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/lion-1209/coderio/namingnpx skills add Lion-1209/coderio --skill naminggit clone --depth 1 https://github.com/Lion-1209/coderioWhat 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 | $0.00025 | $0.01406 |
| Opus 5 | $0.00013 | $0.00703 |
| Sonnet 5 | $0.00005 | $0.00281 |
| Haiku 4.5 | $0.00003 | $0.00141 |
Grade A, and why
naming 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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- naming — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Naming
概述
名字要回答"它是什么/它做什么"，而不是"它在哪/什么类型"。好名字让代码自解释，坏名字逼读者来回跳转确认含义。
何时使用
- 写代码时卡在取某个名字上
- 觉得现有名字不准、误导，想改
- 设计 API/接口，定资源和字段名
- 想统一一个模块的命名风格
不该用：已在用团队既定规范（遵循即可）；纯格式问题（用 linter）。
核心内容
取名前先搞清四件事
套快速规则前先回答这四个问题，否则会在错的对象上取名。前两个是定性（决定名字的形态），后两个是收口（决定用哪个词）：
- 它是对象还是动作？ 数据/状态/实体 → 名词；行为/操作 → 动词。（这是最根本的一刀，定错了后面全错。）
- 一个职责还是两个？ 像"转换 + 校验"这种复合，先问该不该拆成两个名字——能独立复用/测试就拆，再各自取名。别把两件事塞进一个名字（如
parseAndValidateCsv不如parseCsv+validateRecords）。 - 信息够不够？ 用户只甩"flag 叫啥"不给语义时，先反问"它具体表示什么状态"，别凭猜取名。
- 有歧义吗？ 同名异义/异名同义（项目里既有
login又有auth），先定以谁为基准——通常以领域模型/核心资源名为准，全项目统一。
问题 1 的答案同时决定了下面「快速规则」第一条该走名词还是动词那一支。
快速规则
- 函数/方法用动词：
fetchUser、validateEmail - 变量/属性用名词：
user、emailAddress - 布尔用 is/has/can/should：
isLoggedIn、hasPermission - 避免否定：
isEmpty优于isNotEmpty - 避免无意义词：名词
data/info/helper/manager/util，动词process/handle/do——都说不清做啥 - 少缩写：除非领域通用（
id、url、http，以及csv、json、xml这类格式名）；usr、cfg、tmp别用 - 范围越窄越具体：模块内可简短，全局/API 要自解释
- 一致：同一概念全项目用同一个词（别
user/account/member混用）
before / after
| 不好 | 好 | 原因 |
|---|---|---|
processData(d) |
parseCsvToRecords(text) |
说清做什么、入参是啥 |
flag |
isLoggedIn |
布尔用 is，表意明确 |
userList |
users |
复数即集合，去冗余类型后缀 |
strName |
name |
去掉匈牙利记法前缀 |
handleStuff() |
sendInvoice() |
动词具体，不抽象 |
UserInfoManager |
UserProfile |
去掉无意义 Manager |
转换类动词按数据流向选
"把 A 变成 B"这类操作最容易被塞进万能的 process/handle，丢掉数据流向信息。按输入→输出的形态变化选最贴切的动词：
| 动词 | 数据流向 | 例子 |
|---|---|---|
parse |
文本 → 结构化对象 | parseCsv(text) → Record[] |
serialize |
结构 → 文本/字节 | serializeOrder(order) → JSON 字符串 |
convert / transform |
结构 → 结构（同层级换形态） | convertMsToSeconds、transformUserToDto |
format |
结构 → 展示用文本 | formatDate(date) → "2026-06-22" |
map / reduce |
集合 → 集合/标量 | mapToIds(users)、reduceToTotal(items) |
选名时问自己：**读者看到动词，能不能猜出输入和输出分别是什么形态？**猜不出（如 processData）就换。
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.
- 3d ago First seen · 86 lines · 25 tokens per session scan A 6ba13cfb6f6f
naming is a skill published in the GitHub repository Lion-1209/coderio (9 stars, last pushed 5d ago), licensed MIT. It adds 25 tokens to every session and 1,406 once invoked, about $0.0001 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.
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