Imported from majiayu000/claude-skill-registry (skills/other/game-sprite-pipeline/SKILL.md). Install upstream with npx skills add majiayu000/claude-skill-registry --skill game-sprite-pipeline. Copyright stays with the author.

Game Sprite Pipeline

Local-first AI sprite generation. One skill, four modes behind --mode:

• portrait — single full-body character PNG (road-to-aew wrestlers, card-game characters).
• portrait-loop — 2×2 = 4-frame subtle idle (breathing + blink) at 200ms/frame in ONE Codex call. Animated portraits without re-prompting new poses.
• spritesheet — animated multi-frame grid with connected-components detection, ground-line anchor alignment, and Phaser atlas output.
• spritesheet --per-row — row-strip generation: each animation state generated as a separate strip with layout guide grounding and identity lock, then composited into a final sheet. Eliminates cross-row contamination and reduces retry scope from whole-sheet to single-row.

Backend chain (per ADR-198): Codex CLI imagegen is the default when installed and authed. When Codex is unavailable AND GEMINI_API_KEY (or GOOGLE_API_KEY) is set, the skill falls back to Nano Banana via nano-banana-builder's scripts. When neither is available, the skill fails loud with BackendUnavailableError listing both fix paths. Both paths use keys the user already holds — there is no third-party billing the toolkit hides. Reference implementation of the "Local-First, Deterministic Systems Over External APIs" principle in docs/PHILOSOPHY.md (user-owned-key clause).

When to use

Portrait is the road-to-aew immediate need; spritesheet is the forward-looking capability. Both share one backbone (prompt scaffolding, backend dispatch, bg removal, validation).

Reference Loading Table

Load greedily when a signal matches — references are only read on demand, so the cost is paid once per execution, not once per routing decision.

Portrait-mode pipeline (5 phases)

End-to-end: python3 scripts/portrait_pipeline.py --prompt "<desc>" --style <preset> [--target road-to-aew].

Portrait-loop-mode pipeline (5 phases)

End-to-end: python3 scripts/portrait_pipeline.py --mode portrait-loop --display-name "..." --description "..." --style <preset>.

The loop must be SUBTLE: viewers should barely notice the animation (just feels alive). New poses defeat the purpose — that's spritesheet mode. See references/prompt-rules.md for the loop prompt template.

Spritesheet-mode pipeline (8 phases)

End-to-end: python3 scripts/sprite_pipeline.py --prompt "<desc>" --grid <CxR> --cell-size 256.

Per-row generation mode (--per-row)

Row-strip generation eliminates the monolithic-sheet failure mode. Instead of one image-generation call for the entire sheet (where frames drift, cross-row contamination occurs, and the slicer misroutes content), each animation row is generated as a separate strip image.

How it works:

1. Phase A generates a canonical base character image (identity lock anchor). All subsequent rows receive this base as --reference with "match silhouette, face, materials, palette, props exactly" -- prevents cross-row palette shifts, proportion changes, accessory drift.
2. sprite_canvas.py make-layout-guide generates per-row reference PNGs (frame boundaries with numbered cells on transparent background), passed as --reference alongside the canonical base to prevent frame drift at generation time.
3. Each row gets its own prompt with state-specific action/pose + VFX containment rules (see references/vfx-containment.md).
4. Strips are composited into the final sheet after all rows pass QA.

Retry granularity: re-generate a single failed row, not the whole sheet. Cost drops from O(sheet) to O(row).

End-to-end: python3 scripts/sprite_pipeline.py --prompt "<desc>" --preset fighter --per-row.

Animation presets (--preset)

Named animation presets replace raw --grid CxR with semantic state definitions, default frame counts, and per-frame timing.

--preset expands to --grid + per-row metadata + timing arrays. Users say --preset rpg-character instead of computing grid dimensions manually.

Video-to-sprite pipeline

New input modality: extract spritesheet rows from video clips when text prompting fails for complex animations (multi-hit combos, spell effects, motion-captured references).

Wire via: --video-rows "0:idle:/path/to/idle.mp4,4:jump:/path/to/jump.mp4" — row index, state name, video path.

Dependencies: FFmpeg (already available), Pillow (already used). No new dependencies.

Row job manifest

row_job_status.py tracks per-row generation status for subagent orchestration.

Subagent boundary rules (see references/subagent-delegation.md):

• Subagent: generates one row strip image, returns path + QA assessment.
• Parent: owns manifest, identity verification, compositing, finalization, packaging.
• Subagents never edit manifests or finalize — single point of control stays with parent.

