fix: instinct-cli glob and evolve --generate (fixes #216, #217)

- Load both .yaml and .yml files in load_all_instincts() (#216)
  The *.yaml-only glob missed .yml files, causing 'No instincts found'
- Implement evolve --generate to create skill/command/agent files (#217)
  Previously printed a stub message. Now generates SKILL.md, command .md,
  and agent .md files from the clustering analysis into ~/.claude/homunculus/evolved/

.cursor/skills/continuous-learning-v2/scripts/instinct-cli.py

@@ -88,7 +88,8 @@ def load_all_instincts() -> list[dict]:
     for directory in [PERSONAL_DIR, INHERITED_DIR]:
         if not directory.exists():
             continue
-        for file in directory.glob("*.yaml"):
+        yaml_files = sorted(set(directory.glob("*.yaml")) | set(directory.glob("*.yml")))
+        for file in yaml_files:
             try:
                 content = file.read_text()
                 parsed = parse_instinct_file(content)
@@ -433,15 +434,96 @@ def cmd_evolve(args):
             print()
 
     if args.generate:
-        print("\n[Would generate evolved structures here]")
+        generated = _generate_evolved(skill_candidates, workflow_instincts, agent_candidates)
-        print("  Skills would be saved to:", EVOLVED_DIR / "skills")
+        if generated:
-        print("  Commands would be saved to:", EVOLVED_DIR / "commands")
+            print(f"\n✅ Generated {len(generated)} evolved structures:")
-        print("  Agents would be saved to:", EVOLVED_DIR / "agents")
+            for path in generated:
+                print(f"   {path}")
+        else:
+            print("\nNo structures generated (need higher-confidence clusters).")
 
     print(f"\n{'='*60}\n")
     return 0
 
 
+# ─────────────────────────────────────────────
+# Generate Evolved Structures
+# ─────────────────────────────────────────────
+
+def _generate_evolved(skill_candidates: list, workflow_instincts: list, agent_candidates: list) -> list[str]:
+    """Generate skill/command/agent files from analyzed instinct clusters."""
+    generated = []
+
+    # Generate skills from top candidates
+    for cand in skill_candidates[:5]:
+        trigger = cand['trigger'].strip()
+        if not trigger:
+            continue
+        name = re.sub(r'[^a-z0-9]+', '-', trigger.lower()).strip('-')[:30]
+        if not name:
+            continue
+
+        skill_dir = EVOLVED_DIR / "skills" / name
+        skill_dir.mkdir(parents=True, exist_ok=True)
+
+        content = f"# {name}\n\n"
+        content += f"Evolved from {len(cand['instincts'])} instincts "
+        content += f"(avg confidence: {cand['avg_confidence']:.0%})\n\n"
+        content += f"## When to Apply\n\n"
+        content += f"Trigger: {trigger}\n\n"
+        content += f"## Actions\n\n"
+        for inst in cand['instincts']:
+            inst_content = inst.get('content', '')
+            action_match = re.search(r'## Action\s*\n\s*(.+?)(?:\n\n|\n##|$)', inst_content, re.DOTALL)
+            action = action_match.group(1).strip() if action_match else inst.get('id', 'unnamed')
+            content += f"- {action}\n"
+
+        (skill_dir / "SKILL.md").write_text(content)
+        generated.append(str(skill_dir / "SKILL.md"))
+
+    # Generate commands from workflow instincts
+    for inst in workflow_instincts[:5]:
+        trigger = inst.get('trigger', 'unknown')
+        cmd_name = re.sub(r'[^a-z0-9]+', '-', trigger.lower().replace('when ', '').replace('implementing ', ''))
+        cmd_name = cmd_name.strip('-')[:20]
+        if not cmd_name:
+            continue
+
+        cmd_file = EVOLVED_DIR / "commands" / f"{cmd_name}.md"
+        content = f"# {cmd_name}\n\n"
+        content += f"Evolved from instinct: {inst.get('id', 'unnamed')}\n"
+        content += f"Confidence: {inst.get('confidence', 0.5):.0%}\n\n"
+        content += inst.get('content', '')
+
+        cmd_file.write_text(content)
+        generated.append(str(cmd_file))
+
+    # Generate agents from complex clusters
+    for cand in agent_candidates[:3]:
+        trigger = cand['trigger'].strip()
+        agent_name = re.sub(r'[^a-z0-9]+', '-', trigger.lower()).strip('-')[:20]
+        if not agent_name:
+            continue
+
+        agent_file = EVOLVED_DIR / "agents" / f"{agent_name}.md"
+        domains = ', '.join(cand['domains'])
+        instinct_ids = [i.get('id', 'unnamed') for i in cand['instincts']]
+
+        content = f"---\nmodel: sonnet\ntools: Read, Grep, Glob\n---\n"
+        content += f"# {agent_name}\n\n"
+        content += f"Evolved from {len(cand['instincts'])} instincts "
+        content += f"(avg confidence: {cand['avg_confidence']:.0%})\n"
+        content += f"Domains: {domains}\n\n"
+        content += f"## Source Instincts\n\n"
+        for iid in instinct_ids:
+            content += f"- {iid}\n"
+
+        agent_file.write_text(content)
+        generated.append(str(agent_file))
+
+    return generated
+
+
 # ─────────────────────────────────────────────
 # Main
 # ─────────────────────────────────────────────

