Fix watch edge key, claw path, Blade support, WSL MCP docs (0.4.7)

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

CHANGELOG.md

@@ -2,6 +2,13 @@
 
 Full release notes with details on each version: [GitHub Releases](https://github.com/safishamsi/graphify/releases)
 
+## 0.4.7 (2026-04-12)
+
+- Fix: `watch` semantic edge preservation was always empty — `graph.json` uses `links` key but code read `edges` (#269)
+- Fix: `graphify claw install` now writes to `.openclaw/` (correct OpenClaw directory) instead of `.claw/` (#208)
+- Add: Blade template support — `@include`, `<livewire:>` components, and `wire:click` bindings extracted from `.blade.php` files (#242)
+- Docs: WSL/Linux MCP setup note — package name is `graphifyy`, use `.venv/bin/python3` in `.mcp.json` (#250)
+
 ## 0.4.6 (2026-04-12)
 
 - Add: Google Antigravity support — `graphify antigravity install` writes `.agent/rules/graphify.md` (always-on rules) and `.agent/workflows/graphify.md` (`/graphify` slash command) (#203, #199, #53)

README.md

@@ -165,6 +165,15 @@ python -m graphify.serve graphify-out/graph.json
 That gives the assistant structured graph access for repeated queries such as
 `query_graph`, `get_node`, `get_neighbors`, and `shortest_path`.
 
+> **WSL / Linux note:** Ubuntu ships `python3`, not `python`. Install into a project venv to avoid PEP 668 conflicts, and use the full venv path in your `.mcp.json`:
+> ```bash
+> python3 -m venv .venv && .venv/bin/pip install "graphifyy[mcp]"
+> ```
+> ```json
+> { "mcpServers": { "graphify": { "type": "stdio", "command": ".venv/bin/python3", "args": ["-m", "graphify.serve", "graphify-out/graph.json"] } } }
+> ```
+> Also note: the PyPI package is `graphifyy` (double-y) — `pip install graphify` installs an unrelated package.
+
 <details>
 <summary>Manual install (curl)</summary>
 
@@ -329,9 +338,25 @@ graphify sends file contents to your AI coding assistant's underlying model API
 
 NetworkX + Leiden (graspologic) + tree-sitter + vis.js. Semantic extraction via Claude (Claude Code), GPT-4 (Codex), or whichever model your platform runs. Video transcription via faster-whisper + yt-dlp (optional, `pip install graphifyy[video]`). No Neo4j required, no server, runs entirely locally.
 
+## Built on graphify — Penpax
+
+[**Penpax**](https://safishamsi.github.io/penpax.ai) is the enterprise layer on top of graphify. Where graphify turns a folder of files into a knowledge graph, Penpax applies the same graph to your entire working life — continuously.
+
+| | graphify | Penpax |
+|---|---|---|
+| Input | A folder of files | Browser history, meetings, emails, files, code — everything |
+| Runs | On demand | Continuously in the background |
+| Scope | A project | Your entire working life |
+| Query | CLI / MCP / AI skill | Natural language, always on |
+| Privacy | Local by default | Fully on-device, no cloud |
+
+Built for lawyers, consultants, executives, doctors, researchers — anyone whose work lives across hundreds of conversations and documents they can never fully reconstruct.
+
+**Free trial launching soon.** [Join the waitlist →](https://safishamsi.github.io/penpax.ai)
+
 ## What we are building next
 
-graphify is the graph layer. We are building [Penpax](https://safishamsi.github.io/penpax.ai) on top of it — an on-device digital twin that connects your meetings, browser history, files, emails, and code into one continuously updating knowledge graph. No cloud, no training on your data. [Join the waitlist.](https://safishamsi.github.io/penpax.ai)
+graphify is the graph layer. Penpax is the always-on layer on top of it — an on-device digital twin that connects your meetings, browser history, files, emails, and code into one continuously updating knowledge graph. No cloud, no training on your data. [Join the waitlist.](https://safishamsi.github.io/penpax.ai)
 
 ## Star history
 

graphify/__main__.py

@@ -74,7 +74,7 @@ _PLATFORM_CONFIG: dict[str, dict] = {
     },
     "claw": {
         "skill_file": "skill-claw.md",
-        "skill_dst": Path(".claw") / "skills" / "graphify" / "SKILL.md",
+        "skill_dst": Path(".openclaw") / "skills" / "graphify" / "SKILL.md",
         "claude_md": False,
     },
     "droid": {

graphify/detect.py

@@ -80,6 +80,9 @@ _ASSET_DIR_MARKERS = {".imageset", ".xcassets", ".appiconset", ".colorset", ".la
 
 
 def classify_file(path: Path) -> FileType | None:
+    # Compound extensions must be checked before simple suffix lookup
+    if path.name.lower().endswith(".blade.php"):
+        return FileType.CODE
     ext = path.suffix.lower()
     if ext in CODE_EXTENSIONS:
         return FileType.CODE

graphify/extract.py

@@ -1165,6 +1165,53 @@ def extract_php(path: Path) -> dict:
     return _extract_generic(path, _PHP_CONFIG)
 