QA artifacts (--qa-artifacts)

Human-inspectable QA outputs generated alongside verifier JSON when --qa-artifacts is passed.

Script: qa_artifacts.py generates all three artifact types after assembly.

Per-frame variable timing

Presets include per-frame millisecond timing arrays instead of uniform timing.

Example (idle): [280, 110, 110, 140, 140, 320] ms — longer hold on first/last frame creates natural breathing rhythm.

Output integration:

• GIF/WebP output uses per-frame durations via Pillow's duration parameter.
• Phaser atlas JSON includes frameDurations array and animationTimings map.
• Custom timing override via --timing-json <path> for fine-tuning.

Backend (Codex default with Nano Banana fallback, per ADR-198)

Per generation call, evaluated in order:

1. codex in PATH and codex --version exits 0 → use Codex CLI imagegen. Codex CLI 0.125+ no longer exposes --output-image/--aspect-ratio/--reference/--seed as direct flags; image generation goes through the agent's internal image_gen tool, invoked from prompt text. Canonical invocation: codex exec --dangerously-bypass-approvals-and-sandbox --skip-git-repo-check [-i <ref>... --] "<wrapped prompt>". The wrapped prompt instructs the agent to call image_gen and save to an absolute path; aspect ratio, seed, and reference semantics are encoded into the prompt text. Reference list (when used) MUST be terminated with -- before the positional prompt or it consumes the prompt as another image filename. Subprocess timeout: 360s.
2. Else if GEMINI_API_KEY or GOOGLE_API_KEY is set → fall back to Nano Banana via nano-banana-builder's scripts (scripts/nano-banana-generate.py with-reference for reference-guided, batch for multi-variant). The skill never imports the Gemini SDK directly — composition through the existing skill is the contract.
3. Else fail loudly with BackendUnavailableError listing BOTH fix paths:

   BackendUnavailableError: No image-generation backend available.
   
   Fix path 1 (Codex CLI, recommended):
     Install Codex CLI and run `codex auth` to authenticate against your existing subscription.
   
   Fix path 2 (Nano Banana fallback):
     Set GEMINI_API_KEY (or GOOGLE_API_KEY) in your environment to enable the Nano Banana fallback.
   

Both paths use keys the user already holds (Codex subscription, Gemini API key). There is no third-party billing the toolkit hides. The skill never calls api.openai.com directly, remove.bg, or any service the user did not authorize. See references/backend-chain.md for the locked-in invocation contract and failure modes.

--max-frames: pack the canvas

One Codex imagegen call produces ONE image. To get N frames, pack as many cells as possible into that one image rather than firing N calls.

--max-frames (on sprite_canvas.py make-template and sprite_pipeline.py) auto-computes the largest square grid that fits --max-canvas (default 1024x1024) at the given --cell-size:

# 4x4 = 16 frames at 256px on a 1024 canvas (default)
python3 sprite_pipeline.py --description "knight walk cycle" \
    --style snes-16bit-jrpg --cell-size 256 --max-frames --action walking

# 8x8 = 64 frames at 128px on a 1024 canvas
python3 sprite_pipeline.py --description "tiny adventurer, attack cycle" \
    --style nes-8bit --cell-size 128 --max-frames --action attack-punch

# 16x16 = 256 frames at 64px on a 1024 canvas (extreme density)
python3 sprite_pipeline.py --description "GB-era hero, 4-direction walk" \
    --style gameboy-4color --cell-size 64 --max-frames --action walking

--max-frames overrides --grid; the chosen grid is logged to stderr. See references/grid-shapes.md for the cell-size → max-grid → total-frames table at canvas sizes 1024, 1536, and 2048.

Dimension and cell policy

Portrait mode — variable output, validated after trim:

• width 350-850, height 900-1100, aspect 1:1.5 to 1:2.5 (h:w).
• --force-dimensions skips the gate (emergency only; logged loudly).

Spritesheet mode — fixed cells:

• cell-size in {64, 128, 192, 256, 384, 512}; default 256.
• grid CxR via --grid; total canvas <= 2048x2048.
• --grid 4xR or --grid 8xR triggers per-direction strip output.

See references/grid-shapes.md for direction-to-row conventions.

Auto-curation (deterministic)

Default. Applied when --variants N > 1.

1. Fewest edge-touch frames wins (sprite touching canvas edge = clipping).
2. Tiebreak: smallest shared-scale variance (visually consistent height across frames).
3. Tiebreak: lowest seed number (reproducible tie resolution).

