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 blockcell-labs/blockcell --skill shellgit 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/shell)<a href="https://agentmods.dev/skills/blockcell-labs/blockcell/shell"><img src="https://agentmods.dev/badge/skills/blockcell-labs/blockcell/shell/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/blockcell-labs/blockcell/shell"><img src="https://agentmods.dev/badge/skills/blockcell-labs/blockcell/shell.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00325 |
| Opus 5.5 | $0.00000 | $0.00130 |
| Sonnet 5.5 | $0.00000 | $0.00065 |
| Haiku 4.5 | $0.00000 | $0.00032 |
Grade A, and why
shell 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 2mo 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
Shell
Shared {#shared}
- 适合用户明确要求“执行命令”“跑一下”“在终端里执行”这类本机命令。
- 默认工作目录是当前 workspace；如果用户明确指定目录，按用户目录执行。
- 这个 skill 只负责明确的本机命令执行，不负责替用户猜测复杂部署流程。
Prompt {#prompt}
- 只有在以下情况才澄清：
- 用户没有给出明确命令或目标动作
- 用户要执行的动作明显危险，但没有明确确认
- 工具策略：
- 用
exec执行明确命令 - 如果用户给了目录，显式传入工作目录
- 不要无意义地连跑多条无关命令
- 用
- 安全规则：
- 涉及删除、覆盖、停服务、杀进程等危险动作时，不要替用户模糊化；只有用户明确要求时才继续
- 不要把危险命令包装成“只是检查一下”
- 如果只是读取状态或查看信息，优先执行只读命令
- 输出要求：
- 先给一句结果摘要
- 再给关键 stdout / stderr
- 如果失败，明确说明是命令不存在、权限不足、超时还是执行错误
- 如果用户只要求“看一下结果”，优先总结关键行；只有用户要原始输出时再贴更多内容。
What ships with it
2 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.
- 2mo ago First seen · 27 lines · 0 tokens per session scan A a1bdf7b986db
shell is a skill published in the GitHub repository blockcell-labs/blockcell (261 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 325 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
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.
component-fixtures
Use when creating or updating component fixtures for screenshot testing or their shared infrastructure, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, validation, and common pitfalls.