feat: structured skill packages with config overrides, chaining, and TUI integration

Add a skill package system where each skill is a directory with a skill.yaml
manifest and prompt markdown files. Skills support /command triggers, scoped
config overrides (temperature, max_tokens, tool filtering), chain dependencies
with cycle-safe resolution, and a finish_skill completion signal.

Includes four built-in skills: explore, brainstorm, write-document, and plan.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

app/agent/loop.py

@@ -19,6 +19,7 @@ from app.utils.logging import get_logger
 
 if TYPE_CHECKING:
     from app.services.debug_log import DebugLogger
+    from app.services.skill_runner import SkillRunner
     from app.services.skills import SkillsManager
 
 logger = get_logger(__name__)
@@ -45,6 +46,7 @@ class AgentLoop:
         display: DisplayAdapter | None = None,
         debug_logger: DebugLogger | None = None,
         skills_manager: SkillsManager | None = None,
+        skill_runner: SkillRunner | None = None,
     ) -> None:
         self._config = config
         self._ctx = ctx
@@ -55,6 +57,7 @@ class AgentLoop:
         self._display = display
         self._debug = debug_logger
         self._skills = skills_manager
+        self._skill_runner = skill_runner
         self._tools_schema = registry.get_openai_tools_schema()
         self._system_prompt = self._build_system_prompt()
         self._cancelled = False
@@ -81,6 +84,11 @@ class AgentLoop:
         )
         if self._skills:
             prompt += self._skills.get_system_prompt_snippet()
+        if self._skill_runner and self._skill_runner.is_active:
+            prompt += (
+                f"\n\nCurrently active skill: {self._skill_runner.active_skill_name}. "
+                "When the skill's objective is complete, call the `finish_skill` tool."
+            )
         return prompt
 
     def _get_messages_with_system_prompt(self) -> list[Message]:
@@ -199,7 +207,12 @@ class AgentLoop:
                     name=result.tool_name,
                 )
 
-            # Check if finish tool was called
+            # Rebuild tools schema and system prompt if skill state may have changed
+            if any(r.tool_name in ("load_skill", "finish_skill") for r in results):
+                self._tools_schema = self._registry.get_openai_tools_schema()
+                self._system_prompt = self._build_system_prompt()
+
+            # Check if finish tool was called (finish_skill does NOT break the loop)
             if any(r.tool_name == "finish" for r in results):
                 break
         else: