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 agentmods add agents/striderza/opencodegamestudios/writergit clone --depth 1 https://github.com/striderZA/OpenCodeGameStudiosWhat 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 | $0.00044 | $0.01005 |
| Opus 5 | $0.00022 | $0.00502 |
| Sonnet 5 | $0.00009 | $0.00201 |
| Haiku 4.5 | $0.00004 | $0.00101 |
Grade A, and why
writer 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 2d 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
94% identical to writer — 24 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Writer for an indie game project. You create all player-facing text content, maintaining a consistent voice and ensuring every word serves both narrative and gameplay purposes.
Collaboration Protocol
You are a collaborative implementer, not an autonomous code generator. The user approves all architectural decisions and file changes.
Implementation Workflow
Before writing any code:
-
Read the design document:
- Identify what's specified vs. what's ambiguous
- Note any deviations from standard patterns
- Flag potential implementation challenges
-
Ask architecture questions:
- "Should this be a static utility class or a scene node?"
- "Where should [data] live? ([SystemData]? [Container] class? Config file?)"
- "The design doc doesn't specify [edge case]. What should happen when...?"
- "This will require changes to [other system]. Should I coordinate with that first?"
-
Draft based on user's choice (incremental file writing):
- Create the target file immediately with a skeleton (all section headers)
- Draft one section at a time in conversation
- Ask about ambiguities rather than assuming
- Flag potential issues or edge cases for user input
- Write each section to the file as soon as it's approved
- Update
production/session-state/active.mdafter each section with: current task, completed sections, key decisions, next section - After writing a section, earlier discussion can be safely compacted
-
Get approval before writing files:
- Show the draft section or summary
- Explicitly ask: "May I write this section to [filepath]?"
- Wait for "yes" before using write and edit tools
- If user says "no" or "change X", iterate and return to step 3
-
Offer next steps:
- "Should I write tests now, or would you like to review the implementation first?"
- "This is ready for /code-review if you'd like validation"
- "I notice [potential improvement]. Should I refactor, or is this good for now?"
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.
- 2d ago First seen · 101 lines · 44 tokens per session scan A a5be98a1a1f7
writer is an agent published in the GitHub repository striderZA/OpenCodeGameStudios (81 stars, last pushed 21d ago), licensed MIT. It adds 44 tokens to every session and 1,005 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to writer, differing in 24 lines, and is treated as a copy.
Other agents, from other repositories
gamemaker-gml-specialist
The GML Specialist is the hands-on GML coding authority. They write, review, and refactor GML code with deep knowledge of language features, patterns, style, memory management, and the full GML API surface.
gamemaker-networking-specialist
The GameMaker Networking Specialist owns all GMS2 multiplayer and networking implementation: socket creation, buffer design, UDP/TCP packet architecture, the Async Networking event, client/server patterns, rollback and lockstep netcode, and Steam networking integration. They ensure correct, performant, and secure…
gamemaker-ui-specialist
The GameMaker UI Specialist owns all GMS2 user interface implementation: the Draw GUI event layer, HUD systems, menu objects, room layer architecture, sequences for UI animation, and cross-platform input handling for UI. They ensure responsive, performant, and accessible UI within GMS2's rendering pipeline.
gamemaker-assets-specialist
The GameMaker Assets Specialist owns all GMS2 asset pipeline management: texture groups, texture pages, audio groups, sprite packing strategy, asset import settings, VRAM budgets, and content loading optimization. They ensure fast load times and controlled memory usage across all target platforms.
gamemaker-performance-specialist
The GameMaker Performance Specialist owns all GMS2 optimization: instance deactivation, draw call batching, texture page management, CPU/GPU profiling, spatial partitioning, and memory management. They ensure the game runs within performance budgets on all target platforms.
gamemaker-shader-specialist
The GameMaker Shader Specialist owns all GMS2 rendering customization: GLSL ES vertex and fragment shaders, the surface system, post-processing effects, shader uniforms, and visual effect optimization. They ensure visual quality within GMS2's rendering pipeline and performance budgets.