skills/continuous-learning-v2/scripts/instinct-cli.py

@@ -88,7 +88,8 @@ def load_all_instincts() -> list[dict]:
     for directory in [PERSONAL_DIR, INHERITED_DIR]:
         if not directory.exists():
             continue
-        for file in directory.glob("*.yaml"):
+        yaml_files = sorted(set(directory.glob("*.yaml")) | set(directory.glob("*.yml")))
+        for file in yaml_files:
             try:
                 content = file.read_text()
                 parsed = parse_instinct_file(content)
@@ -433,15 +434,96 @@ def cmd_evolve(args):
             print()
 
     if args.generate:
-        print("\n[Would generate evolved structures here]")
+        generated = _generate_evolved(skill_candidates, workflow_instincts, agent_candidates)
-        print("  Skills would be saved to:", EVOLVED_DIR / "skills")
+        if generated:
-        print("  Commands would be saved to:", EVOLVED_DIR / "commands")
+            print(f"\n✅ Generated {len(generated)} evolved structures:")
-        print("  Agents would be saved to:", EVOLVED_DIR / "agents")
+            for path in generated:
+                print(f"   {path}")
+        else:
+            print("\nNo structures generated (need higher-confidence clusters).")
 
     print(f"\n{'='*60}\n")
     return 0
 
 
+# ─────────────────────────────────────────────
+# Generate Evolved Structures
+# ─────────────────────────────────────────────
+
+def _generate_evolved(skill_candidates: list, workflow_instincts: list, agent_candidates: list) -> list[str]:
+    """Generate skill/command/agent files from analyzed instinct clusters."""
+    generated = []
+
+    # Generate skills from top candidates
+    for cand in skill_candidates[:5]:
+        trigger = cand['trigger'].strip()
+        if not trigger:
+            continue
+        name = re.sub(r'[^a-z0-9]+', '-', trigger.lower()).strip('-')[:30]
+        if not name:
+            continue
+
+        skill_dir = EVOLVED_DIR / "skills" / name
+        skill_dir.mkdir(parents=True, exist_ok=True)
+
+        content = f"# {name}\n\n"
+        content += f"Evolved from {len(cand['instincts'])} instincts "
+        content += f"(avg confidence: {cand['avg_confidence']:.0%})\n\n"
+        content += f"## When to Apply\n\n"
+        content += f"Trigger: {trigger}\n\n"
+        content += f"## Actions\n\n"
+        for inst in cand['instincts']:
+            inst_content = inst.get('content', '')
+            action_match = re.search(r'## Action\s*\n\s*(.+?)(?:\n\n|\n##|$)', inst_content, re.DOTALL)
+            action = action_match.group(1).strip() if action_match else inst.get('id', 'unnamed')
+            content += f"- {action}\n"
+
+        (skill_dir / "SKILL.md").write_text(content)
+        generated.append(str(skill_dir / "SKILL.md"))
+
+    # Generate commands from workflow instincts
+    for inst in workflow_instincts[:5]:
+        trigger = inst.get('trigger', 'unknown')
+        cmd_name = re.sub(r'[^a-z0-9]+', '-', trigger.lower().replace('when ', '').replace('implementing ', ''))
+        cmd_name = cmd_name.strip('-')[:20]
+        if not cmd_name:
+            continue
+
+        cmd_file = EVOLVED_DIR / "commands" / f"{cmd_name}.md"
+        content = f"# {cmd_name}\n\n"
+        content += f"Evolved from instinct: {inst.get('id', 'unnamed')}\n"
+        content += f"Confidence: {inst.get('confidence', 0.5):.0%}\n\n"
+        content += inst.get('content', '')
+
+        cmd_file.write_text(content)
+        generated.append(str(cmd_file))
+
+    # Generate agents from complex clusters
+    for cand in agent_candidates[:3]:
+        trigger = cand['trigger'].strip()
+        agent_name = re.sub(r'[^a-z0-9]+', '-', trigger.lower()).strip('-')[:20]
+        if not agent_name:
+            continue
+
+        agent_file = EVOLVED_DIR / "agents" / f"{agent_name}.md"
+        domains = ', '.join(cand['domains'])
+        instinct_ids = [i.get('id', 'unnamed') for i in cand['instincts']]
+
+        content = f"---\nmodel: sonnet\ntools: Read, Grep, Glob\n---\n"
+        content += f"# {agent_name}\n\n"
+        content += f"Evolved from {len(cand['instincts'])} instincts "
+        content += f"(avg confidence: {cand['avg_confidence']:.0%})\n"
+        content += f"Domains: {domains}\n\n"
+        content += f"## Source Instincts\n\n"
+        for iid in instinct_ids:
+            content += f"- {iid}\n"
+
+        agent_file.write_text(content)
+        generated.append(str(agent_file))
+
+    return generated
+
+
 # ─────────────────────────────────────────────
 # Main
 # ─────────────────────────────────────────────