--curate writes a contact sheet and opens a manual review gate. Off by default; interactive gates block automation.

Shared constraints

• User-owned keys only. Codex CLI (default) and Nano Banana via GEMINI_API_KEY/GOOGLE_API_KEY (fallback) are the two authorized backends — both billed under the user's existing accounts. The skill never calls api.openai.com directly, remove.bg, or any service the user did not authorize. See ADR-198 and the user-owned-key clause in docs/PHILOSOPHY.md.
• Magenta background (#FF00FF) is the chroma-key default because it never appears in realistic character skin or wrestling gear. Backend prompts include explicit "solid magenta background" instruction; post-processing validates the dominant corner color.
• Fixed seed per run for reproducibility. Re-running with the same --seed should produce identical output given identical backend output (best-effort: Codex CLI does not currently expose a public seed flag, so the seed travels in the prompt body as a comment).

Verification

Before shipping any change to this skill, run:

cd /home/feedgen/vexjoy-agent
python3 scripts/generate-skill-index.py
python3 scripts/validate-references.py --check-do-framing
ruff check . --config pyproject.toml
ruff format --check . --config pyproject.toml

Plus the two smoke tests:

# Portrait (no backend required in dry-run)
python3 skills/game/game-sprite-pipeline/scripts/portrait_pipeline.py \
    --prompt "veteran wrestler, indie circuit, 35yo, scarred face, leather jacket" \
    --style slay-the-spire-painted --target road-to-aew --dry-run

# Spritesheet (no backend required in dry-run; --allow-frame-duplication
# because the synthetic fixture has 4 near-identical figures that trip the
# verify_frames_distinct gate by construction at the new 70% threshold;
# see "Verifier gates" below). Default-on verify; exits 0 on success,
# 2 on gate failure, 3 on --no-verify (ADR-207 Rule 4).
python3 skills/game/game-sprite-pipeline/scripts/sprite_pipeline.py \
    --prompt "wrestler walk cycle, 4 frames" \
    --grid 4x1 --cell-size 256 --dry-run --allow-frame-duplication

Both dry-run modes skip the backend call, generate a synthetic fixture, and exercise every post-processing phase. Pass criteria: exit 0, expected output files present, dimension gates satisfied.

Verifier gates (default-on, ADR-199)

Both pipelines run a verifier suite as the LAST step (after assemble). Default-on; opt out with --no-verify.

Per-mode gate selection:

Output JSON shape on stdout (last thing the pipeline prints before exit):

{
  "passed": false,
  "verifier_verdict": "FAIL",
  "gates_run": ["verify_no_magenta", "verify_grid_alignment", ...],
  "failures": [{"check": "verify_no_magenta", "file": "...", "details": {...}}],
  "backends_available": {"codex": true, "nano_banana": true},
  "elapsed_seconds": 0.21
}

verifier_verdict (ADR-207 Rule 2) is the contracted consumer-facing field. Manifest writers, orchestrators, and downstream classifiers MUST derive their own status fields from this string; the toolkit's write_manifest_record writer asserts at write time that verifier_verdict == "PASS" implies an empty verifier_failures list (and vice versa).

Exit codes:

• 0: passed: true (or --no-verify for portrait / portrait-loop modes).
• 2: at least one gate failed (distinct from generic pipeline error rc=1 so CI can branch on "verifier said no" vs "the pipeline blew up").
• 3: --no-verify was passed in spritesheet mode (ADR-207 Rule 4 — VERIFIER_SKIPPED_EXIT_CODE). Orchestrators that explicitly want to skip spritesheet verification must explicitly accept exit code 3.

Logging (ADR-202)

Both pipelines emit diagnostic logs via stdlib logging on stderr. Verifier JSON and other structured machine-readable output stays on stdout. Logger name pattern: sprite-pipeline.<module> (e.g., sprite-pipeline.sprite_pipeline, sprite-pipeline.sprite_bg). Default level: INFO.

Stream contract: stdout carries structured output (verifier JSON, generated paths); stderr carries diagnostic logs. Redirect them independently (e.g., python3 sprite_pipeline.py ... 1>out.json 2>logs.txt).

