docs(skills): add dpdata plugin skill

skills/dpdata-plugin/SKILL.md

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+---
+name: dpdata-plugin
+description: Create and install dpdata plugins (especially custom Format readers/writers) using Format.register(...) and pyproject.toml entry_points under 'dpdata.plugins'. Use when extending dpdata with new formats or distributing plugins as separate Python packages.
+---
+
+# dpdata-plugin
+
+dpdata loads plugins in two ways:
+
+1. **Built-in plugins** in `dpdata.plugins.*` (imported automatically)
+1. **External plugins** exposed via Python package entry points: `dpdata.plugins`
+
+This skill focuses on **external plugin packages**, the recommended way to add new formats without modifying dpdata itself.
+
+## What can be extended?
+
+Most commonly: add a new **Format** (file reader/writer) via:
+
+```python
+from dpdata.format import Format
+
+
+@Format.register("myfmt")
+class MyFormat(Format): ...
+```
+
+## How dpdata discovers plugins
+
+dpdata imports `dpdata.plugins` during normal use (e.g. `dpdata.system` imports it). That module:
+
+- imports every built-in module in `dpdata/plugins/*.py`
+- then loads all **entry points** in group `dpdata.plugins`
+
+So an external plugin package only needs to ensure that importing the entry-point target triggers the `@Format.register(...)` side effects.
+
+## Minimal external plugin package (based on plugin_example/)
+
+### 1) Create a new Python package
+
+Example layout:
+
+```text
+dpdata_random/
+  pyproject.toml
+  dpdata_random/
+    __init__.py
+```
+
+### 2) Implement and register your Format
+
+In `dpdata_random/__init__.py` (shortened example):
+
+```python
+from __future__ import annotations
+
+import numpy as np
+from dpdata.format import Format
+
+
+@Format.register("random")
+class RandomFormat(Format):
+    def from_system(self, N, **kwargs):
+        return {
+            "atom_numbs": [20],
+            "atom_names": ["X"],
+            "atom_types": np.zeros(20, dtype=int),
+            "cells": np.repeat(np.eye(3)[None, ...], N, axis=0) * 100.0,
+            "coords": np.random.rand(N, 20, 3) * 100.0,
+            "orig": np.zeros(3),
+            "nopbc": False,
+        }
+```
+
+Return dicts must match dpdata’s expected schema (cells/coords/atom_names/atom_types/...).
+
+### 3) Expose an entry point
+
+In `pyproject.toml`:
+
+```toml
+[project]
+name = "dpdata_random"
+version = "0.0.0"
+dependencies = ["numpy", "dpdata"]
+
+[project.entry-points.'dpdata.plugins']
+random = "dpdata_random:RandomFormat"
+```
+
+Any importable target works; this pattern points directly at the class.
+
+### 4) Install and test
+
+In a clean env (recommended via `uv`):
+
+```bash
+uv run --with dpdata --with numpy python3 - <<'PY'
+import dpdata
+from dpdata.format import Format
+
+# importing dpdata will load entry points (dpdata.plugins)
+print('random' in Format.get_formats())
+PY
+```
+
+If it prints `True`, your plugin was discovered.
+
+## Debug checklist
+
+- Did you install the plugin package into the same environment where you run dpdata?
+- Does `pyproject.toml` contain `[project.entry-points.'dpdata.plugins']`?
+- Does importing the entry point module/class execute the `@Format.register(...)` decorator?
+- If using `uv run`, remember each command runs in its own environment unless you’re in a `uv` project (or you rely on `uv run --with ...`).