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name: img2threejs 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. license: Apache-2.0 version: 1.5.2

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.

This file is the always-loaded router: it holds the order of operations and every hard rule as one line. The full contract behind each rule lives in the grimoire/ or docs/ file that rule names — read the named file at the moment you reach that stage, not before.

Canonical shared checkout

Keep one checkout of this repository and let every host enter it through a symlink, so Claude and Codex execute the same code instead of drifting apart:

~/.claude/skills/img2threejs -> <your checkout>
~/.codex/skills/img2threejs  -> <your checkout>

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:

1. Run python3 forge/next.py --state .img2threejs/state.json [<spec>] first, at every start, resume, and before every correction iteration. It reports the ordered checklist, exact next command, evidence status, and bounded correction-loop status; it never replaces the spec/pass gates. Obey a hard stop; never continue from memory.
2. Validate the image is a suitable 3D target (grimoire/intake/validation_rubric.md).
3. Assess object class + complexity, then write a qualityContract before any code.
4. Spec it: component hierarchy, materials, lighting, pivots, sockets, action anchors.
5. Build pass-by-pass from blockout → structure → form → material → lighting → interaction → optimization.
6. 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.

Mandatory Local State Gate

Conversation context is disposable; .img2threejs/state.json is the local checklist authority. Initialize once per reconstruction, then gate every step through it:

python3 forge/state.py init --state .img2threejs/state.json --reference <img> --profile <generic|cs2|character|animated-character> --spec object-sculpt-spec.json
python3 forge/next.py --state .img2threejs/state.json [object-sculpt-spec.json]
python3 forge/state.py mark <step-id> --state .img2threejs/state.json --evidence <path>

• next.py prints the current step, pass, incomplete mandatory steps, exact next command, and loop/max. Exit code 3 or status=stopped is a hard stop: report the reason and request input. Never bypass it by reconstructing progress from chat history.
• Every completed step needs evidence; mark a non-applicable step skipped only with --reason — silent omission is forbidden. Loop counts derive from reviewHistory actions (refine-spec/refine-code), not agent memory. Defaults: 3 corrections per pass, 6 total.
• Profiles add mandatory gates without changing the core order: cs2 requires classification, manifest, and a machine-readable CS2 review before AI review; character requires the character contracts and landmark evidence; animated-character adds all of character plus the nine Stage R steps (grimoire/readiness/animation_contract.md). Pick it whenever the rig must MOVE — on character the Stage R gates are absent and the build completes without ever running them, which is how animation used to ship broken. Its order is load-bearing: repair the mesh, freeze it, bind additively, then verify parity. Every profile records suitability, projection applicability, and material-evidence applicability. The state file is a resumability index, not visual evidence: renders, specs, review history, and deterministic gates remain the authoritative artifacts.

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)
• for a CS2 request, an authoritative classification record (family/subtype and evidence refs) or an explicit request for the user/vision provider to supply one; heuristic detection alone is not enough to select a geometry adapter

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.

1. Analyze the image first (agent vision, before any script): work the layered observation protocol in grimoire/intake/image_analysis.md — identify/classify, decompose macro→meso→micro, map part relationships, name materials in PBR terms, list identity-defining features, and flag what the single view hides. Observation before inference; controlled 3D vocabulary; 3D object-space not 2D image-space. Then probe local images: forge/stage1_intake/probe_image.py <image> (metadata only, not a visual check). 1a. Local Spec Search — after image analysis, before writing or refining a spec, pull local domain evidence (anatomy/PBR/wear/geometry/runtime/physics) rather than inventing it: python3 forge/stage2_spec/new_pre_spec_assessment.py "Name" --image <img> --out assessment.json (auto-runs BM25, auto-picks cs2/core_3d collection, writes a localSpecSearch bundle that new_sculpt_spec.py --assessment carries into the spec). Full query-expansion recipe (bilingual terms, focused search_specs.py retrieval, cache rules): grimoire/intake/local_spec_search.md. MUST read it before retrying an incomplete or domain-specific query. 1b. CS2 intake manifest — for a CS2 request, create and validate cs2-intake.json before pre-spec authoring (admission, heuristic signal, classification, family/route resolution). MUST read grimoire/intake/cs2_intake_contract.md completely before creating the manifest or running pre-spec assessment. 1c. Optional fidelity evidence adapters — only when they improve an observed weak point; the stdlib core remains authoritative. Thin/complex masks → local SAM2; character face/pose → MediaPipe; weak front/back cues → Depth Anything V2 (forge/stage1_intake/run_vision_adapter.py <segment|landmarks|depth> ...; every adapter emits provenance; monocular depth is relative only). MCP-only scene mutations never count as implementation — write the proven change back to the spec or TypeScript, rebuild, recapture. Full adapter + MCP routing and authority boundaries: docs/integrations/reference_fidelity_tooling.md.
2. 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). Supported CS2 knife skins and Glock-18 assets: always pass --cs2, which defaults the complexity tier to ultra-complex (targetMinDetails 16, floor 9) — the finish/wear/hardware is the item, so CS2 is held to the top fidelity bar. Author procedural GEOMETRY but route the FINISH through the projection path in step 2c — a procedural finish for a patterned skin (Doppler/Gamma/Marble/Fade) reads visibly wrong against the reference. Finish routes + rulebook: grimoire/build/cs2_finishes.md; optional exact-texture acquisition: grimoire/intake/cs2_texture_acquisition.md. 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. Projection-first fidelity (characters AND reference-matched surfaces — supported CS2 skins, decals, painted patterns) — when the goal is matching a specific reference's surface, put the photo's own pixels on the mesh instead of approximating them procedurally. This is the single biggest fidelity lever; a procedural material for a patterned surface is the #1 reconstruction failure. Recipe (grimoire/character/likeness_maximization.md — its two levers generalize past characters): solve the camera (stage1_intake/solve_camera_pose.py → referenceCamera), de-light the reference (stage1_intake/delight_albedo.py, hard requirement — de-lighting is what makes projection safe), then project the de-lit crop and bake it into UVs (stage3_build/bake_projected_texture.py --mesh-id <id>). For a CS2 skin the projected de-lit crop IS the finish — no procedural Doppler material. For characters, first capture landmarks (stage1_intake/extract_landmarks.py --out anatomy.json), fill preSpecAssessment.anatomy, route grimoire/character/reconstruction.md. A single view cannot show hidden sides — report per-region confidence and request more views when it matters. Character sub-routes, in order — decide what parts exist before shaping any, and shape the head before the hair that sits on it:
   • Parts — grimoire/character/structure_decomposition.md
   • Head — grimoire/character/head_construction.md (what the likeness gate reads against)
   • Hair — grimoire/character/stylized_hair_threejs.md + parameter contract in grimoire/character/threejs_hair_parameter_contract.json. Lock topology only after the silhouette review passes: material tuning cannot repair wrong lock topology. 2d. Reference-free humanoid — a generic figure with no reference image has nothing to measure, so fill anatomy from public canon: forge/stage2_spec/humanoid_proportions.py <spec> --style-heads 8 --in-place. It writes anatomy.source: "canon-table" so canon is never mistaken for measurement, refuses to run when the spec names a reference image, and names anything the corpus does not supply rather than interpolating it.
3. Author the spec from the assessment: forge/stage2_spec/new_sculpt_spec.py "Name" --image <img> --assessment assessment.json --manifest cs2-intake.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-graphi