design-validate

name

design-validate

description

Use this skill to run the full 5-layer validation pipeline on the kitchen permit drawings. Combines programmatic compliance (Layer 1), SVG text extraction (Layer 2), Claude dual-pass visual layout review (Layer 3), small-element checklist (Layer 4), and human escalation flags (Layer 5). Produces a unified validation report. Use for pre-permit sign-off or after any design change. DO NOT use for a quick single-check — use design:review instead.

design:validate — 5-Layer Kitchen Drawing Validation

What This Skill Does

Runs the layered validation pipeline from research/synthesis.md against the current output/kitchen/ drawings. Produces a unified report at /tmp/kitchen-validate/report.md with a pass/fail verdict per layer.

Layers:

• L1 — Programmatic clearance compliance (ezdxf geometry, no vision)
• L2 — SVG text extraction (dimension labels injected into all prompts)
• L3 — Claude dual-pass visual review (PNG spatial + text block)
• L4 — Small-element checklist (GFCI, hood, outlets)
• L5 — Human escalation flags (any LOW confidence item)

---

Prerequisites

• output/kitchen/ drawings are current: pixi run permit-docs was run after last spec change
• ~/.claude/skills/pdf-proof/.venv has: ezdxf, Pillow, PyMuPDF (fitz), cairosvg
• ~/.claude/skills/freecad-review/scripts/ has: extract_clearances.py, check_compliance.py

---

Step 1: L1 — Programmatic Compliance

Same as design:review Layer 1. Run extract_clearances.py and check_compliance.py against output/kitchen/kitchen_floor_plan_annotated.svg.

~/.claude/skills/pdf-proof/.venv/bin/python3 \
  ~/.claude/skills/freecad-review/scripts/extract_clearances.py \
  --svg /home/tstapler/Documents/711-N60th-Plans/output/kitchen/kitchen_floor_plan_annotated.svg \
  --output /tmp/kitchen-validate/clearances.json

~/.claude/skills/pdf-proof/.venv/bin/python3 \
  ~/.claude/skills/freecad-review/scripts/check_compliance.py \
  --clearances /tmp/kitchen-validate/clearances.json \
  --spec /home/tstapler/Documents/711-N60th-Plans/design_spec.py \
  --output /tmp/kitchen-validate/layer1.json

Record: L1_pass (bool), L1_failures (list of {rule, measured, required}).

---

Step 2: L2 — SVG Text Extraction

Extract all dimension labels from the floor plan SVG before any Claude vision call. This prevents measurement hallucination by injecting known labels into prompts.

import xml.etree.ElementTree as ET, json, pathlib

svg_path = '/home/tstapler/Documents/711-N60th-Plans/output/kitchen/kitchen_floor_plan_annotated.svg'
tree = ET.parse(svg_path)
ns = {'svg': 'http://www.w3.org/2000/svg'}
labels = [el.text.strip() for el in tree.iter('{http://www.w3.org/2000/svg}text')
          if el.text and el.text.strip()]
pathlib.Path('/tmp/kitchen-validate/layer2_labels.json').write_text(json.dumps(labels, indent=2))
print(f"Extracted {len(labels)} text labels")

Inject these labels as a preamble for all Claude vision calls in L3/L4:

"Labeled dimensions in drawing: {labels}. Do not estimate any unlabeled dimension."

---

Step 3: L3 — Claude Dual-Pass Visual Review

3a: Rasterize floor plan to PNG

~/.claude/skills/pdf-proof/.venv/bin/python3 - <<'EOF'
import cairosvg, pathlib
cairosvg.svg2png(
    url='/home/tstapler/Documents/711-N60th-Plans/output/kitchen/kitchen_floor_plan_annotated.svg',
    write_to='/tmp/kitchen-validate/floor_plan_2000px.png',
    output_width=2000
)
print("Rasterized")
EOF

3b: Pass 1 — Element Inventory

Read /tmp/kitchen-validate/floor_plan_2000px.png visually. Use this prompt structure:

System context: "You are reviewing a kitchen floor plan for a permit submission. The following dimension labels are present in the drawing: {L2 labels}. Do not estimate any unlabeled dimension — if a measurement is not in the label list, mark it as UNKNOWN."

