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 skills/davidyichengwei/agentic-engineering-framework/std-gonpx skills add davidYichengWei/agentic-engineering-framework --skill std-gogit clone --depth 1 https://github.com/davidYichengWei/agentic-engineering-frameworkWhat 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 | $0.00032 | $0.00532 |
| Opus 5 | $0.00016 | $0.00266 |
| Sonnet 5 | $0.00006 | $0.00106 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
std-go 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
Go 编码规范
基于 Google Golang 代码规范,结合实际工程经验进行了调整和补充。
规范等级定义
| 等级 | 定义 |
|---|---|
| 必须(Mandatory) | 用户必须采用,代码扫描工具应将其视为错误 |
| 推荐(Preferable) | 用户理应采用,但如有特殊情况可以不采用 |
| 可选(Optional) | 用户可参考,自行决定是否采用 |
核心规则速查
| 类别 | 必须遵守 |
|---|---|
| 格式化 | 使用 gofmt 格式化代码 |
| import | 使用 goimports,禁止相对路径导入,标准包在最上 |
| 错误处理 | 必须处理 error,error 必须是最后一个返回值 |
| panic | 禁止用于一般错误处理,仅用于不变量断言 |
| 命名 | 驼峰式,包名小写无下划线,文件名小写下划线分隔 |
| 注释 | 导出名字必须有文档注释,格式 // Name 描述 |
| switch | 必须有 default 分支 |
| goto | 业务代码禁止使用 |
| 嵌套 | 深度不超过 4 层 |
| 代码行数 | 文件 ≤ 800 行,函数 ≤ 80 行 |
| 依赖管理 | 使用 go modules |
完整规范
详见 reference/full-standards.md,包含:
- 代码风格(格式化、换行、括号空格、import)
- 错误处理(error、panic、recover)
- 注释规范(包、结构体、方法、变量、常量、类型)
- 命名规范(包、文件、结构体、接口、变量、常量、函数)
- 控制结构(if、for、range、switch、return、goto)
- 函数规范(参数、defer、接收器、代码行数、嵌套、变量声明、魔法数字)
- 依赖管理和应用服务规范
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 44 lines · 32 tokens per session scan A 9fe1a4e175c5
std-go is a skill published in the GitHub repository davidYichengWei/agentic-engineering-framework (159 stars, last pushed 5mo ago), licensed MIT. It adds 32 tokens to every session and 532 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.