Threejs World Generation
calesthio/OpenMontage
Build deterministic, editable, free-viewpoint Three.js worlds from text or structured briefs.
A skill your agent uses when turning a dense sculpt, scan or AI-generated mesh into clean topology in Blender, for animation, subdivision or a game low poly with a triangle budget.
$ npx skills add scenario-labs/skills --skill scenario-blender-retopology -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install scenario-labs/skills scenario-blender-retopology --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dcc/blender/scenario-blender-retopology .claude/skills/scenario-blender-retopology && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "scenario-blender-retopology" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopology into .claude/skills/scenario-blender-retopology/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-blender-retopology", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopologyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add scenario-labs/skills --skill scenario-blender-retopology -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install scenario-labs/skills scenario-blender-retopology --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dcc/blender/scenario-blender-retopology .agents/skills/scenario-blender-retopology && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "scenario-blender-retopology" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopology into .agents/skills/scenario-blender-retopology/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-blender-retopology", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add scenario-labs/skills --skill scenario-blender-retopology -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install scenario-labs/skills scenario-blender-retopology --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dcc/blender/scenario-blender-retopology .cursor/skills/scenario-blender-retopology && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "scenario-blender-retopology" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopology into .cursor/skills/scenario-blender-retopology/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-blender-retopology", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/scenario-labs/skills.git --path skills/dcc/blender/scenario-blender-retopology--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add scenario-labs/skills --skill scenario-blender-retopology -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install scenario-labs/skills scenario-blender-retopology --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dcc/blender/scenario-blender-retopology .gemini/skills/scenario-blender-retopology && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "scenario-blender-retopology" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopology into .gemini/skills/scenario-blender-retopology/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-blender-retopology", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install scenario-labs/skills scenario-blender-retopologyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add scenario-labs/skills --skill scenario-blender-retopology -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dcc/blender/scenario-blender-retopology .github/skills/scenario-blender-retopology && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "scenario-blender-retopology" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopology into .github/skills/scenario-blender-retopology/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-blender-retopology", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add scenario-labs/skills --skill scenario-blender-retopology -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install scenario-labs/skills scenario-blender-retopology --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dcc/blender/scenario-blender-retopology .opencode/skills/scenario-blender-retopology && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "scenario-blender-retopology" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/dcc/blender/scenario-blender-retopology into .opencode/skills/scenario-blender-retopology/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-blender-retopology", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
scenario-blender-retopologyA skill your agent uses when turning a dense sculpt, scan or AI-generated mesh into clean topology in Blender, for animation, subdivision or a game low poly with a triangle budget.
Scenario Blender Retopology is an agent skill from scenario-labs/skills. Use when turning a dense sculpt, scan or AI-generated mesh into clean topology in Blender, for animation, subdivision or a game low poly with a triangle budget. Also when choosing between QuadriFlow or voxel remesh and manual retopo, placing loops around eyes, mouth and joints, deciding pole placement, setting up a Shrinkwrap cage, fixing volume loss after subdivision, preparing a low poly for baking, or auditing topology for spirals, 6-poles and triangles. Keywords: retopo, retopology, quad remesh, clean up an…
Its SKILL.md is about 5.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `references/critique.md`, `references/expert-notes.md` and `references/procedures.md`).
It sits in Game Development. It works with Blender. The repository describes itself as: Get production-ready images, video, audio, and 3D from any AI agent: skills that pick the right model, price before spending, and keep characters and brands consistent through… The licence is MIT.
8 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f6f8ab7. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
npxFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Scenario Blender Retopology loads about 5.5k tokens when it runs, and up to ~31k if it reads all its reference files. Until then it costs about 146 tokens; SKILL.md has 1,867 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 1,867 words, ~5,507 tokens.
.claude/skills/scenario-blender-retopology/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.Expert retopology is a plan executed with the fewest loops that capture the forms and let the mesh deform: loops close around eyes, mouth and joints, poles sit where nothing moves, and the subdivided surface, not the cage, matches the sculpt. An agent without a mouse can build every piece of this from data, but it reaches expert quality only on the parts it plans explicitly. Automatic remeshing is a finish for static assets and a start for everything else. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.