Pass 1 prompt: "Using only the labeled dimensions listed and what you can see in the image, list every named element and its approximate zone position (use: north-wall, south-wall, island, east-wall, west-wall). Output as JSON with fields: element, zone, labeled_dimension (or null), notes."

Save output as /tmp/kitchen-validate/layer3_inventory.json.

3c: Pass 2 — Comparison vs. design_spec.py

Load design_spec.py SPEC values. Compare each inventoried element against spec:

Pass 2 prompt: "Given this element inventory {layer3_inventory} and this design spec {SPEC.to_json()}, identify every element whose drawn position or dimension CONFLICTS with the spec. For each conflict: cite the element, the drawn value, the spec value, and your confidence (HIGH/MEDIUM/LOW). Output as JSON with fields: element, drawn, spec, confidence."

Save as /tmp/kitchen-validate/layer3_conflicts.json.

---

Step 4: L4 — Small-Element Checklist

For each of the following, crop a 400×400px region around its expected position from floor_plan_2000px.png and ask a yes/no question:

Element	Expected Location	Check Question
GFCI outlet	N wall near sink	"Is a GFCI outlet symbol visible near the sink?"
Range hood	Island center	"Is a hood/ventilation symbol visible above the island range?"
DW outlet	E wall near DW	"Is an outlet symbol visible adjacent to the dishwasher?"

Use the L2 label list as context. Record: {element: pass/fail/cannot_verify}.

---

Step 5: L5 — Human Escalation Flags

Aggregate all LOW confidence items from L3 Pass 2 and any cannot_verify from L4. These must be manually reviewed before permit submission.

import json, pathlib

conflicts = json.loads(pathlib.Path('/tmp/kitchen-validate/layer3_conflicts.json').read_text())
low_conf = [c for c in conflicts if c.get('confidence') == 'LOW']

escalations = [
    {"source": "L3", "item": c['element'], "reason": c.get('notes', '')}
    for c in low_conf
]

pathlib.Path('/tmp/kitchen-validate/layer5_escalations.json').write_text(
    json.dumps(escalations, indent=2)
)

---

Step 6: Write Unified Report

import json, pathlib, datetime

out = pathlib.Path('/tmp/kitchen-validate')
layer1 = json.loads((out / 'layer1.json').read_text()) if (out / 'layer1.json').exists() else {}
labels = json.loads((out / 'layer2_labels.json').read_text()) if (out / 'layer2_labels.json').exists() else []
conflicts = json.loads((out / 'layer3_conflicts.json').read_text()) if (out / 'layer3_conflicts.json').exists() else []
escalations = json.loads((out / 'layer5_escalations.json').read_text()) if (out / 'layer5_escalations.json').exists() else []

l1_pass = layer1.get('all_pass', False)
l3_high_conf_conflicts = [c for c in conflicts if c.get('confidence') == 'HIGH']

verdict = 'PASS' if (l1_pass and not l3_high_conf_conflicts and not escalations) else \
          'FIX-REQUIRED' if (not l1_pass or l3_high_conf_conflicts) else 'REVIEW-NEEDED'

report = f"""# Kitchen Drawing Validation Report
Generated: {datetime.datetime.now().isoformat()}

## Verdict: {verdict}

## L1 Programmatic Compliance: {'PASS' if l1_pass else 'FAIL'}
{json.dumps(layer1.get('failures', []), indent=2)}

## L2 Dimension Labels Extracted: {len(labels)} labels

## L3 Visual Conflicts (HIGH confidence):
{json.dumps(l3_high_conf_conflicts, indent=2)}

## L4 Small-Element Checklist:
(see /tmp/kitchen-validate/layer4_checklist.json)

## L5 Human Escalation Required ({len(escalations)} items):
{json.dumps(escalations, indent=2)}
"""

(out / 'report.md').write_text(report)
print(report)

---

Related Skills

• design:review — faster single-session review (Layers 0-3 only, no L4/L5)
• design:loop — iterative fix loop using design:review as the gate
• design:modify — apply a single spec change after a FAIL is identified