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 AISEE-LAB/aisee-plugin --skill hw-srsgit clone --depth 1 https://github.com/AISEE-LAB/aisee-pluginWrote 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/aisee-lab/aisee-plugin/hw-srs)<a href="https://agentmods.dev/skills/aisee-lab/aisee-plugin/hw-srs"><img src="https://agentmods.dev/badge/skills/aisee-lab/aisee-plugin/hw-srs.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 | $0.00160 | $0.01767 |
| Opus 5 | $0.00080 | $0.00883 |
| Sonnet 5 | $0.00032 | $0.00353 |
| Haiku 4.5 | $0.00016 | $0.00177 |
Grade A, and why
hw:srs 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hw:srs
把自然语言想法收敛为硬件/嵌入式项目的需求与硬件适配输入文档。
本技能是 OpenSpec 前置输入层,不直接创建 OpenSpec change,不写 proposal.md、specs/**、design.md 或 tasks.md。后续由 hw:change-plan 把本文档映射到 aisee-device-spec-driven change 的 source-map.md seed。
Inputs
用户可提供:
- 原始想法、目标或问题现象
- 旧项目说明、竞品、测试记录、规格书
- 成本、周期、体积、功耗、可靠性、制造难度、维护性等约束
- 候选 MCU/CPU/FPGA/传感器/执行器/模组/平台
- 已有库存、采购限制、团队熟悉工具链
- 既有 OpenSpec specs、历史需求或 active changes
可选参数:
--lang zh|en,默认zh--depth shallow|standard|deep,默认standard--baseline-aware,存在openspec/specs/、openspec/changes/或历史 SRS 时默认启用
References
需求澄清时读取:
references/question-bank.md
硬件能力评估维度不足时读取:
references/capability-checklist.md
Output
保存到:
aisee/docs/requirements/<YYYY-MM-DD>-<slug>-hw-srs.md
生成时读取:
assets/srs-template.md
必须包含:
- 项目目标、边界、非目标
- 用户/操作者、使用场景、环境
- 功能需求 FR,使用
FR-001形式编号 - 非功能需求 NFR
- 成本、周期、体积、功耗、制造、维护、可靠性和合规约束
- 需求可调整项与不可调整项
- 硬件/平台候选矩阵
- 需求与硬件能力不匹配项
- 需求调整与取舍记录
- 最终硬件/平台方向或待确认项
- 验收目标和证据形式
[ASSUMPTION]、[OPEN]、[FIT-DATA-MISSING]、[SPEC-GAP]- 给
hw:architecture的输入提示 - 给
hw:change-plan的 FR 变更候选清单
Phase 0 - Read Context
先读取已有上下文,避免重复提问。
PowerShell:
Get-Content -ErrorAction SilentlyContinue README.md
Get-Content -ErrorAction SilentlyContinue openspec/project.md
if (Test-Path openspec/specs) { rg --files openspec/specs }
if (Test-Path openspec/changes) { Get-ChildItem openspec/changes -Directory | Select-Object -ExpandProperty Name }
if (Test-Path aisee/docs/requirements) { rg --files aisee/docs/requirements }
POSIX shell:
cat README.md 2>/dev/null
cat openspec/project.md 2>/dev/null
test -d openspec/specs && rg --files openspec/specs
test -d openspec/changes && find openspec/changes -maxdepth 1 -type d
test -d aisee/docs/requirements && rg --files aisee/docs/requirements
Phase 1 - Anchor Scope
第一轮只问一个最关键的范围问题。优先确认:
- 新产品、旧产品改版、验证样机、课程/竞赛项目,还是量产项目
- 目标用户或操作者
- 主要物理对象:信号、传感器、执行器、通信链路、显示、人机交互、控制对象、供电系统等
Phase 2 - Discovery Dialogue
读取 references/question-bank.md 后按主题推进。
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.
- 8d ago First seen · 164 lines · 160 tokens per session scan A a1ced933dedf
hw:srs is a skill published in the GitHub repository AISEE-LAB/aisee-plugin (11 stars, last pushed 2mo ago), licensed MIT. It adds 160 tokens to every session and 1,767 once invoked, about $0.0008 per session on Opus 5. 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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