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 rules/visiontw/godot-ai-harness/phase-execution-checklistgit clone --depth 1 https://github.com/visionTw/godot-ai-harnessWrote 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/rules/visiontw/godot-ai-harness/phase-execution-checklist)<a href="https://agentmods.dev/rules/visiontw/godot-ai-harness/phase-execution-checklist"><img src="https://agentmods.dev/badge/rules/visiontw/godot-ai-harness/phase-execution-checklist.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 | $0.00337 | $0.00337 |
| Opus 5 | $0.00169 | $0.00169 |
| Sonnet 5 | $0.00067 | $0.00067 |
| Haiku 4.5 | $0.00034 | $0.00034 |
Grade A, and why
phase-execution-checklist 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 5d 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.
What it actually says
Phase Execution Checklist
任务开始前（必做）
- 确认当前目标 Phase，并读取：
docs/phases/phase-*/feature_plan.mddocs/phases/phase-*/test_cases.mddocs/test/phases/phase-*/automation_plan.md
- 明确本次任务范围：仅实现当前 Phase 目标，不跨阶段扩展。
- 若发现需求变更，先更新
docs/再实施代码。
开发过程中（必做）
- 功能实现对齐阶段功能点编号（如
F3-01）。 - 保留可验证证据：日志、截图、测试记录路径。
- 涉及联机同步修改时，必须补对应回归测试计划。
提交前（必做）
- 至少完成当前改动对应的 smoke 检查。
- 对关键路径执行阶段测试用例（引用
TC-P*-*）。 - 将结果回写到对应
development_log.md。 - 检查文档索引是否需要更新（
docs/README.md）。
阶段结束门禁（Go / No-Go）
- 当前 Phase 的验收标准全部满足才可进入下一 Phase。
- 关键阻断问题（联机不同步、数据破坏、崩溃）必须为 0。
- 若门禁未通过，优先修复并更新文档记录，不推进下一阶段。
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.
- 5d ago First seen · 35 lines · 337 tokens per session scan A 382690efd20e
phase-execution-checklist is a cursor rule published in the GitHub repository visionTw/godot-ai-harness (2 stars, last pushed 18d ago), licensed MIT. It adds 337 tokens to every session, about $0.0017 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 2026-08-31.
Other cursor rules, from other repositories
08-client-server
IF 判断当前环境是否为客户端 → FabricLoader.getInstance().getEnvironmentType() == EnvType.CLIENT → World.isClient（Yarn 字段；yarn 1.14.4 World.mapping）。不要用 MCP/Forge 的 isRemote.
07-datagen
IF 生成物品/方块模型 JSON → 手动编写 JSON 在 src/main/resources/assets/{modid}/models/.
meta-quest-agentic-tools
Use Meta Quest Agentic Tools for Meta Quest and Horizon OS samples.
narrative-writing
游戏叙事写作助手行为约束（game-narrative-mcp）.
meta-quest-agentic-tools
Use Meta Quest Agentic Tools for Meta Quest and Horizon OS samples.
visual-and-observational-rules
Defines the visual aspects of the game and how the player observes the world. This includes map color-coding, screen effects, and the overall simulation style.