Adapt Pinscope to DeepSeek, auto datasheets, and a shared library.

Based on manvalan/pinscope main. Default LLM is DeepSeek with local
skills and PDF ingest. Datasheets are fetched from LCSC/TI, stored in
the component library, and review extracts abs-max with a deeper
checklist. Adds scripts/update-pinscope.sh for the production host.

skills/extract-pintable/SKILL.md

@@ -41,7 +41,18 @@ Decode the MPN and package details into a single `PackageInfo`:
 
 Look for an "Ordering Information" or "Device Information" table in the datasheet — most datasheets have one.
 
-### 4. Assign component subtype (taxonomy)
+### 4. Extract absolute maximum ratings
+
+Copy the **Absolute Maximum Ratings** table (not Recommended Operating Conditions). For each row that a reviewer would need to compare against the schematic rails:
+
+- `parameter` (str) — as printed (`VCC`, `VIN`, `I/O pin voltage`, `Storage temperature`, …)
+- `min` / `max` (number or null) — numeric limit; omit the other side if the table only lists one
+- `unit` (str) — `V`, `mA`, `°C`, …
+- `source_page` (int) — 1-based datasheet page of that row
+
+Include supply voltages, pin/input voltages, input current, and temperature. Skip ESD human-body-model rows unless they are the only voltage limit given. Do not invent numbers; if the table is a raster with no readable values, return an empty array.
+
+### 5. Assign component subtype (taxonomy)
 
 The existing IC taxonomy subtypes are provided in the system prompt under `EXISTING IC TAXONOMY SUBTYPES`. Pick the best matching subtype based on the component's MPN, package info, and pin names.
 
@@ -49,7 +60,7 @@ If no existing subtype fits, propose a new one following the dot-notation conven
 
 Set the chosen subtype on the `component_subtype` field.
 
-### 5. Quality checks
+### 6. Quality checks
 
 Before producing output, verify:
 - Pin count matches what the datasheet says for this package
@@ -57,7 +68,7 @@ Before producing output, verify:
 - No pins are missing (compare against the datasheet's stated pin count)
 - Pin names look reasonable (not garbled OCR artifacts)
 
-### 6. Validate and output
+### 7. Validate and output
 
 Validate your extraction against the output schema:
 

skills/extract-pintable/schema.json

@@ -30,6 +30,20 @@
         },
         "required": ["number", "name"]
       }
+    },
+    "absolute_maximum_ratings": {
+      "type": "array",
+      "items": {
+        "type": "object",
+        "properties": {
+          "parameter": {"type": "string"},
+          "min": {"type": ["number", "null"]},
+          "max": {"type": ["number", "null"]},
+          "unit": {"type": "string"},
+          "source_page": {"type": "integer"}
+        },
+        "required": ["parameter", "unit", "source_page"]
+      }
     }
   },
   "required": ["component_subtype", "package_info", "pintable"]

skills/extract-pintable/validate.py

@@ -47,6 +47,21 @@ def validate(data: dict) -> list[str]:
             if dupes:
                 errors.append(f"Duplicate pin numbers: {dupes}")
 
+    if "absolute_maximum_ratings" in data:
+        ratings = data["absolute_maximum_ratings"]
+        if ratings is not None and not isinstance(ratings, list):
+            errors.append("absolute_maximum_ratings must be an array")
+        elif isinstance(ratings, list):
+            for i, row in enumerate(ratings):
+                if not isinstance(row, dict):
+                    errors.append(f"absolute_maximum_ratings[{i}] must be an object")
+                    continue
+                for f in ("parameter", "unit", "source_page"):
+                    if f not in row:
+                        errors.append(
+                            f"absolute_maximum_ratings[{i}] missing required field: {f}"
+                        )
+
     return errors