Error handling

Error: "BackendUnavailableError: No image-generation backend available"

• Cause: Neither codex CLI nor GEMINI_API_KEY/GOOGLE_API_KEY is available.
• Solution: Install Codex CLI (npm install -g @openai/codex or per-OS) and run codex auth, OR set GEMINI_API_KEY (or GOOGLE_API_KEY) in your environment to use the Nano Banana fallback. Both paths use keys the user already holds; pick whichever is available. Never set OPENAI_API_KEY for this skill — direct OpenAI calls are not an authorized path.

Error: "Aspect ratio X outside allowed range [1:1.5, 1:2.5]"

• Cause: Character rendered too wide (crouched pose) or too tall (full-extension jump pose).
• Solution: Re-generate with a neutral standing prompt. If the character must have an atypical pose, add --force-dimensions (logs loudly, should not become routine).

Error: "Frame count mismatch: detected 6 components, grid expected 8"

• Cause: Connected-components merged neighboring frames, or small fragments were filtered.
• Solution: Increase cell-size (gives more separation gap), re-generate, or use --chroma-threshold to tighten the bg mask. See references/frame-detection.md.

Error: "Codex CLI grid-template input not supported"

• Cause: Codex imagegen may not consume a magenta grid canvas as a structural input.
• Solution: Skill auto-falls-back to per-frame generation + Pillow compositing. Slower but deterministic.

Error: "rembg not installed"

• Cause: --bg-mode rembg requested without the opt-in dependency.
• Solution: pip install rembg onnxruntime (~200MB ONNX model). Or re-run with default magenta chroma key.

Error: "road-to-aew directory not found at ~/road-to-aew"

• Cause: --target road-to-aew resolves to a path that does not exist.
• Solution: Pass --target-dir <explicit-path> or clone the repo to ~/road-to-aew. The deploy step refuses to guess.

Failure Patterns

Failure mode: Codex regeneration as a post-processing fix

What it looks like: A verifier flags a blank cell, clipped fire, missing silhouette, or any other final-asset defect. The reflex is to re-run codex exec to redraw the raw with a different prompt or seed. STOP.

Why wrong: Codex generation is treated as ground truth. The raw PNG in <your-output-dir>/raw/<slug>.png is what Codex painted, and it is almost always correct. If the final-sheet shows blank cells, clipped effects, or missing silhouettes, the bug is in one of the post-processing steps:

• slice_grid_cells derived the wrong pitch (raw_size / grid math) and cut the cell at the wrong place
• slice_with_content_awareness claimed a component to the wrong cell (centroid mapping bug)
• The despill chain (chroma_pass2_edge_flood, kill_pink_fringe, neutralize_interior_magenta_spill) ate the silhouette
• The mass-centroid anchor pinned the wrong body part to the ground line
• The LANCZOS resize between magenta padding and content created pink fringe

The user's framing: "the codex generation has never failed, it is working perfectly, the rest has failed."

Do instead: Open the raw and the final side-by-side. Confirm the raw has the content (it almost always does). Trace which post-processing step lost it. Specifically for boundary clipping (asset 27 dragon flame, asset 30 plasma trail): set has_effects: True and/or content_aware_extraction: True in the spec to use slice_with_content_awareness, which expands cell windows to recover content extending past conceptual cell boundaries.

Caveat (ADR-207 RC-1, dense-grid downgrade): on dense grids (cols * rows >= 16 AND both dims >= 4 — i.e. 4x4 and denser), the slicer dispatch in sprite_pipeline.py and cmd_extract_frames silently downgrades --content-aware-extraction (and the spec's content_aware_extraction / has_effects slicer leg) to strict-pitch with a WARNING log because content-aware routing on Codex's fractional-pitch raws drops cells via centroid drift. To opt INTO content-aware on a dense grid for genuine sparse effects assets, also pass --effects-asset (orchestrator-side) or set effects_asset: True (spec-side). Character grids with arms touching cell edges should stay on the strict slicer and rely on verify_raw_vs_final_cell_parity to flag genuine slicing bugs.

See references/error-catalog.md for the full diagnostic procedure.

Failure mode: Calling a third-party paid API the user did not authorize

What it looks like: Adding a try/except that falls back from Codex CLI → api.openai.com direct / remove.bg / any service whose billing relationship the user did not establish.

Why wrong: The user-owned-key clause (PHILOSOPHY.md, ADR-198) authorizes fallbacks gated on environment variables the user explicitly set — Codex's auth and GEMINI_API_KEY/GOOGLE_API_KEY for Nano Banana qualify because the user holds the keys. A fallback that hits a service the toolkit pays for, or that silently charges a card the user never connected, does not. That's the failure mode the Local-First principle exists to prevent.

