Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/OpenDCAI/GameFactory-3Anpx agentmods add skills/opendcai/gamefactory-3a/imageWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/opendcai/gamefactory-3a/image)<a href="https://agentmods.dev/skills/opendcai/gamefactory-3a/image"><img src="https://agentmods.dev/badge/skills/opendcai/gamefactory-3a/image/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/opendcai/gamefactory-3a/image"><img src="https://agentmods.dev/badge/skills/opendcai/gamefactory-3a/image.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.02409 |
| Opus 5.5 | $0.00000 | $0.00964 |
| Sonnet 5.5 | $0.00000 | $0.00482 |
| Haiku 4.5 | $0.00000 | $0.00241 |
Grade A, and why
image scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image preparation and T-pose generation Skill
Use this Skill when a game plan needs a single-subject concept image, a character reference cleaned for image-to-3D, or a front-facing transparent T-pose image for downstream character reconstruction. T-pose generation is an image-generation and image-editing task; it is not a separate asset category.
Scope and handoff
| Need | Route | Next step |
|---|---|---|
| Single-object concept art for reconstruction | <REPO_PATH>/models/gen_image/sdxl_turbo.py |
Review image, then use <REPO_PATH>/agent_skills/asset_qa/3d_object/SKILL.md |
| Convert an existing character image into a T-pose | <REPO_PATH>/pipeline/assets_gen/gen_tpose_image/run.py |
Use the transparent PNG as input to the selected 3D-object or motion workflow |
| Validate a generated T-pose | This Skill | Confirm pose, identity, silhouette, alpha, framing, and style before handoff |
Do not use multi-view sheets, collages, multiple characters, busy scenery, watermarks, floor shadows, or cropped limbs as input to an image-to-3D workflow. They tend to become fused geometry, baked texture, or missing body parts.
Models and pipeline
| Component | Location | Responsibility |
|---|---|---|
| Concept image model | <REPO_PATH>/models/gen_image/sdxl_turbo.py |
Fast single-object text-to-image concept art; tuned for reconstruction inputs |
| Image editor (local) | <REPO_PATH>/models/gen_image/qwen_edit_model.py |
Turns a supplied character reference into a white-background T-pose render |
| Image editor (cloud API) | <REPO_PATH>/models/gen_image/seedream_model.py |
Uses Seedream image editing as a swappable T-pose generation backend |
| Foreground extraction | <REPO_PATH>/models/tools/image_matting/rmbg_model.py or <REPO_PATH>/models/tools/image_matting/depth_anything_model.py |
Creates a foreground alpha mask |
| Task operator | <REPO_PATH>/operators/gen_tpose_image/operator.py |
Reads a task, generates the T-pose, saves artifacts and metadata |
| Runner | <REPO_PATH>/pipeline/assets_gen/gen_tpose_image/run.py |
Loads models, accepts CLI/JSONL tasks, and writes result summaries |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 225 lines · 0 tokens per session scan A 75dc2d98968e
image is a skill published in the GitHub repository OpenDCAI/GameFactory-3A (928 stars, last pushed 5d ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 2,409 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
scenario-blender-retopology
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…
scenario-maya-retopology-uv
Use when turning a dense sculpt, scan, ZBrush export or AI-generated mesh into animation-ready or game-ready topology in Maya without a mouse ("clean up this AI mesh", "retopo this character", Quad Draw, Retopologize), testing it deforms before rigging (bad elbow or wrist bend, lids popping through the eyes), or…
scenario-zbrush-expert
Use when an agent drives Maxon ZBrush 2026 for any task (sculpt in ZBrush, DynaMesh, ZRemesher, UVs, export, polypaint, posing, 3D print, clean up an AI mesh in ZBrush), when writing ZBrush Python (zbrush.commands) or ZScript, when the ZBrush bridge is not answering, a palette path or set() does nothing, a scripted…
scenario-godot-expert
Use when an agent drives Godot 4.7 on macOS or Windows for any task: headless --script jobs, --import, --check-only, command-line exports, GUT tests, windowed screenshots, the headless editor (-e) or an MCP server into a running editor; when a run hangs or fails silently, a capture is black, Godot 3 code breaks in…
scenario-godot-multiplayer
Use when a Godot 4 game goes online or co-op: host and join with ENet, WebSocket for a web build, RPCs (@rpc, rpcid, anypeer), MultiplayerSpawner and MultiplayerSynchronizer, player authority, lobbies and login, a dedicated or headless server export, lag, rubber-banding, prediction or netfox, cheating, bandwidth…
scenario-blender-hair
Use when grooming hair or fur in Blender with hair curves, such as a character hairstyle, animal fur, procedural fur in geometry nodes, or hair cards and mesh hair for games. Also covers the Essentials hair node assets (Interpolate, Clump, Curl, Frizz, Noise, Trim), density masks, bald spots, parting lines, strand…