Fix validate_metadata layering and type annotations in _tools.py

CHANGELOG.md

@@ -3,10 +3,7 @@
 
 ### Added
 
-- **`create-skill` CLI command**: Generate standalone skill packages with embedded LanceDB databases. Supports tool selection, custom preamble/description, and optional config embedding. Generated packages register as `haiku.skills` entry points.
+- **`create-skill` CLI command**: Generate standalone skill packages with embedded LanceDB databases. Generated packages register as `haiku.skills` entry points.
-- **`haiku.rag.skill_generator`**: Programmatic API for skill generation (`generate_skill()`, `render_templates()`)
-- **`haiku.rag.skills._tools`**: Reusable tool implementations and `create_skill_tools()` factory shared by built-in and generated skills
-- **Jinja2 dependency**: Added for skill template rendering
 
 ## [0.35.0] - 2026-03-24
 

haiku_rag_slim/haiku/rag/skill_generator/__init__.py

@@ -36,13 +36,12 @@ def _get_env() -> Environment:
 
 
 def validate_metadata(name: str, description: str) -> None:
+    if not name.isidentifier():
+        raise ValueError(f"{name!r} is not a valid Python identifier")
+
     from haiku.skills import SkillMetadata
 
     SkillMetadata(name=name, description=description)
-    if not name.isidentifier():
-        raise ValueError(f"{name!r} is not a valid Python identifier")
-    if not name.islower():
-        raise ValueError(f"{name!r} must be lowercase")
 
 
 def validate_tools(tools: list[str]) -> None:

haiku_rag_slim/haiku/rag/skills/_tools.py

@@ -5,6 +5,7 @@ from pydantic import BaseModel
 from pydantic_ai import RunContext
 
 from haiku.rag.agents.research.models import Citation
+from haiku.rag.config.models import AppConfig
 from haiku.rag.tools.document import DocumentInfo
 from haiku.rag.tools.qa import QAHistoryEntry
 from haiku.skills.state import SkillRunDeps
@@ -25,7 +26,7 @@ class AnalysisEntry(BaseModel):
 async def find_relevant_prior_qa(
     qa_history: list[QAHistoryEntry],
     query: str,
-    config: Any,
+    config: AppConfig,
 ) -> list[QAHistoryEntry]:
     from haiku.rag.embeddings import get_embedder
     from haiku.rag.tools.qa import PRIOR_ANSWER_RELEVANCE_THRESHOLD
@@ -61,7 +62,7 @@ async def find_relevant_prior_qa(
 
 async def skill_search(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
     query: str,
     limit: int | None = None,
     document_filter: str | None = None,
@@ -85,7 +86,7 @@ async def skill_search(
 
 async def skill_list_documents(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
     limit: int | None = None,
     offset: int | None = None,
 ) -> list[dict[str, Any]]:
@@ -108,7 +109,7 @@ async def skill_list_documents(
 
 async def skill_get_document(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
     query: str,
 ) -> dict[str, Any] | None:
     from haiku.rag.client import HaikuRAG
@@ -130,7 +131,7 @@ async def skill_get_document(
 
 async def skill_ask(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
     question: str,
     qa_history: list[QAHistoryEntry] | None = None,
     document_filter: str | None = None,
@@ -166,7 +167,7 @@ async def skill_ask(
 
 async def skill_research(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
     question: str,
     document_filter: str | None = None,
 ) -> tuple[str, str, str]:
@@ -203,7 +204,7 @@ async def skill_research(
 
 async def skill_analyze(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
     question: str,
     document: str | None = None,
     filter: str | None = None,
@@ -235,7 +236,7 @@ def update_documents_state(
             documents_state.append(doc_info)
 
 
-def _get_state(ctx: RunContext[SkillRunDeps], state_type: type) -> Any:
+def _get_state(ctx: RunContext[SkillRunDeps], state_type: type[BaseModel]) -> Any:
     if ctx.deps and ctx.deps.state and isinstance(ctx.deps.state, state_type):
         return ctx.deps.state
     return None
@@ -243,8 +244,8 @@ def _get_state(ctx: RunContext[SkillRunDeps], state_type: type) -> Any:
 
 def create_skill_tools(
     db_path: Path,
-    config: Any,
+    config: AppConfig,
-    state_type: type,
+    state_type: type[BaseModel],
     tool_names: list[str],
 ) -> dict[str, Any]:
     """Create tool closures for a skill.

tests/test_skill_generator.py

@@ -43,7 +43,7 @@ class TestValidateMetadata:
             validate_metadata("Recipes", "A skill.")
 
     def test_rejects_empty_name(self):
-        with pytest.raises(ValueError, match="name"):
+        with pytest.raises(ValueError, match="identifier"):
             validate_metadata("", "A skill.")
 
     def test_rejects_not_identifier(self):
@@ -51,11 +51,11 @@ class TestValidateMetadata:
             validate_metadata("123abc", "A skill.")
 
     def test_rejects_spaces_in_name(self):
-        with pytest.raises(ValueError, match="name"):
+        with pytest.raises(ValueError, match="identifier"):
             validate_metadata("my recipes", "A skill.")
 
     def test_rejects_special_chars(self):
-        with pytest.raises(ValueError, match="name"):
+        with pytest.raises(ValueError, match="identifier"):
             validate_metadata("my@recipes", "A skill.")
 
     def test_rejects_empty_description(self):
@@ -313,7 +313,7 @@ class TestGenerateSkill:
 
     def test_rejects_invalid_name(self, tmp_path):
         db_path = _make_fake_lancedb(tmp_path / "test.lancedb")
-        with pytest.raises(ValueError, match="name"):
+        with pytest.raises(ValueError, match="identifier"):
             generate_skill(
                 db_path=db_path,
                 output_dir=tmp_path,