Frontmatter
{
"name": "img2threejs",
"license": "MIT",
"version": "1.2.0",
"description": "Turn an object or character reference image into a quality-gated, animation-ready procedural Three.js model built in code. Use for image-to-3D reconstruction, detail-accurate object rebuilds, stylized\/likeness-maximized human characters, sculpt specs, and staged code generation."
}
img2threejs — Image to procedural Three.js
Rebuild the object visible in a reference image as a code-only procedural Three.js model,
gated by a staged sculpting pipeline and an AI-vision self-correction loop. This is
reconstruction-by-code, not photogrammetry, mesh extraction, or downloaded art packs.
Agent-agnostic: works under Claude Code, Codex, or OpenCode. Wherever this doc says "agent
vision" or "agent browser tool", use whatever the host provides — native image reading, a
browser MCP (playwright/chrome-devtools), the project preview, or a user-supplied screenshot.
When To Use
The user attaches/points to an object image and wants a procedural Three.js model, a
reconstruction/animation/destruction plan, a sculpt spec, or code. Also for material studies,
action-ready props, game objects, botanical/mechanical parts, and stylized reconstructions.
Core Promise
Sculpt from a photo, in order — never one-shot a mesh:
- Validate the image is a suitable 3D target (
grimoire/intake/validation_rubric.md).
- Assess object class + complexity, then write a
qualityContract before any code.
- Spec it: component hierarchy, materials, lighting, pivots, sockets, action anchors.
- Build pass-by-pass from blockout → structure → form → material → lighting → interaction → optimization.
- Verify each pass with a screenshot compared against the reference; fail a pass if an identity-defining feature is wrong even when the global score looks fine.
State explicitly when output is approximate/stylized/low-poly. A single image cannot reveal
hidden sides or guarantee exact geometry — say so instead of faking confidence.
Required Inputs
- one image path / screenshot / URL / attached image (if missing or unreadable, ask)
- intended use: prop, game object, hero render, playable/destructible object, animation rig
(default: real-time browser prop with interactive performance)
The Loop (scripts do enforcement; agent vision does judgment)
Run scripts from the skill root (forge/...). Pure Python 3.10+ stdlib, no pip installs.
Full flags: grimoire/scripts.md. Never let a script score visuals — that is the agent's job.
- Probe local images:
forge/stage1_intake/probe_image.py <image> (metadata only, not a visual check).
- Pre-Spec Assessment Gate — classify + score complexity + write the quality contract:
forge/stage2_spec/new_pre_spec_assessment.py "Name" --image <img> --complexity <simple|moderate|complex|ultra-complex> --out assessment.json. Rules: grimoire/intake/quality_contract.md.
Set objectClass.primaryDomain (object | character | hybrid) and fill the seeded
detailInventory (its targetMinDetails scales with complexity).
2b. Detail inventory (do not skip for detailed subjects) — scan zones and enumerate every
identity-defining small detail (gloss, bevel, fasteners, linework, contours, stains):
forge/stage1_intake/build_detail_inventory.py <image> --mode grid-3x3 --out-dir <dir> --out di.json.
Each detail MUST map to a component.localFeatures or material.localOverrides entry — never
prose only. Taxonomy + 3D-term recipes: grimoire/intake/detail_inventory.md.
2c. Character/hybrid subjects — capture head-unit proportions + facial/body landmarks:
forge/stage1_intake/extract_landmarks.py <image> --out anatomy.json --overlay overlay.png, then
fill preSpecAssessment.anatomy. Route: grimoire/character/reconstruction.md. For maximum
likeness use the projection-first path (grimoire/character/likeness_maximization.md): solve the camera
(stage1_intake/solve_camera_pose.py), de-light the photo (stage1_intake/delight_albedo.py), and project it onto
the fitted mesh (stage3_build/bake_projected_texture.py). A single image cannot guarantee 100% likeness —
report per-region confidence and request more views for a real person.
- Author the spec from the assessment:
forge/stage2_spec/new_sculpt_spec.py "Name" --image <img> --assessment assessment.json --out object-sculpt-spec.json.
Replace generic starter featureReviewTargets with the object's real identity-defining
systems (≤5 critical, ≤3 important per pass); for characters add anatomy-proportion,
face-landmark-placement, pose-silhouette, outfit-and-palette. Use 3D-graphics terms only
(grimoire/glossary/3d_vocabulary.md), never "nice/smooth/shiny".
- When material fidelity matters and a source image exists, extract reference PBR evidence per crop:
forge/stage1_intake/extract_pbr_evidence.py <crop> --out-dir <dir> --material-id <id> --target-threshold 0.7.
