Mirror — a deterministic SVG perception eye for LLM agents

Mirror renders SVG in a real browser and reports what is actually where — in grid cells and W3C color names, with prose and structured output — and it never guesses. Spatial layout constraints become unit tests. And every tool description is a claim the server proves about itself. Built for agents that can't afford to hallucinate coordinates.

What is this?

When an LLM agent edits an SVG, how does it know whether the change worked? Today it either guesses from the source text (and hallucinates positions, because layout is a render-time property, not a source property) or it takes a screenshot and guesses from pixels (and burns tokens on a vision round-trip that still can't name a color or address a region precisely).

Mirror is the third option: a measuring eye. It is a sensory organ for LLMs, not a tool with a purpose. It perceives and measures; it never interprets, decides, or acts — the brain (the LLM or you) does that. The eye has three tissues:

Because the measurement runs in a real browser engine, Mirror sees what the browser sees — including things the SVG source never tells you.

Killer demo: the perceive → constrain → correct → compare loop

A cold agent (no source code, MCP only) built a 17-element mission-control panel and verified it to an exact stop-condition. Here is the loop, with real outputs from that session:

# 1 — INSPECT: see the layout in LLM grammar (no constraints checked yet)
inspect(svg)
  → scene: 16 elements, grid 16×10, canvas_validity: valid
    e.g. { id: "led-ok", tag: "circle", cell: "B3", color: "lime" }
    colors come out as W3C NAMES, never hex.

# 2 — CONSTRAINTS: ask the vocabulary (it is finite and closed)
constraints()
  → 11 types. RIGHT-OF / BELOW deliberately do NOT exist
    (use LEFT-OF / ABOVE with swapped operands).

# 3 — ANALYZE: turn layout intent into unit tests
analyze(svg, ["#title CENTERED-IN #frame", "#led-ok ABOVE #led-warn", ...16 constraints])
  → PARTIAL: 2 unchecked SUBJECT_TIME_VARIANT
    "#beacon has an animated r → not measurable; geometrically satisfied @t0 (bbox …)"
    # the eye refuses to guess about an animated value. It says so, with a reason code.

# 4 — fix, re-analyze until PASS (convergence is tracked, not vibes)
analyze(svg_v3, [...], previousIssueCount: N)
  → PASS  (corrections == [] && unchecked == [] && canvas_validity == valid && diff == [])

# 5 — SNIPER LOOP: pin a baseline, edit, catch regressions in one call
bookmark("panel-pass", analysisId)
compare(sabotaged_svg, [], "panel-pass")
  → FAIL: FARBÄNDERUNG orange→crimson  +  VERSCHOBEN D7→H8
    with ready-to-apply fixes: { x: 262→182, y: 372→324 }
    # exactly the two injected faults. Nothing more, nothing less.

The agent's verdict, verbatim: "In 13 calls it never once guessed, lied, or made me guess. analyze landed on the first try. Lost diagnostic loops: 0." — 8.5/10.

Features — the honesty axes

Mirror's differentiator is not what it measures but that it is honest about what it cannot.

| Capability | What it gives the agent | Honest about | |----

... View full README on GitHub