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/suharvest/sensecraft-solutions/solution-clinpx skills add suharvest/sensecraft-solutions --skill solution-cligit clone --depth 1 https://github.com/suharvest/sensecraft-solutionsWrote 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/suharvest/sensecraft-solutions/solution-cli)<a href="https://agentmods.dev/skills/suharvest/sensecraft-solutions/solution-cli"><img src="https://agentmods.dev/badge/skills/suharvest/sensecraft-solutions/solution-cli.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 | $0.00051 | $0.01890 |
| Opus 5 | $0.00026 | $0.00945 |
| Sonnet 5 | $0.00010 | $0.00378 |
| Haiku 4.5 | $0.00005 | $0.00189 |
Grade A, and why
solution-cli 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -o /dev/null -w '%{http_code}\n' http://localhost:2125/healthz # → 200 How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
solution-cli — 用 solutionctl 在命令行驱动引擎
solutionctl 是 packages/solutionctl/ 里的瘦客户端:它自己不含任何引擎代码,只负责定位
引擎二进制(provisioning-station)并通过子进程调用它。AI agent 加载本 skill 后,无需知道二进制
路径,就能在终端发现方案、部署、离线校验、查已部署 app。
何时用
- headless / CI / 脚本化部署:GitHub Actions、批量给多台设备部署、跑完即退。
- 没有桌面 App GUI 的环境(纯命令行机器、远程 SSH)。
- 想离线校验一个方案目录是否符合 spec 契约(这一项不需要引擎,见下)。
不适用:内容编辑(改文案 → 用桌面 App 的编辑模式)、引擎/插件开发(在闭源引擎仓库)。
前提
- 已安装 SenseCraft Solution App,或本机有
provisioning-station引擎二进制。solutionctl按三级顺序自动定位,agent 不用关心路径:- 环境变量
$SENSECRAFT_ENGINE_BIN ~/.sensecraft/engine.json握手文件(App 首次启动写入)- 平台原生查找(macOS
mdfind/ Windows 注册表 / Linuxdpkg)
- 环境变量
- 定位失败时
solutionctl会给出清晰提示(装 App,或export SENSECRAFT_ENGINE_BIN=<引擎绝对路径>)。 - 例外:
solutionctl validate是纯离线的,不需要引擎二进制。
命令速查
从仓库 clone 内跑命令即可,
solutionctl会自动把PS_SOLUTIONS_DIR指向这个 clone 的solutions/(cwd 在 repo 根下任意位置都行),无需--solutions-dir;同时 best-effort 把PS_DEVICES_DIR指向已装桌面 App 的devices/目录(含device_class的方案需要)。 命令行不用加uv run前缀的话直接solutionctl;在 clone 里用uv run --package sensecraft-solutionctl solutionctl <...>。
# 看引擎能力 / 契约元数据(版本、支持的 deployer 类型等)
solutionctl meta
# 发现方案:列出所有方案 ID
solutionctl solution list
部署三步法(deploy-info → 填 → deploy)
别凭空猜 preset 名,也别啃 solution show 的原始 JSON。 走 deploy-info:
# 1. 看这个方案怎么部署:有哪些 preset、每步要填什么、local/remote 怎么选
solutionctl deploy-info <solution_id> [--preset <p>] [--lang en|zh]
# → JSON 输出:
# presets : 每个 preset 的 id + name(按用户意图选一个,再 --preset 收窄)
# steps : 每步的 device_id / type / 必填参数;
# has_targets=true 的步骤(如 docker_deploy)提供 local vs remote 两种 target
# local = 部署到本机 Docker(免 SSH)
# remote = SSH 部署到边缘设备
# request_template : 每个 device 预填好的连接骨架,<REQUIRED: ...> 是用户必须补的空
# 2. 从 request_template 拷出来,填好空,组成 --connection(嵌套 dict)
# 本机 Docker(免 SSH):选 local target,零凭据
# {"<device_id>":{"target":"<...>_local","target_type":"local"}}
# 远程 SSH:选 remote target,补 host/username/password/port
# {"<device_id>":{"target":"<...>_remote","target_type":"remote","host":"...","username":"...","password":"<REDACTED>","port":22}}
# 3. 部署(一次性,跑完即退)—— 注意:不要自己加 --json!
solutionctl deploy <solution_id> \
--preset <preset_id> \
--device <device_id> \
--connection '<填好的 JSON>' \
--yes
# device_id 必须和 deploy-info 里的一致;--device 省略 = 部署该 preset 的全部步骤(CI 场景)
# --verbose 看完整事件流(docker 拉层 + 轮询);默认只渲染生命周期骨架 + 错误日志
# --replace-existing 同名容器已存在时自动停掉重建(默认会报错让用户确认)
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 · 129 lines · 51 tokens per session scan A 89fc113355ac
solution-cli is a skill published in the GitHub repository suharvest/sensecraft-solutions (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 51 tokens to every session and 1,890 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…