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 commands/qingzhoupro/afsim-skill/afsimgit clone --depth 1 https://github.com/qingzhoupro/afsim-skillWhat 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 | $0.00000 | $0.00588 |
| Opus 5 | $0.00000 | $0.00294 |
| Sonnet 5 | $0.00000 | $0.00118 |
| Haiku 4.5 | $0.00000 | $0.00059 |
Grade A, and why
afsim 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.
What it actually says
/afsim — 主命令入口
显示 AFSIM-SKILL 命令列表和快速参考。
命令列表
| 命令 | 功能 |
|---|---|
/afsim-auto |
全自动代码生成，无需确认直接输出 |
/afsim-auto step |
半自动，逐模块确认，适合学习/复杂场景 |
/afsim-learn <文档路径或内容> |
解析 MD/PDF 文档，融入 skill |
/afsim-debug |
报错处理，粘贴 Warlock/Wizard 报错信息获取修正 |
黄金法则
不要凭空自造 AFSIM 语法，要基于验证过的模板和官方 Demo 输出！
快速开始
新建场景（推荐用 /afsim-auto step）
/afsim-auto step
按提示输入需求，例如："做一个红方萨姆防空系统对抗蓝方战机的场景"
AI 会逐模块确认：platform_type → sensor → weapon → route → processor，每步等待你的确认。
快速生成（用 /afsim-auto）
/afsim-auto 做一个红方萨姆防空系统对抗蓝方战机的场景
AI 自动完成全流程，直接输出代码。
学习文档（用 /afsim-learn）
/afsim-learn 将这个.md文件解析进skill：f:\docs\afsim_传感器.md
AI 自动解析文档中的 AFSIM 语法要点，存入 refs/learn/ 对应分类。
报错处理（用 /afsim-debug）
/afsim-debug
粘贴 Warlock/Wizard 的报错信息，AI 会匹配 errors-ref 并激活相关教训，给出修正方案。
快速参考
AFSIM 代码的核心块结构：
radar_signature NAME
constant 10 m^2
end_radar_signature
platform_type NAME WSF_PLATFORM
side blue
icon F-18E
radar_signature NAME
mover WSF_AIR_MOVER
debug
end_mover
end_platform_type
platform instance_name TYPE
side blue
route
position 30:00:00n 120:00:00e altitude 10000 ft msl
speed 300 kts
end_route
end_platform
random_seed 1
end_time 30 sec
完整模板见
refs/quick-ref.mdDemo 速查见refs/demos-index.md
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 · 86 lines · 0 tokens per session scan A 4a4c232a241e
afsim is a command published in the GitHub repository qingzhoupro/afsim-skill (51 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 588 tokens. 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.