REQUIRED BACKGROUND: scenario-blender-expert (execution channel, review loop, 5.2 API changes). Toolkit: scripts/bx_retopo.py (import sys; sys.path.append("<skills>/scenario-blender-retopology/scripts"); import bx_retopo as R), all coordinates in the sculpt's local space.
R.surface_point), then builds.R.fit_subdiv. Kaspar's Multires Apply Base does the same job but overshoots (measured below).| Input | Why it changes the plan | Default when silent |
|---|---|---|
| Purpose | film cage renders at subdivision 2 (Kaspar); game ships triangles and bakes | deforming character: film-style all-quad cage |
| Budget | film: no vertex budget, minimum loops (Kaspar); game: triangle budget | film stylized head 1,650 to 4,100 faces, body 9,400 to 16,500 (Blender Studio meshes); game character < 10,000 tris |
| Deformation | face rig, joints, how far the mouth travels (expression bounds) | face + limbs deform |
| Camera | detail and density follow the closest view (SpeedChar) | close-up face |
| Style | stylized: creases in topology; realistic: generic base + displacement (Kaspar) | stylized |
| Symmetry | R.topology_report(sculpt)["sym_local_pct"], local space | Mirror only above ~98 % (the sheep is 21 %, posed) |
| Separate parts | eyes, teeth, hair clumps, clothing (from the body duplicate) | separate objects |
Inspect (procedures P1): holes, manifoldness, scale, rotation, symmetry. GATE: all four written down.
Map: read the sculptor's face sets first (R.face_set_map, R.face_set_review, P1b: lip line, eye masks, ears, hooves); landmarks with coordinates, loop counts per feature from the Numbers table, crease list (check expression shape keys), per-part density. GATE: map exists before any geometry.
Choose a method per part:
| Part | Method | Evidence |
|---|---|---|
| Eyes, mouth, brows (deforming) | carve_rings(corners=, count=(lo, hi)): upper = lower by construction, geodesic rings, the border's count kept when inside the range; pair odd boundaries first (parity_strip) | v2: eyes 24 (12/12), mouth 30 (15/15) on every clean ring; forcing Kaspar's 18/24 cost 40 more poles |
| Nasolabial, face frame, neck (map lines) | carve_band along enclosing_contour of face sets (P7): one clean loop, poles pushed onto the base | v2: nasolabial +18 poles; face frame opt-in, +64 poles on the sheep |
| Limbs, ears, tail, fingers, horns | limb_profile (geodesic contours, root and joints found) + socket_tube(count=) (P3b, P8); straight parts: tube from sections | v2: all 7 parts incl. the 1 m curled tail, 3 rings per joint |
| Skull, torso, smooth masses | QuadriFlow start acceptable, else grid patches | little deformation |
| Static prop, scan, bake-only | QuadriFlow whole object (R.quadriflow) | Lampel, Grant Abbitt |
| Realistic human head | shrinkwrap a clean generic base mesh, then fit (Kaspar BCON22 [00:20:16]) | not scripted here |
Build islands separately and roughly (Kaspar: "don't focus on tweaking all the points"). Stack via R.setup_cage (Mirror clip > Shrinkwrap Target Normal Project > Subsurf hidden in edit mode). GATE: topology gate below passes per island.
Relax and freeze hand-built layouts: R.relax, R.freeze. Not after QuadriFlow (worsened coverage 0.44 % to 0.55 %).
Connect by counts: R.boundary_loops, then R.bridge / R.weld_loops on equal counts; reduce the larger side first (Kaspar: wrist 10 vs hand 16 was "six too many"). GATE: no triangles created.
Volume: film R.fit_subdiv (gentle defaults); game R.push_outside then R.triangulate_twisted and a Triangulate modifier on export.
