+agentready extract-skills . --output-format skill_md
 
 # Create GitHub issue templates
-agentready learn . --output-format github_issues
+agentready extract-skills . --output-format github_issues
 ```
 
 ### LLM-Powered Enrichment
@@ -142,16 +142,16 @@ agentready learn . --output-format github_issues
 export ANTHROPIC_API_KEY=sk-ant-api03-...
 
 # Extract skills with LLM enrichment (top 5 skills)
-agentready learn . --enable-llm
+agentready extract-skills . --enable-llm
 
 # Enrich more skills with custom budget
-agentready learn . --enable-llm --llm-budget 10
+agentready extract-skills . --enable-llm --llm-budget 10
 
 # Bypass cache for fresh analysis
-agentready learn . --enable-llm --llm-no-cache
+agentready extract-skills . --enable-llm --llm-no-cache
 
 # Generate all formats with LLM enrichment
-agentready learn . --enable-llm --output-format all
+agentready extract-skills . --enable-llm --output-format all
 ```
 
 ### LLM Enrichment Features

specs/llm-pattern-extraction.md

@@ -815,10 +815,10 @@ def run_full_workflow(
 
 ### Phase 3: CLI Enhancement
 
-**File**: `src/agentready/cli/learn.py` (modifications)
+**File**: `src/agentready/cli/extract_skills.py` (modifications)
 
 ```python
-# Add new options to learn command
+# Add new options to extract-skills command
 @click.option(
     "--enable-llm",
     is_flag=True,
@@ -835,7 +835,7 @@ def run_full_workflow(
     is_flag=True,
     help="Bypass LLM response cache (always call API)",
 )
-def learn(repository, output_format, output_dir, attribute, min_confidence, verbose, enable_llm, llm_budget, llm_no_cache):
+def extract_skills(repository, output_format, output_dir, attribute, min_confidence, verbose, enable_llm, llm_budget, llm_no_cache):
     """Extract reusable patterns and generate Claude Code skills.
 
     ... existing docstring ...
@@ -1056,7 +1056,7 @@ dependencies = [
 ## Success Criteria
 
 1. **LLM Integration Works**:
-   - `agentready learn . --enable-llm` successfully calls Claude API
+   - `agentready extract-skills . --enable-llm` successfully calls Claude API
    - Enriched skills have detailed instructions (5-10 steps)
    - Code examples include real file paths from repository
 
@@ -1092,10 +1092,10 @@ export ANTHROPIC_API_KEY=sk-ant-api03-...
 agentready assess .
 
 # Extract skills with LLM enrichment
-agentready learn . --enable-llm --llm-budget 5 --verbose
+agentready extract-skills . --enable-llm --llm-budget 5 --verbose
 
 # Expected output:
-# 🧠 AgentReady Learning Loop
+# 🧠 AgentReady Skill Extraction
 # ==================================================
 # Repository: /Users/jeder/repos/agentready
 # LLM enrichment: ENABLED (budget: 5 skills)
@@ -1118,7 +1118,7 @@ agentready learn . --enable-llm --llm-budget 5 --verbose
 - [ ] Create `src/agentready/services/llm_cache.py`
 - [ ] Create `src/agentready/learners/llm_enricher.py`
 - [ ] Modify `src/agentready/services/learning_service.py`
-- [ ] Modify `src/agentready/cli/learn.py`
+- [ ] Modify `src/agentready/cli/extract_skills.py`
 - [ ] Create `tests/unit/learners/test_llm_enricher.py`
 - [ ] Run linters (black, isort, ruff)
 - [ ] Test on AgentReady repository (dogfooding)

src/agentready/cli/extract_skills.py

@@ -0,0 +1,241 @@
+"""Extract-skills command for extracting patterns and generating skills."""
+
+import os
+import sys
+from pathlib import Path
+
+import click
+
+from ..services.learning_service import LearningService
+
+
+@click.command("extract-skills")
+@click.argument("repository", type=click.Path(exists=True), default=".")
+@click.option(
+    "--output-format",
+    type=click.Choice(
+        ["json", "skill_md", "github_issues", "markdown", "all"], case_sensitive=False
+    ),
+    default="json",
+    help="Output format for discovered skills (default: json)",
+)
+@click.option(
+    "--output-dir",
+    type=click.Path(),
+    default=".skills-proposals",
