Inspect skill image text layers; inventory image references #698

Problem

No analyzer looks at image content bundled or cited in skills:
references.py treats markdown images as passive grammar,
mcp_tool_poisoning flags base64 blobs in metadata only, and the
LLM path is text-only (no image_url in any provider). SVG is
already visible to static patterns as text; PNG/JPG cited or bundled
are unscanned hiding places for payload text in metadata layers.

Proposed scope

• Per-skill inventory of LOCAL image files (markdown targets plus
  loose files) in the inspection ledger, no verdicts. Remote-cited
  URLs are inventoried but never fetched: no network access
  mid-scan, by design.
• Stdlib-only extraction of embedded text layers (PNG text chunks
  and EXIF, JPEG comments and EXIF, GIF comments) routed through
  the existing static prompt-injection patterns, with findings
  attributed to the image path. Bounded, never raises, no pixels,
  no new dependencies.
• Omitted deliberately: pixel decoding (no OCR), remote
  fetching, GIF plain-text extensions, WebP EXIF, BMP/WebP text
  layers. Rendered QR payloads and steganography need a vision-LLM
  design, proposed separately — not claimed here.

Acceptance

• Inventory present in the ledger for local files; remote URLs
  cited-but-unfetched.
• Extracted image text flows through static patterns with tests;
  textless images keep existing skip accounting.