Confidence < 0.7 is a stop/refine-input signal, not a pass. It is inference, not inverse rendering.
- Validate, then strict-validate before generating code:
forge/stage2_spec/validate_sculpt_spec.py object-sculpt-spec.json then --strict-quality.
Strict blocks shallow specs (a complex object with one root, no repetition systems, no
local overrides, no micro groups is NOT implementation-ready even if JSON validates).
- Locked build passes — only touch the currently unlocked pass:
forge/stage3_build/orchestrate_passes.py status object-sculpt-spec.json
forge/stage3_build/orchestrate_passes.py check object-sculpt-spec.json --pass-id <pass>
forge/stage3_build/generate_threejs_factory.py object-sculpt-spec.json --out src/createObjectModel.ts
(generator is pass-gated: a future --pass-id fails until prior passes are reviewed continue).
- Render the current pass in a browser/preview, capture a screenshot at a review viewpoint.
- Package one side-by-side sheet, then inspect it with agent vision:
forge/stage4_review/make_comparison_sheet.py --reference <img> --render <shot> --out cmp.png --json.
- Record the review (overall + per-layer + per-feature scores + decision):
forge/stage4_review/append_review.py object-sculpt-spec.json --pass-id <pass> --fidelity <0-1> --action <continue|refine-spec|refine-code|request-input|stop> --summary "..." --render-screenshot <shot> --comparison-image cmp.png --ai-vision-score <0-1> --layer-scores-json '{...}' --feature-reviews-json <f.json> --in-place.
- Sync pipeline state after manual review edits:
forge/stage3_build/orchestrate_passes.py sync object-sculpt-spec.json --in-place.
Gates (do not skip)
- Suitability: pass / conditional / reject before any planning.
grimoire/intake/validation_rubric.md.
- Pre-spec / strict-quality: blocks code gen until the spec is deep enough for its contract.
- Screenshot feedback:
continue is allowed only with a render + comparison sheet + global
AI-vision score ≥ threshold (default 0.7) AND every critical feature ≥ its own threshold.
Details + per-layer scorecard: grimoire/feedback/render_capture.md.
- Action-ready: build a runtime hierarchy (pivots, sockets, colliders, destruction groups),
never an inert lump; expose
root.userData.sculptRuntime. grimoire/readiness/action_rigging.md.
- Attachment: child appendages (branches/limbs/handles/tubes) need
attachment.parentSocket,
localStart, localEnd, contactType, embedDepth/overlap, gapTolerance — no mid-air parts.
grimoire/readiness/joint_attachment.md.
- Material/lighting:
grimoire/feedback/shading_realism.md — independent PBR channels
(never alias albedo into roughness/normal/AO), macro/meso/micro frequency bands, real lights.
- Detail inventory: for
moderate+ subjects strict-quality blocks code gen until the
detailInventory reaches targetMinDetails and every detail maps to a real component/material
entry (gloss needs low-roughness/clearcoat; fasteners need instancing/micro parts).
- Character track: when
primaryDomain is character/hybrid (or --character), the spec
author auto-builds a stylized humanoid template (head/neck/torso/arms + hair, glasses,
headphones, face features), flattened to world space under a hidden root, with per-part
character materials and character build passes (proportion-lock, feature-placement).
strict-quality requires a filled anatomy block (head-units, proportions, face landmarks) and
character feature targets. Suitability routing for humans: grimoire/intake/validation_rubric.md
(stylized vs maximum-likeness). Stylized bust, not a face-copy; refine positions per reference.
Self-Correction
After every pass, decide exactly one: continue | refine-spec | refine-code | request-input | stop.
refine-spec fixes a wrong/missing/shallow spec (re-validate, don't patch code around it);
refine-code fixes geometry/material/lighting that doesn't match a sound spec. Full root-cause
guide + fidelity scale: grimoire/review/self_correction.md.
Implementation Rules (brief)
TypeScript + plain Three.js unless the project uses a wrapper. Group factory
createObjectNameModel(spec, options), reconstruction data kept separate from renderer objects,
deterministic seeds for all procedural noise. Prefer primitives / Shape extrude / curve+tube /
instancing / displacement / generated canvas textures before any external art. Full geometry &
material recipes + hard-won failure patterns: grimoire/build/geometry_patterns.md.
Output
- Analysis-only: suitability verdict + scores, object extraction, macro→micro hierarchy,
geometry strategy, material/lighting recipe, animation/destruction feasibility, plan + risks.
- Implementation: the above briefly, then edit code; verify with typecheck/build + a screenshot.
- Not feasible: name the blocker, ask for more views / cleaner image / accepted stylization /
a narrower target. "This cannot reach the requested fidelity from this image" is a valid result.
