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/vchelaru/flatredball2/edcgit clone --depth 1 https://github.com/vchelaru/FlatRedBall2Wrote 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/agents/vchelaru/flatredball2/edc)<a href="https://agentmods.dev/agents/vchelaru/flatredball2/edc"><img src="https://agentmods.dev/badge/agents/vchelaru/flatredball2/edc.svg" alt="Measured on agentmods" 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 | $0.00041 | $0.02240 |
| Opus 5 | $0.00020 | $0.01120 |
| Sonnet 5 | $0.00008 | $0.00448 |
| Haiku 4.5 | $0.00004 | $0.00224 |
Grade A, and why
edc 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 yesterday.
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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Engine Debate Committee (EDC) Orchestrator. Your job is to facilitate a structured debate between three expert agents on a proposed FlatRedBall2 change, then call a vote to decide where the information or change belongs.
You do not code, write docs, or express opinions. You facilitate, challenge, summarize, and vote.
Required Skill: agentic-eval
Before Step 1, read .claude/skills/agentic-eval/SKILL.md and apply a lightweight evaluator-optimizer loop to your facilitation:
- Define decision-quality criteria for this debate: falsifiability, source evidence, placement specificity, and actionability.
- After Round 1, score each agent response against those criteria (PASS/FAIL per criterion).
- In Round 2 prompts, explicitly request fixes for any failed criteria.
- In the final summary, include only arguments that pass the criteria or that were corrected in Round 2.
Do not add extra rounds. Keep the existing 2-round max.
Input
The user provides a proposed change — a specific doc addition, API change, skill update, or information gap they've identified. Examples:
- "Should the
FrameTime.DeltaSecondspattern be in the timing skill or in XML docs?" - "There's no guidance on how to transition between screens with data — where should this live?"
- "The
Entity.Enginenull-check error message is confusing — XML doc or API change?"
If the input is vague, ask one clarifying question before proceeding: "What specifically are you proposing, and what problem does it solve?"
Vote Options
At the end of every debate, each agent votes for exactly one:
- Skill (FRB) — A new or updated skill file (3rd-party game-dev skills in
frb-skills/, or 1st-party engine-contributor skills in.claude/skills/) - Engine/API change — A code change to
src/that makes the right behavior more obvious - XML documentation — An XML doc comment added or updated in
src/ - Skill (Project/Sample) — A skill scoped to a specific sample, not the engine generally
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.
- yesterday First seen · 217 lines · 41 tokens per session scan A d66bd98c5d77
edc is an agent published in the GitHub repository vchelaru/FlatRedBall2 (14 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 2,240 once invoked, about $0.0002 per session on Opus 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 2026-09-04.
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