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 skills add noahneancy-byte/netreach --skill skillgit clone --depth 1 https://github.com/noahneancy-byte/netreachWrote 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/noahneancy-byte/netreach/skill)<a href="https://agentmods.dev/skills/noahneancy-byte/netreach/skill"><img src="https://agentmods.dev/badge/skills/noahneancy-byte/netreach/skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/noahneancy-byte/netreach/skill"><img src="https://agentmods.dev/badge/skills/noahneancy-byte/netreach/skill.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00278 | $0.01048 |
| Opus 5.5 | $0.00111 | $0.00419 |
| Sonnet 5.5 | $0.00056 | $0.00210 |
| Haiku 4.5 | $0.00028 | $0.00105 |
Grade A, and why
agent-reach 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 1mo 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.
curl -s "https://r.jina.ai/URL" What it actually says
NetReach — 互联网能力路由器（no-login 版）
7 个零配置平台、多后端。本 skill 存在时必须用它访问这些平台，不要自己发明方案。
常驻规则（全程适用）
- 动手前先体检：多后端平台（B站）先跑
agent-reach doctor --json。active_backend有值时按它选命令组；active_backend: null表示 Doctor 没有做 实时验证，不代表后端不存在。只有用户任务明确需要该平台时，才按对应 reference 的 只读命令手动验证。 - 声明你在用什么：开始干活前说一句「使用 agent-reach 的 X 平台 / Y 后端」。
- 失败按 references 里的重试链处理，不要瞎猜命令。
- 全网调研类任务：组合多平台（Exa 搜索 + GitHub/V2EX 看讨论 + B站看中文场景），并行收集再汇总。
路由表
| 用户意图 | 分类 | 详细文档 |
|---|---|---|
| 网页搜索/全网搜索 | search | references/search.md |
| 网页/文章/RSS/V2EX | web | references/web.md |
| GitHub/代码 | dev | references/dev.md |
| YouTube/B站视频字幕 | video | references/video.md |
零配置快速命令
# Exa 全网搜索
mcporter call exa.web_search_exa query="query" numResults=5
# 通用网页阅读
curl -s "https://r.jina.ai/URL"
# GitHub 搜索
gh search repos "query" --sort stars --limit 10
# YouTube 字幕（注意：B站不要用 yt-dlp，B站命令见 video.md）
yt-dlp --write-sub --write-auto-sub --skip-download -o "/tmp/%(id)s" "URL"
# V2EX 热门
curl -s "https://www.v2ex.com/api/topics/hot.json" -H "User-Agent: agent-reach/1.0"
# B站搜索（bili-cli，无需登录）
bili search "query" --type video -n 5
# RSS 订阅源
python3 -c "import feedparser; [print(f'{e.title} — {e.link}') for e in feedparser.parse('FEED_URL').entries[:5]]"
环境检查
# 检查可用 channel 与每个平台当前激活的后端
agent-reach doctor --json
工作区规则
不要在 agent workspace 创建文件。 使用 /tmp/ 存放临时输出，~/.agent-reach/ 存放持久数据。
详细文档
What ships with it
5 files 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.
- 1mo ago First seen · 89 lines · 278 tokens per session scan A 8fe61aa945b0
agent-reach is a skill published in the GitHub repository noahneancy-byte/netreach (35 stars, last pushed 2mo ago), licensed MIT. It adds 278 tokens to every session and 1,048 once invoked, about $0.0011 per session on Opus 5.5. 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 2026-08-31.
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