fix: address community issues #37 #30 #36

- s03: inject reminder into tool_result instead of mutating history (#37)
- s05: SkillLoader uses rglob("SKILL.md") + frontmatter name priority,
  matching Agent Skills standard (#30, PR #34)
- CI: upgrade actions/checkout and actions/setup-node to v6 (#36)
- docs: update s05 skill directory structure in all 3 languages

agents/s03_todo_write.py

@@ -163,11 +163,7 @@ TOOLS = [
 def agent_loop(messages: list):
     rounds_since_todo = 0
     while True:
-        # Nag reminder: if 3+ rounds without a todo update, inject reminder
-        if rounds_since_todo >= 3 and messages:
-            last = messages[-1]
-            if last["role"] == "user" and isinstance(last.get("content"), list):
-                last["content"].insert(0, {"type": "text", "text": "<reminder>Update your todos.</reminder>"})
+        # Nag reminder is injected below, alongside tool results
         response = client.messages.create(
             model=MODEL, system=SYSTEM, messages=messages,
             tools=TOOLS, max_tokens=8000,
@@ -189,6 +185,8 @@ def agent_loop(messages: list):
                 if block.name == "todo":
                     used_todo = True
         rounds_since_todo = 0 if used_todo else rounds_since_todo + 1
+        if rounds_since_todo >= 3:
+            results.insert(0, {"type": "text", "text": "<reminder>Update your todos.</reminder>"})
         messages.append({"role": "user", "content": results})
 
 

agents/s05_skill_loading.py

@@ -7,19 +7,25 @@ Two-layer skill injection that avoids bloating the system prompt:
     Layer 1 (cheap): skill names in system prompt (~100 tokens/skill)
     Layer 2 (on demand): full skill body in tool_result
 
+    skills/
+      pdf/
+        SKILL.md          <-- frontmatter (name, description) + body
+      code-review/
+        SKILL.md
+
     System prompt:
     +--------------------------------------+
     | You are a coding agent.              |
     | Skills available:                    |
-    |   - git: Git workflow helpers        |  <-- Layer 1: metadata only
-    |   - test: Testing best practices     |
+    |   - pdf: Process PDF files...        |  <-- Layer 1: metadata only
+    |   - code-review: Review code...      |
     +--------------------------------------+
 
-    When model calls load_skill("git"):
+    When model calls load_skill("pdf"):
     +--------------------------------------+
     | tool_result:                         |
     | <skill>                              |
-    |   Full git workflow instructions...  |  <-- Layer 2: full body
+    |   Full PDF processing instructions   |  <-- Layer 2: full body
     |   Step 1: ...                        |
     |   Step 2: ...                        |
     | </skill>                             |
@@ -44,10 +50,10 @@ if os.getenv("ANTHROPIC_BASE_URL"):
 WORKDIR = Path.cwd()
 client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
 MODEL = os.environ["MODEL_ID"]
-SKILLS_DIR = WORKDIR / ".skills"
+SKILLS_DIR = WORKDIR / "skills"
 
 
-# -- SkillLoader: parse .skills/*.md files with YAML frontmatter --
+# -- SkillLoader: scan skills/<name>/SKILL.md with YAML frontmatter --
 class SkillLoader:
     def __init__(self, skills_dir: Path):
         self.skills_dir = skills_dir
@@ -57,10 +63,10 @@ class SkillLoader:
     def _load_all(self):
         if not self.skills_dir.exists():
             return
-        for f in sorted(self.skills_dir.glob("*.md")):
-            name = f.stem
+        for f in sorted(self.skills_dir.rglob("SKILL.md")):
             text = f.read_text()
             meta, body = self._parse_frontmatter(text)
+            name = meta.get("name", f.parent.name)
             self.skills[name] = {"meta": meta, "body": body, "path": str(f)}
 
     def _parse_frontmatter(self, text: str) -> tuple:

agents/s_full.py

@@ -199,7 +199,7 @@ class SkillLoader:
     def __init__(self, skills_dir: Path):
         self.skills = {}
         if skills_dir.exists():
-            for f in sorted(skills_dir.glob("*.md")):
+            for f in sorted(skills_dir.rglob("SKILL.md")):
                 text = f.read_text()
                 match = re.match(r"^---\n(.*?)\n---\n(.*)", text, re.DOTALL)
                 meta, body = {}, text
@@ -209,7 +209,8 @@ class SkillLoader:
                             k, v = line.split(":", 1)
                             meta[k.strip()] = v.strip()
                     body = match.group(2).strip()
-                self.skills[f.stem] = {"meta": meta, "body": body}
+                name = meta.get("name", f.parent.name)
+                self.skills[name] = {"meta": meta, "body": body}
 
     def descriptions(self) -> str:
         if not self.skills: return "(no skills)"