Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add striderZA/OpenCodeGameStudios --skill art-generategit clone --depth 1 https://github.com/striderZA/OpenCodeGameStudiosWrote 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/striderza/opencodegamestudios/art-generate)<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/art-generate"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/art-generate/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/striderza/opencodegamestudios/art-generate"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/art-generate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high YARA Match · line 3 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
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 | $0.00057 | $0.02645 |
| Opus 5.5 | $0.00023 | $0.01058 |
| Sonnet 5.5 | $0.00011 | $0.00529 |
| Haiku 4.5 | $0.00006 | $0.00265 |
Grade A, and why
art-generate 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 — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
If no argument is provided, read design/assets/asset-manifest.md:
- If it exists: find the first target with any asset at
Status: Neededand usequestion:- Prompt: "The next unspecced target is [target]. Generate placeholder art for it?"
- Options:
[A] Yes — generate for [target]/[B] Pick a different target/[C] Stop here
- If no manifest: fail with:
"No asset manifest found. Run
/asset-spec [target]first — I need asset specs to generate art from."
Phase 0: Parse Target
Resolve the target:
- If argument matches
system:<name>→ spec atdesign/assets/specs/[name]-assets.md - If argument matches
level:<name>→ spec atdesign/assets/specs/[name]-assets.md - If argument matches
character:<name>→ spec atdesign/assets/specs/[name]-assets.md - If argument is a path → read that file directly
- If argument is a path to a .md file → treat as spec file
Fail if the spec file does not exist:
"No asset spec found at
[path]. Run/asset-spec [target]first."
Phase 1: Gather Context
Read all source material before generating anything.
Required reads:
- Asset spec: Read the resolved spec file. Extract all
ASSET-NNNentries. For each, extract: Category, Dimensions, Format, Naming, Visual Description. - Art bible: Read
design/art/art-bible.md— fail if missing:"No art bible found. Run
/art-biblefirst — I need the palette and shape language to generate art." Extract: Color System (Section 2), Shape Language (Section 3), Asset Standards (Section 8 — dimension tiers). - Asset manifest: Read
design/assets/asset-manifest.md— note which assets already have placeholders. Filter to assets withStatus: Needed.
Present context summary:
art-generate: [Target Type] — [Target Name]
- Spec: [path] — [N] assets identified
- Art bible: found — [N] palette colors, shape language: [style]
- Assets to generate: [N] (filtered from [N] total — [N] already have placeholders)
- Output: assets/source/[target]/ and assets/sprites/[target]/
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 · 322 lines · 57 tokens per session scan A c85faead6bc2
art-generate is a skill published in the GitHub repository striderZA/OpenCodeGameStudios (99 stars, last pushed 13d ago), licensed MIT. It adds 57 tokens to every session and 2,645 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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design-system
Guided, section-by-section GDD authoring for a single game system. Gathers context from existing docs, walks through each required section collaboratively, cross-references dependencies, and writes incrementally to file.
setup-engine
Configure the project's game engine and version. Pins the engine in OPENCODE.md, detects knowledge gaps, and populates engine reference docs via WebSearch when the version is beyond the LLM's training data.
gate-check
Validate readiness to advance between development phases. Produces a PASS/CONCERNS/FAIL verdict with specific blockers and required artifacts.
reverse-document
Generate design or architecture documents from existing implementation. Works backwards from code/prototypes to create missing planning docs.
estimate
Estimates task effort by analyzing complexity, dependencies, historical velocity, and risk factors. Produces a structured estimate with confidence levels.