 
+def extract_blade(path: Path) -> dict:
+    """Extract @include, <livewire:> components, and wire:click bindings from Blade templates."""
+    import re
+    try:
+        src = path.read_text(encoding="utf-8", errors="replace")
+    except OSError:
+        return {"error": f"cannot read {path}"}
+
+    file_nid = _make_id(str(path))
+    nodes = [{"id": file_nid, "label": path.name, "file_type": "code",
+              "source_file": str(path), "source_location": None}]
+    edges = []
+
+    # @include('path.to.partial') or @include("path.to.partial")
+    for m in re.finditer(r"@include\(['\"]([^'\"]+)['\"]", src):
+        tgt = m.group(1).replace(".", "/")
+        tgt_nid = _make_id(tgt)
+        if tgt_nid not in {n["id"] for n in nodes}:
+            nodes.append({"id": tgt_nid, "label": m.group(1), "file_type": "code",
+                          "source_file": str(path), "source_location": None})
+        edges.append({"source": file_nid, "target": tgt_nid, "relation": "includes",
+                      "confidence": "EXTRACTED", "confidence_score": 1.0,
+                      "source_file": str(path), "source_location": None, "weight": 1.0})
+
+    # <livewire:component.name /> or <livewire:component.name>
+    for m in re.finditer(r"<livewire:([\w.\-]+)", src):
+        tgt_nid = _make_id(m.group(1))
+        if tgt_nid not in {n["id"] for n in nodes}:
+            nodes.append({"id": tgt_nid, "label": m.group(1), "file_type": "code",
+                          "source_file": str(path), "source_location": None})
+        edges.append({"source": file_nid, "target": tgt_nid, "relation": "uses_component",
+                      "confidence": "EXTRACTED", "confidence_score": 1.0,
+                      "source_file": str(path), "source_location": None, "weight": 1.0})
+
+    # wire:click="methodName"
+    for m in re.finditer(r'wire:click=["\']([^"\']+)["\']', src):
+        tgt_nid = _make_id(m.group(1))
+        if tgt_nid not in {n["id"] for n in nodes}:
+            nodes.append({"id": tgt_nid, "label": m.group(1), "file_type": "code",
+                          "source_file": str(path), "source_location": None})
+        edges.append({"source": file_nid, "target": tgt_nid, "relation": "binds_method",
+                      "confidence": "EXTRACTED", "confidence_score": 1.0,
+                      "source_file": str(path), "source_location": None, "weight": 1.0})
+
+    return {"nodes": nodes, "edges": edges}
+
+
 def extract_lua(path: Path) -> dict:
     """Extract functions, methods, require() imports, and calls from a .lua file."""
     return _extract_generic(path, _LUA_CONFIG)
@@ -2655,7 +2702,11 @@ def extract(paths: list[Path]) -> dict:
     for i, path in enumerate(paths):
         if total >= _PROGRESS_INTERVAL and i % _PROGRESS_INTERVAL == 0 and i > 0:
             print(f"  AST extraction: {i}/{total} files ({i * 100 // total}%)", flush=True)
-        extractor = _DISPATCH.get(path.suffix)
+        # .blade.php must be checked before suffix lookup since Path.suffix returns .php
+        if path.name.endswith(".blade.php"):
+            extractor = extract_blade
+        else:
+            extractor = _DISPATCH.get(path.suffix)
         if extractor is None:
             continue
         cached = load_cached(path, root)

graphify/watch.py

@@ -43,7 +43,7 @@ def _rebuild_code(watch_path: Path, *, follow_symlinks: bool = False) -> bool:
                 existing = json.loads(existing_graph.read_text(encoding="utf-8"))
                 code_ids = {n["id"] for n in existing.get("nodes", []) if n.get("file_type") == "code"}
                 sem_nodes = [n for n in existing.get("nodes", []) if n.get("file_type") != "code"]
-                sem_edges = [e for e in existing.get("edges", [])
+                sem_edges = [e for e in existing.get("links", existing.get("edges", []))
                              if e.get("confidence") in ("INFERRED", "AMBIGUOUS")
                              or (e.get("source") not in code_ids and e.get("target") not in code_ids)]
                 result = {

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "graphifyy"
-version = "0.4.6"
+version = "0.4.7"
 description = "AI coding assistant skill (Claude Code, Codex, OpenCode, Cursor, OpenClaw, Factory Droid, Trae) - turn any folder of code, docs, papers, images, or videos into a queryable knowledge graph"
 readme = "README.md"
 license = { file = "LICENSE" }

tests/test_install.py

@@ -8,7 +8,7 @@ PLATFORMS = {
     "claude": (".claude/skills/graphify/SKILL.md",),
     "codex": (".agents/skills/graphify/SKILL.md",),
     "opencode": (".config/opencode/skills/graphify/SKILL.md",),
-    "claw": (".claw/skills/graphify/SKILL.md",),
+    "claw": (".openclaw/skills/graphify/SKILL.md",),
     "droid": (".factory/skills/graphify/SKILL.md",),
     "trae": (".trae/skills/graphify/SKILL.md",),
     "trae-cn": (".trae-cn/skills/graphify/SKILL.md",),
@@ -39,7 +39,7 @@ def test_install_opencode(tmp_path):
 
 def test_install_claw(tmp_path):
     _install(tmp_path, "claw")
-    assert (tmp_path / ".claw" / "skills" / "graphify" / "SKILL.md").exists()
+    assert (tmp_path / ".openclaw" / "skills" / "graphify" / "SKILL.md").exists()
 
 
 def test_install_droid(tmp_path):