periscope/skills/extract-pattern/SKILL.md

skill_name, description

skill_name	description
extract-pattern	Extract passive component MPN pattern (resistor, capacitor, inductor) from a datasheet PDF. Returns structured data via the save_pattern tool.

Extract Passive Component Pattern

Extract the part numbering system from a passive component datasheet (resistor, capacitor, inductor) and return it as structured JSON via the save_pattern tool.

Steps

1. Read the datasheet PDF

The datasheet PDF is provided in the user message. Focus on finding the Part Numbering System, Ordering Information, or Explanation of Part No. section — every passive component datasheet has one. This section shows:

• A diagram or table breaking the MPN into positional fields
• The meaning of each field position
• Lookup tables mapping codes to values (sizes, tolerances, voltage ratings, etc.)
• An example part number with decoded fields

Also identify from the front page:

• Manufacturer name (e.g., "Uniroyal", "Samsung Electro-Mechanics")
• Component type — must be one of: resistor, capacitor, inductor
• Series/product name (e.g., "Thick Film Chip Resistors", "CL Series MLCC")

2. Extract each field

For every field in the part number format, extract:

• name — a short snake_case identifier matching the regex group name. Use these standard names where applicable:
  • size — package size code
  • tolerance — value tolerance
  • resistance — resistance value digits (for resistors)
  • capacitance — capacitance value digits (for capacitors)
  • inductance — inductance value digits (for inductors)
  • voltage — rated voltage
  • wattage — power rating (resistors)
  • dielectric — temperature characteristic / dielectric type (capacitors)
  • packing_type — tape/reel vs bulk
  • packing_qty — quantity per reel
  • series — product series prefix
  • special — special features
  • thickness — component thickness
  • reserved — reserved/unused codes
• position — 0-based character offset in the MPN string
• length — number of characters
• description — human-readable description from the datasheet
• lookup — complete mapping of code -> meaning extracted from the datasheet. For the primary value field (resistance/capacitance/inductance), leave lookup as {} since it's decoded algorithmically.

3. Determine the value decoder

Based on the component type and how the value field works, select the decoder type:

For capacitors using 3-digit EIA code in picofarads (e.g., "106" = 10x10^6 pF = 10uF):

{
  "type": "eia3_pf",
  "base_unit": "pF",
  "output_unit": "F",
  "letter_multipliers": {},
  "zero_code": null,
  "conditional_on": null
}

For resistors using 4-digit code where the digit layout depends on tolerance:

{
  "type": "eia4_ohm_conditional",
  "base_unit": "ohm",
  "output_unit": "ohm",
  "letter_multipliers": {"J": -1, "K": -2, "L": -3, "M": -4, "N": -5, "P": -6},
  "zero_code": "0000",
  "conditional_on": {
    "field": "tolerance",
    "high_tolerance": ["J"],
    "high_tolerance_layout": {
      "significant_start": 1,
      "significant_count": 2,
      "multiplier_index": 3
    },
    "low_tolerance_layout": {
      "significant_start": 0,
      "significant_count": 3,
      "multiplier_index": 3
    }
  }
}

Read the datasheet carefully for:

• Which tolerance codes use 3 vs 2 significant digits (the high_tolerance list)
• Whether letter multiplier codes are supported (J, K, L, etc.) and their exponent values
• Whether there's a special zero/jumper code

If the datasheet describes a different encoding scheme, adapt the decoder accordingly.

4. Build the regex pattern

Build a Python regex with named capture groups, one per field. The regex must:

• Start with ^ and end with $ (full MPN match)
• Use (?P<name>...) syntax for each field
• Be as specific as possible — enumerate known codes in alternation groups (e.g., (?P<size>0603|0805|1206)) rather than broad patterns like \d{4}
• Handle the value field with appropriate character classes (digits + any letter multiplier codes)

5. Assign component subtype (taxonomy)

The existing passive taxonomy subtypes are provided in the system prompt under EXISTING PASSIVE TAXONOMY SUBTYPES. Pick the most specific matching subtype.

If no existing subtype fits, propose a new one following the dot-notation convention (passive.{type}.{specific}).

6. Quality checks

Before producing output, verify:

• The regex matches ALL example MPNs (provided in the system prompt as BOM MPNs)
• Every field has position + length that sum correctly across the full MPN
• No field positions overlap
• The primary value field (resistance/capacitance) has an empty lookup dict (it's decoded algorithmically)
• All other fields have non-empty lookup dicts with codes extracted from the datasheet
• The value decoder type is appropriate for the component type

7. Validate and output

Validate your extraction against the output schema:

python3 /skills/extract-pattern/validate.py '<your JSON here>'

If validation passes, call the save_pattern tool with the structured result. Do NOT write files to disk — use the tool.