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/bytesagain/ai-skills/api-tester-cnnpx skills add bytesagain/ai-skills --skill api-tester-cngit clone --depth 1 https://github.com/bytesagain/ai-skillsWrote 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/skills/bytesagain/ai-skills/api-tester-cn)<a href="https://agentmods.dev/skills/bytesagain/ai-skills/api-tester-cn"><img src="https://agentmods.dev/badge/skills/bytesagain/ai-skills/api-tester-cn.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 | $0.00064 | $0.00288 |
| Opus 5 | $0.00032 | $0.00144 |
| Sonnet 5 | $0.00013 | $0.00058 |
| Haiku 4.5 | $0.00006 | $0.00029 |
Grade A, and why
Api Tester Cn — Bilingual Enhanced Edition scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- "Generate curl command for this POST request" (生成该POST请求的curl命令) The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 5d ago First seen · 29 lines · 64 tokens per session scan A ab8900949b80
Api Tester Cn — Bilingual Enhanced Edition is a skill published in the GitHub repository bytesagain/ai-skills (13 stars, last pushed 4mo ago), with no licence file. It adds 64 tokens to every session and 288 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
offer-compare-skill
Offer 对比决策器。用户同时拿到两份（或多份）offer 纠结怎么选时，扮演 Senior Career Decision Advisor：结构化对比 comp / 成长 / AI 敞口 / 公司强度 / 团队风险 / 晋升速度 / 生活方式，识别 front-loaded vs long-term upside、resume value、switch-out 难度、hidden risks，最后给一条明确、有立场、不中性的推荐（并附「你是 X 类人选 A，你是 Y 类人选 B」的分叉判定）。三步：贴两份 offer → 补 priorities & 现状 → 自动生成并打开一份 HTML Offer Decision…
offer-toolkit-skill
求职工具包。把「找岗位 → 签 offer」拆成六个独立子 skill：⓪ Job Hunt 批量发现岗位，① Job Description 解码具体 JD，② Resume 定向简历，③ BQ 准备行为面试，④ Offer Compare 对比多份 offer，⑤ Salary Negotiation 谈 package。任何求职相关请求（找工作、该不该投、改简历、准备面试、选 offer、谈薪）都从这里进，再路由到对应子 skill。关键词：求职, offer, career, job hunt, LinkedIn jobs, JD, resume, CV, behavioral interview, BQ, STAR…
bq-skill
行为面试 skill。帮求职者挖掘真实经历、用 STAR/CAR 结构化、映射能力标签、构建可复用的中英双语故事库（Story Bank）；并能接入 JD + 简历，针对具体岗位生成 Top 20 BQ 选题 + 基于真实经历的 STAR 准备模板（HTML 报告）。不是背答案，而是建立可复用的职业叙事体系，让任何行为面试题都能自然作答。关键词：behavioral question, BQ, 行为面试, STAR, 故事库, Amazon LP, 职业故事, tell me about a time, 面试准备, JD 面试题预测, top 20 题。.
linkedin-job-search-skill
LinkedIn 岗位发现与匹配排序。根据用户给的一份种子 JD 和简历，提取目标岗位画像，自动生成多组 LinkedIn Jobs 搜索，采集、去重并按证据给岗位分层，最终输出可直接投递的 shortlist。用户说‘帮我找工作’、‘在 LinkedIn 搜适合我的岗位’、‘找相似职位’、‘根据简历推荐岗位’、‘job search’、‘find jobs like this’时必须使用。只搜索和推荐，不自动投递、不代替用户登录、不绕过验证码。.
response-compression
Compresses verbose responses by removing filler and framing to save 200-400 tokens. Use when responses feel bloated or context is filling fast.
smart-sourcing
Selects optimal sources for tool calls, balancing accuracy with token cost. Use before research tasks or when deciding whether a claim needs verification.