Review and hand off: gates, two render sheets, handoff hygiene (P13). Report what the agent did not plan.
tests/code/blender-retopology/sheep_results.json and compare/metrics.json)| Strategy | Faces | Subdiv-2 mean error | Inside | Eye / mouth rings | Closed-loop edges | Looks |
|---|---|---|---|---|---|---|
| Kaspar's own retopo | 2,596 | 0.24 % | 47 % | 5,5 / 2 | 29.9 % | clean, reads unsubdivided |
| QuadriFlow, area-matched budget | 4,372 | 0.14 % | 87 % | 0 / 0 | 1.6 % | faceted, torn ear, uniform density |
+ gentle fit_subdiv | 4,372 | 0.045 % | 53 % | 0 / 0 | 1.6 % | smooth masses, lumpy hooves |
| + Multires Apply Base instead | 4,372 | 0.11 % | 15 % | 0 / 0 | 1.6 % | overshoot |
| Hybrid: eye rings + ear tubes + gentle fit | 4,544 | 0.042 % | 52 % | 3,3 / 0 | 5.9 % | first skill version |
| E1 run with the skill (fresh agent: face sets, warp, 4 eye rings, 5 lip rings, limb tubes) | 5,778 | 0.040 % | 51 % | 4,4 / 5 (46 to 48 verts) | 19.4 % | planned face, rippled lids, lumps at leg joins |
v2 tools, final (test_sheep_v2.py: face sets, counts as ranges, corner split, geodesic rings and tubes, nasolabial loop) | 4,980 | 0.028 % | 52 % | 4,4 clean 24-vert rings, 12/12 / 5 x 30, 15/15 | 33.9 % | best agent result: poles 5.7 % (Kaspar 5.2 %), none on clean rings, no 6-poles; nose and upper-lip patch irregular (human pass) |
Numbers flatter the agent: an aggressive fit scored 0.043 % and looked lumpier than Kaspar's cage. What stays human-level only: articulation counts with handle loops, crease loops placed from expression shapes, pole routing and loop budgets out of the face. Say so in the report.
| Item | Value | Source |
|---|---|---|
| Render subdivision (film) | 2 levels; viewport 1 | Kaspar Live #6 [00:21:53]; BCON22 frame 00:26:38 |
| Joint | 3 loops over the bending part | Kaspar Live #5 [01:37:48] |
| Limb start ring | 8 verts (legs 8 then 12); Dikko arms 8 min, 10 to 12 typical, legs 18 | Kaspar Live #4 [00:06:54]; Dikko [00:13:47] |
| Eyelid | 2 loops per lid crease + ~4 across; 10/10 spans example | Kaspar Live #1 [02:11:22]; Dikko [00:04:16] |
| Studio mesh | 99.9 %+ quads, 0 to 4 valence 6+ (report and justify each), poles ~1.8 % head, ~5 % body, edge CV 0.33 to 0.8 | calibration (bx_audit on Blender Studio files) |
| Auto-remesh hint (not a gate) | edge CV ~0.17 to 0.27 on an unedited uniform remesh, near 0 % closed loops | calibration, sheep |
| Game | head 2,000 to 3,000 tris, hands ~1,000 both, body 5,000 to 6,000 | SpeedChar ep23 [00:09:58], ep24 [00:50:34] |
| Apply Base levels | 2 body, 3 head, hair, clothes | Kaspar Live #5 [02:15:03] |
Code (thresholds [added], calibrated on Kaspar's sheep: 0.24 % mean, 47 % inside, coverage p95 0.82 %):
retopo_gate = R.topology_report(retopo)
fit_gate = R.fidelity(retopo, sculpt, levels=2)
gate = {"six_poles_to_justify": retopo_gate["valence_6plus"], "no_rim_poles": retopo_gate["rim_poles"] == 0,
"quads": retopo_gate["non_quads_visible"] == 0 or retopo_gate["quads_pct"] >= 99.0,
"subd_fit": fit_gate["mean_pct"] <= 0.3 and 40 <= fit_gate["inside_pct"] <= 60,
"coverage": fit_gate["cov_p95_pct"] <= 1.0, "loops": R.loop_stats(retopo)}
print(gate)Edge-length CV is never pass/fail (studio meshes read 0.33 to 0.8); 6-poles are reported and justified, not banned (studio 0 to 4). Also: crease_poles == 0, center_poles == 0 on mirrored faces, R.loops_around(retopo, eye, normal, max_radius) returns at least 3 closed rings per eye and mouth, ring counts equal before every merge, triangles only in hidden or rigid areas, budget met (R.tri_count). Visual (bx_review, same views as the sculpt): cage in wire (rings close, no wandering loops, poles in still areas) and subdivided matcap (lumps, pinching at poles, creases held), then the cage alone: it must read without subdivision (Kaspar Finale [01:58:41]). Score with references/critique.md.
