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/blockcell-labs/blockcell/wechat_binancenpx skills add blockcell-labs/blockcell --skill wechat_binancegit clone --depth 1 https://github.com/blockcell-labs/blockcellWrote 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/blockcell-labs/blockcell/wechat_binance)<a href="https://agentmods.dev/skills/blockcell-labs/blockcell/wechat_binance"><img src="https://agentmods.dev/badge/skills/blockcell-labs/blockcell/wechat_binance.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 | $0.00000 | $0.00493 |
| Opus 5 | $0.00000 | $0.00246 |
| Sonnet 5 | $0.00000 | $0.00099 |
| Haiku 4.5 | $0.00000 | $0.00049 |
Grade A, and why
wechat_binance 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 4d 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
币安行情微信推送
Shared {#shared}
- 用于抓取 Binance USDT 交易对中按流通市值估算排名靠前的代币，并通过 macOS 微信客户端发送给指定联系人。
- 运行环境必须是 macOS，微信客户端已登录，并已向运行 BlockCell 的终端授予辅助功能权限。
- 本地入口是
SKILL.py，依赖python3、requests和系统命令osascript。 - 发送消息属于外部副作用：联系人必须来自用户当前请求；用户没有指定联系人时才使用“文件传输助手”。
- 不得编造行情、联系人匹配结果或发送结果，最终回复只能依据脚本的实际 stdout。
Prompt {#prompt}
- 用户要求抓取并发送币安行情时，固定调用：
exec_local(path="SKILL.py", runner="python3", cwd_mode="skill", args=["{\"contact\":\"好友昵称\",\"top\":10}"]) args只传一个 JSON 字符串，字段约定：contact：微信联系人昵称；未指定时传“文件传输助手”。top：正整数，默认 10，允许范围 1 到 100。
- 不要传
message：脚本会根据实际行情生成发送内容。 exec_local返回包装后的 JSON，脚本真实输出位于stdout。优先解析 stdout 中的 JSON：- 成功时使用
display_text向用户确认发送结果。 - 失败时根据
error或 stderr 说明失败原因，不得声称已经发送。
- 成功时使用
- 如果联系人不明确但用户显然不希望发送给“文件传输助手”，先询问联系人；如果只是未指定，则直接使用默认联系人。
- 如果用户只要求查看行情而没有要求通过微信发送，不要调用此 Skill，因为该入口始终会执行发送操作。
Summary {#summary}
- 成功回复应包含实际联系人、发送的 Top 数量和脚本返回的行情概览。
- 失败回复应简要说明网络、微信状态、联系人匹配或辅助功能权限中的实际错误。
- 不输出内部日志、完整 tool trace 或未验证的数据。
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.
- 4d ago First seen · 30 lines · 0 tokens per session scan A daeb70dc2d67
wechat_binance is a skill published in the GitHub repository blockcell-labs/blockcell (263 stars, last pushed 20d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 493 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.
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