+    help="Directory for generated skill files (default: .skills-proposals)",
+)
+@click.option(
+    "--attribute",
+    multiple=True,
+    help="Specific attribute(s) to extract (can be specified multiple times)",
+)
+@click.option(
+    "--min-confidence",
+    type=int,
+    default=70,
+    help="Minimum confidence score to include skills (default: 70)",
+)
+@click.option(
+    "--verbose",
+    "-v",
+    is_flag=True,
+    help="Enable verbose output with detailed skill information",
+)
+@click.option(
+    "--enable-llm",
+    is_flag=True,
+    help="Enable LLM-powered skill enrichment (requires ANTHROPIC_API_KEY)",
+)
+@click.option(
+    "--llm-budget",
+    type=int,
+    default=5,
+    help="Maximum number of skills to enrich with LLM (default: 5)",
+)
+@click.option(
+    "--llm-no-cache",
+    is_flag=True,
+    help="Bypass LLM response cache (always call API)",
+)
+def extract_skills(
+    repository,
+    output_format,
+    output_dir,
+    attribute,
+    min_confidence,
+    verbose,
+    enable_llm,
+    llm_budget,
+    llm_no_cache,
+):
+    """Extract reusable patterns and generate Claude Code skills.
+
+    Analyzes assessment results to identify successful patterns that could
+    be extracted as reusable Claude Code skills for other repositories.
+
+    This command looks for the most recent assessment in .agentready/ and
+    extracts skills from high-scoring attributes (default: ≥70% confidence).
+
+    REPOSITORY: Path to repository (default: current directory)
+
+    Examples:
+
+        \b
+        # Discover skills from current repository
+        agentready extract-skills .
+
+        \b
+        # Generate SKILL.md files
+        agentready extract-skills . --output-format skill_md
+
+        \b
+        # Create GitHub issue templates
+        agentready extract-skills . --output-format github_issues
+
+        \b
+        # Extract specific attributes only
+        agentready extract-skills . --attribute claude_md_file --attribute type_annotations
+
+        \b
+        # Generate all formats with higher confidence threshold
+        agentready extract-skills . --output-format all --min-confidence 85
+    """
+    repo_path = Path(repository).resolve()
+
+    # Validate repository exists
+    if not repo_path.exists():
+        click.echo(f"Error: Repository not found: {repo_path}", err=True)
+        sys.exit(1)
+
+    # Find latest assessment file
+    agentready_dir = repo_path / ".agentready"
+    if not agentready_dir.exists():
+        click.echo(
+            "Error: No assessment found in .agentready/\n"
+            "Run 'agentready assess .' first to generate an assessment.",
+            err=True,
+        )
+        sys.exit(1)
+
+    # Look for assessment files
+    assessment_files = sorted(agentready_dir.glob("assessment-*.json"))
+    if not assessment_files:
+        click.echo(
+            "Error: No assessment files found in .agentready/\n"
+            "Run 'agentready assess .' first to generate an assessment.",
+            err=True,
+        )
+        sys.exit(1)
+
+    # Use most recent assessment
+    assessment_file = assessment_files[-1]
+
+    # Display header
+    click.echo("🧠 AgentReady Skill Extraction")
+    click.echo("=" * 50)
+    click.echo(f"\nRepository: {repo_path}")
+    click.echo(f"Assessment: {assessment_file.name}")
+    click.echo(f"Output format: {output_format}")
+    click.echo(f"Min confidence: {min_confidence}%")
+    if attribute:
+        click.echo(f"Filtering attributes: {', '.join(attribute)}")
+
+    # Display LLM status
+    if enable_llm:
+        api_key = os.environ.get("ANTHROPIC_API_KEY")
+        if api_key:
+            click.echo(f"LLM enrichment: ENABLED (budget: {llm_budget} skills)")
+            if llm_no_cache:
+                click.echo("LLM cache: DISABLED")
+        else:
+            click.echo("⚠️  LLM enrichment: DISABLED (ANTHROPIC_API_KEY not set)")
+            enable_llm = False
+    click.echo()
+
+    # Create learning service
+    learning_service = LearningService(
+        min_confidence=min_confidence,
+        output_dir=output_dir,
+    )
+
+    # Run learning workflow
+    try:
+        results = learning_service.run_full_workflow(
+            assessment_file=assessment_file,
+            output_format=output_format,
+            attribute_ids=list(attribute) if attribute else None,
+            enable_llm=enable_llm,
+            llm_budget=llm_budget,
+        )
+    except Exception as e:
+        click.echo(f"\nError during skill extraction: {str(e)}", err=True)
+        if verbose:
+            import traceback
+
+            traceback.print_exc()
+        sys.exit(1)
+
+    # Display results
+    skills_count = results["skills_discovered"]
+    generated_files = results["generated_files"]
+
+    click.echo("=" * 50)
+    click.echo(
+        f"\n✅ Discovered {skills_count} skill(s) with confidence ≥{min_confidence}%\n"
+    )
+
+    # Show LLM info if used
+    if enable_llm and skills_count > 0:
+        enriched_count = min(llm_budget, skills_count)
+        click.echo(f"🤖 LLM-enriched {enriched_count} skill(s)\n")
+
+    if skills_count == 0:
+        click.echo("No skills met the confidence threshold.")
+        click.echo(
+            f"Try lowering --min-confidence (current: {min_confidence}) "
+            "or run assessment on a higher-scoring repository."
+        )
+        return
+
+    # Display discovered skills
+    if verbose:
+        click.echo("Discovered Skills:")
+        click.echo("-" * 50)
+        for skill in results["skills"]:
+            click.echo(f"\n📚 {skill.name}")
+            click.echo(f"   ID: {skill.skill_id}")
+            click.echo(f"   Confidence: {skill.confidence}%")
+            click.echo(f"   Impact: +{skill.impact_score} pts")
+            click.echo(f"   Reusability: {skill.reusability_score}%")
+            click.echo(f"   Source: {skill.source_attribute_id}")
+            click.echo(f"\n   {skill.pattern_summary}")
+        click.echo()
+
+    # Display generated files
+    click.echo("\nGenerated Files:")
+    click.echo("-" * 50)
+    for file_path in generated_files:
+        click.echo(f"  ✓ {file_path}")
+
+    # Next steps
+    click.echo("\n" + "=" * 50)
+    click.echo("\n📖 Next Steps:\n")
+
+    if output_format in ["skill_md", "all"]:
+        click.echo("  1. Review generated SKILL.md files in " + output_dir)
+        click.echo("  2. Test skills on 3-5 repositories")
+        click.echo("  3. Refine instructions based on testing")
+        click.echo("  4. Copy to ~/.claude/skills/ or .claude/skills/")
+
+    if output_format in ["github_issues", "all"]:
+        click.echo(f"  1. Review issue templates in {output_dir}")
+        click.echo("  2. Create GitHub issues:")
+        click.echo("     gh issue create --body-file .skills-proposals/skill-*.md")
+
+    if output_format == "json":
+        click.echo(f"  1. Review discovered-skills.json in {output_dir}")
+        click.echo("  2. Generate other formats:")
+        click.echo("     agentready extract-skills . --output-format all")
+
+    click.echo()

src/agentready/cli/main.py

@@ -57,7 +57,7 @@
 from .assess_batch import assess_batch
 from .bootstrap import bootstrap
 from .demo import demo
-from .learn import learn
+from .extract_skills import extract_skills
 from .repomix import repomix_generate
 from .research import research
 from .schema import migrate_report, validate_report
@@ -493,7 +493,7 @@ def generate_config():
 cli.add_command(assess_batch)
 cli.add_command(bootstrap)
 cli.add_command(demo)
-cli.add_command(learn)
+cli.add_command(extract_skills)
 cli.add_command(migrate_report)
 cli.add_command(repomix_generate)
 cli.add_command(research)