| Mistake | Looks like | Fix |
|---|---|---|
| Carving around QuadriFlow's closed eye slits | every eye ring odd (47, 45), no all-quad fix | R.parity_strip between the two odd boundaries BEFORE carving |
| Counts inherited from a dense cut, or forced far below it | eye rings 46 to 48; or pole density 9.5 % | count=(lo, hi): each reduction unit costs 4 poles; ranges took the sheep from 9.5 to 5.7 % |
| 3D-nearest lookups where surfaces touch | a band or socket cut bites an ear lying on the cheek | geodesic fields, curve_verts, oriented nearest_vertex (built into bands and tubes) |
| Tight rings for an edge-flow loop | a ridge after subdivision | band spacing = edge length; tight only for creases |
| Shipping a snapped cage | subdivided surface inside the sculpt (87 %) | R.fit_subdiv |
| Shrinkwrap offset for volume | cavities worse | fit, offset 0 |
Raw quadriflow_remesh on a small dense mesh | CANCELED, "needs to be manifold" | R.quadriflow (scale trick, voxel fallback) |
| QuadriFlow symmetry left at its default True | wrong half on a posed mesh | symmetry=False unless symmetric |
| Relaxing an auto-remesh | tips and ears shrink | relax hand-built layouts only |
| Mark Sharp / Seam as reminders | shading breaks (4.1+), unwrap cuts | retopo_crease attribute (P5) |
| Grid fill on an odd loop | FINISHED, 0 faces | count first; R.grid_fill raises |
| Connecting parts early | every new loop runs everywhere | islands, count, merge last |
| Trusting mean error | lumpy fit passes | matcap review, gentle fit |
| Re-shrinkwrap after Apply Base | volume lost again | never (Kaspar Live #6 [00:20:08]) |
| Game quads left non-planar | lines in the normal map | R.triangulate_twisted, Triangulate on export |
overlay.show_retopology, offset 0.01 m since 4.5); "Project Individual Elements" is snap_elements_individual = {'FACE_PROJECT'}. GUI only.bx_gui); headless use R.relax. F2, LoopTools, BSurfaces are extensions; mesh.circularize, space_edge_loops_evenly, flatten are built in; mesh.select_by_pole_count exists (4.4).sharp_edge is always honored since 4.1; Auto Smooth is gone (Smooth by Angle modifier).object.multires_base_apply(apply_heuristic=True); QuadriFlow lost its shortcut and has the traps above.references/procedures.md: tested code, P0 to P14 (inspect, face sets P1b, stack, tubes, geodesic limbs P3b, freeze/relax, annotations, QuadriFlow, map-line loops and rings, sockets, volume, checks, game, expression test, handoff, AI-mesh finishing). Load before writing any code.references/expert-notes.md: principles by expert with timestamps, face and body loop maps, clothing, game rules, the sheep experiment in full. Load when planning a face, body, clothing or game mesh.references/critique.md: the rubric to judge your own retopo. Load at every review.references/sources.md: all 24 source videos with best timestamps.© scenario-labs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 5 other files (scripts, references) in skills/dcc/blender/scenario-blender-retopology of scenario-labs/skills.