Do instead: Stop at the two authorized backends (Codex CLI, then Nano Banana via user-set Gemini key). When neither is available, raise BackendUnavailableError with both fix paths in the message. Adding a third backend requires a new env-var-gated path AND an ADR amendment — never a silent runtime fallback.

Failure mode: Naive grid-math frame cropping

What it looks like: frame = sheet.crop((col*CELL, row*CELL, (col+1)*CELL, (row+1)*CELL)) for every cell.

Why wrong: Generated frames drift within their cells (the model does not respect grid boundaries precisely). Naive cropping captures neighbor-cell pixels and truncates the current sprite.

Do instead: Use connected-components clustering (flood-fill from non-magenta pixels, bound each cluster by its actual pixel extent). See references/frame-detection.md.

Failure mode: Trusting the backend's alpha channel

What it looks like: Prompting "transparent background" and consuming the output PNG directly.

Why wrong: Both Codex CLI and Nano Banana produce backgrounds that are nominally transparent but often have magenta/white/gray fringing, full-opacity backgrounds, or inconsistent alpha. Downstream consumers get dirty assets.

Do instead: Always post-process: prompt for a known chroma color (magenta #FF00FF), then run local bg removal. Two-pass flood fill handles feathering. references/bg-removal-local.md has the algorithm.

Failure mode: Interactive curation as the default

What it looks like: Every pipeline run opens a contact-sheet viewer and waits for user confirmation.

Why wrong: Blocks automation (batch generation of 50 wrestlers), adds cognitive load, and prevents reproducibility. The user is not always at the keyboard.

Do instead: Deterministic auto-curation is the default (rank by edge-touches → scale variance → seed). Expose --curate for cases where the automated pick is visibly wrong. Reproducibility matters more than picking the single prettiest variant.

Reference files

• references/style-presets.md — full catalog of 9 era/hardware presets, prompt fragments, --style custom slot.
• references/wrestler-archetypes.md — 9 color archetypes, 10 gimmick types, tier modifiers (Act 1/2/3).
• references/grid-shapes.md — cell-size table, grid validation, direction-to-row mapping.
• references/prompt-rules.md — ART_STYLE, CHAR_STYLE, GRID_RULES slot content; negative prompts.
• references/backend-chain.md — Codex CLI invocation pattern, auth checks, failure modes.
• references/frame-detection.md — connected-components algorithm, minimum-separation gap, component filter.
• references/anchor-alignment.md — shared-scale percentile, bottom-anchor math, horizontal centering.
• references/bg-removal-local.md — two-pass chroma, rembg opt-in, failure modes.
• references/output-formats.md — PNG / GIF / WebP / atlas JSON / strips matrix per mode.
• references/error-catalog.md — error message → cause → fix, per phase.
• references/road-to-aew-integration.md — snake_case naming, deploy paths, manifest regen.
• references/subagent-delegation.md — subagent boundary rules: who generates, who composes, who finalizes.
• references/vfx-containment.md — VFX containment ruleset: allowed/forbidden effects, per-state rules.

Demo idempotency

Demo orchestrators (e.g. <your-output-dir>/generate.py) should be idempotent: running them again on a partial output skips assets whose assets/<slug>/final.png (or final-sheet.png) AND meta.json already exist. This saves ~30-60s per asset of Codex CLI time when iterating. The pattern:

def _is_done(asset_dir: Path) -> bool:
    if not (asset_dir / "meta.json").exists():
        return False
    if (asset_dir / "final.png").exists() or (asset_dir / "final-sheet.png").exists():
        return True
    return False

def run_one(spec, force=False):
    if not force and _is_done(asset_dir):
        return existing_meta  # log "skipping" + return
    ...

Provide --force to override (re-run all) and --force-slug <prefix> to re-run a specific asset. Document the behavior in the orchestrator's docstring so future maintainers don't accidentally regenerate everything.

Related skills

• phaser-gamedev — downstream consumer of spritesheet output (atlas JSON with frameDurations and animationTimings).
• threejs-builder — may consume portrait output for 3D card framing.
• game-asset-generator — sibling umbrella for 3D models / textures / matrix-driven pixel art. Its references/pixel-art-sprites.md redirects AI-driven sprite work here.
• game-pipeline — parent lifecycle orchestrator; slot this skill under its ASSETS phase when building a new game.
• motion-pipeline — CPU-only motion data processing; can provide BVH-derived reference frames for video-to-sprite extraction.