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 team-levelgit 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/team-level)<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/team-level"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/team-level/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/team-level"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/team-level.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00039 | $0.02184 |
| Opus 5.5 | $0.00016 | $0.00874 |
| Sonnet 5.5 | $0.00008 | $0.00437 |
| Haiku 4.5 | $0.00004 | $0.00218 |
Grade A, and why
team-level 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.
This is a copy
89% identical to team-level — 162 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When this skill is invoked:
Decision Points: At each step transition, use question to present
the user with the subagent's proposals as selectable options. Write the agent's
full analysis in conversation, then capture the decision with concise labels.
The user must approve before moving to the next step.
-
Read the argument for the target level or area (e.g.,
tutorial,forest dungeon,hub town,final boss arena). -
Gather context:
- Read the game concept at
design/gdd/game-concept.md - Read game pillars at
design/gdd/game-pillars.md - Read existing level docs in
design/levels/ - Read relevant narrative docs in
design/narrative/ - Read world-building docs for the area's region/faction
- Read the game concept at
How to Delegate
Use the Task tool to spawn each team member as a subagent:
subagent_type: narrative-director— Narrative purpose, characters, emotional arcsubagent_type: world-builder— Lore context, environmental storytelling, world rulessubagent_type: level-designer— Spatial layout, pacing, encounters, navigationsubagent_type: systems-designer— Enemy compositions, loot tables, difficulty balancesubagent_type: art-director— Visual theme, color palette, lighting, asset requirementssubagent_type: accessibility-specialist— Navigation clarity, colorblind safety, cognitive loadsubagent_type: qa-tester— Test cases, boundary testing, playtest checklist
Always provide full context in each agent's prompt (game concept, pillars, existing level docs, narrative docs).
- Orchestrate the level design team in sequence:
Step 1: Narrative + Visual Direction (narrative-director + world-builder + art-director, parallel)
Spawn all three agents simultaneously — issue all three Task calls before waiting for any result.
Spawn the narrative-director agent to:
- Define the narrative purpose of this area (what story beats happen here?)
- Identify key characters, dialogue triggers, and lore elements
- Specify emotional arc (how should the player feel entering, during, leaving?)
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 · 176 lines · 39 tokens per session scan A d85eb0072c97
team-level is a skill published in the GitHub repository striderZA/OpenCodeGameStudios (99 stars, last pushed 13d ago), licensed MIT. It adds 39 tokens to every session and 2,184 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to team-level, differing in 162 lines, and is treated as a copy.
Other skills, from other repositories
professional-game-developer
Universal production game engineering skill — design, build, profile, test, and ship games across Unreal Engine 5, Unity 6 (DOTS), Godot 4.3+, Roblox (Luau), and Web/Custom engines with senior studio-grade architectural discipline. Encompasses all 42 specialized game studio job roles across 6 departments: Game Design…
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.