Open the folder on GitHubat commit f6f8ab7
Scenario Blender Retopology next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Scenario Blender Retopology this skillscenario-labs/skills | 946 | — | ~5.5k | Automated safety check: Pass | MIT | |
| Threejs World Generationcalesthio/OpenMontage | 66k | — | ~2k | Automated safety check: Pass | AGPL-3.0 | |
| 3Dviz Pro Max Scene Builderviettranx/3dviz-pro-max | 709 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Asset Pipelinerehan-remade/universal-modder | 6.5k | — | ~2k | Automated safety check: Pass | MIT | |
| Blender Image To 3Dmajidmanzarpour/blender-game-skills | 135 | — | ~5.7k | Automated safety check: Pass | MIT | |
| Text To 3D AssetLaurentiuGabriel/unreal-game-assets-creation-skill | 148 | — | ~2.1k | Automated safety check: Pass | None |
calesthio/OpenMontage
Build deterministic, editable, free-viewpoint Three.js worlds from text or structured briefs.
viettranx/3dviz-pro-max
Guides building an expressive 3D scene in Three.js or Blender by reasoning through intent, object construction and scientific grounding before using a catalog of recipes and kits.
rehan-remade/universal-modder
Turn generated or hand-made art into exactly what a game engine loads.
majidmanzarpour/blender-game-skills
Build a game-ready 3D asset in Blender from reference images (concept art, photos, turnarounds, sketches, screenshots) for any category, including characters, creatures, architecture, vehicles…
LaurentiuGabriel/unreal-game-assets-creation-skill
Generate a game-ready 3D asset by running the local AI pipeline sequentially: Fooocus (SDXL text-to-image) - Hunyuan3D-2 (image-to-textured-GLB) - optional Blender FBX convert + Unreal import.
zenstory-ai/novel-to-game
Builds a risk-matched whitebox or an approved production game candidate from a game design for its target runtime, with replayable evidence.
scenario-labs/skills
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scenario-labs/skills
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scenario-labs/skills
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scenario-labs/skills
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scenario-labs/skills
A skill your agent uses when animating characters or scenes in Godot 4.7: AnimationPlayer clips and RESET, AnimationTree state machines and blend spaces built in code, Mixamo or glTF import, loop…
scenario-labs/skills
A skill your agent uses when adding or fixing sound in Godot 4.7: audio buses and effects, volume sliders, 'too many sounds', combat audio with hundreds of enemies, sounds clipping or distorting, 3D…
Works with
Categories
A skill your agent uses when turning a dense sculpt, scan or AI-generated mesh into clean topology in Blender, for animation, subdivision or a game low poly with a triangle budget. Scenario Blender Retopology is an agent skill from scenario-labs/skills. Use when turning a dense sculpt, scan or AI-generated mesh into clean topology in Blender, for animation, subdivision or a game low poly with a triangle budget.
Scenario Blender Retopology fits situations like: turning a dense sculpt; AI-generated mesh into clean topology in Blender; A game low poly with a triangle budget.
Run `npx skills add scenario-labs/skills --skill scenario-blender-retopology -a claude-code`. Or copy the skill folder (skills/dcc/blender/scenario-blender-retopology in scenario-labs/skills) into .claude/skills/scenario-blender-retopology in your project. Claude Code loads it when a task matches its description.
Run `npx skills add scenario-labs/skills --skill scenario-blender-retopology -a codex`. Or copy the skill folder (skills/dcc/blender/scenario-blender-retopology in scenario-labs/skills) into .agents/skills/scenario-blender-retopology in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add scenario-labs/skills --skill scenario-blender-retopology -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scenario-blender-retopology, .gemini/skills/scenario-blender-retopology, .github/skills/scenario-blender-retopology and .opencode/skills/scenario-blender-retopology in your project.
Going by SKILL.md and its folder, Scenario Blender Retopology needs Python for the scripts in its folder and the command-line tools its instructions call (npx). Our summary lists: Python 3; Node.js.
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Scenario Blender Retopology is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.5k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 25k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Scenario Blender Retopology: Threejs World Generation (calesthio/OpenMontage, 66k stars), 3Dviz Pro Max Scene Builder (viettranx/3dviz-pro-max, 709 stars), Asset Pipeline (rehan-remade/universal-modder, 6.5k stars) and Blender Image To 3D (majidmanzarpour/blender-game-skills, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 946 GitHub stars. The repository holds 146 skills in this directory. The repository was last updated on October 10, 2026.
Source: scenario-labs/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.