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 Jinchen-Yang/diansai-skill --skill plan-solutiongit clone --depth 1 https://github.com/Jinchen-Yang/diansai-skillWrote 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/jinchen-yang/diansai-skill/plan-solution)<a href="https://agentmods.dev/skills/jinchen-yang/diansai-skill/plan-solution"><img src="https://agentmods.dev/badge/skills/jinchen-yang/diansai-skill/plan-solution/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/jinchen-yang/diansai-skill/plan-solution"><img src="https://agentmods.dev/badge/skills/jinchen-yang/diansai-skill/plan-solution.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 | $0.00083 | $0.01065 |
| Opus 5.5 | $0.00033 | $0.00426 |
| Sonnet 5.5 | $0.00017 | $0.00213 |
| Haiku 4.5 | $0.00008 | $0.00106 |
Grade A, and why
plan-solution 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
plan-solution —— 方案 + 需求(流水线 ②)
lane: lead(推理重,建议 Claude) · needs: 无 · 门: 人工签字需求表
把题目变成"怎么做 + 要满足哪些硬指标"。借鉴金奖经验,别凭空设计。
前置
读 design/problem.yaml(没有就先跑 /read-problem)。重点看 restrictions.camera_allowed —— 决定视觉路线。
步骤
- 查金奖经验/技术栈(Read,不复制):
kb/10-典型赛题实战Playbook与Checklist.md—— "典型赛题技术栈组合"表,找与本题category最近的一行作起点。kb/09-开源资源与备赛经验.md—— 金奖做法/避坑。kb/06-PID及衍生控制算法.md、kb/08-软件架构与调试工程化.md—— 控制结构。
- 定方案(逐子系统):
- 主控:默认 MSPM0G3507(KB03),需更强算力/FPU 再议 STM32G431。
- 视觉:
camera_allowed=true→ K230 做识别/巡线;=false→ 纯灰度/电磁,显著标注本届不上 K230。 - 传感:循迹(灰度阵列/电磁/K230)、定位(编码器/IMU/TOF)按题目功能选。
- 执行:电机+驱动(默认 TB6612+编码电机)、舵机(如需转向/云台)。
- 控制结构:嵌套 PID(外环位置/航向 ← 视觉/IMU/灰度;内环速度 ← 编码器)+ FSM 跑流程。
- 推导需求(硬数字,给后续选材/供电/接线用):
- 电源轨与电压、每轨最坏电流(电机用堵转)、逻辑电平。
- 接口清单与数量:要几路 PWM/UART/I2C/SPI/ADC/QEI(对照 MCU 能力表
contracts/mcu/)。 - 每个外设及其接口、对端连接器。
- 写
design/solution.md(模板见下)。 - 人工门:把"签字需求表"摊给用户逐项确认;用户没确认的硬指标不要默认,标 TODO。确认后更新
STATUS.md→ ③/④,并提示可并行:lead 跑/setup-env,随后/select-parts。
design/solution.md 模板
# 方案与需求 —— <题目名>
来源: design/problem.yaml | 类别: <category> | 摄像头: <允许/禁止>
## 技术方案
- 主控: MSPM0G3507(理由…)
- 视觉: K230 / 无(依据 camera_allowed)
- 传感: … 执行: … 控制结构: 嵌套PID + FSM
- 参考金奖技术栈: KB10 <哪一行>
## 子系统清单
| 子系统 | 方案 | 接口 | 备注 |
## 签字需求表(★用户逐项确认)
| # | 需求 | 指标 | 确认 |
|---|------|------|------|
| 电源 | 轨/电压/最坏电流 | … | ☐ |
| 接口数量 | PWMx? UARTx? I2C? ADCx? QEIx? | … | ☐ |
| 每外设接口+电平 | … | … | ☐ |
| 连接器 | … | … | ☐ |
## 待确认/风险(不擅自默认)
- …(源自 problem.yaml.ambiguities)
注意
- 需求表是后面
select-parts/power-design/interconnect的输入契约,数字要硬。 camera_allowed=false时整条视觉链改纯灰度/电磁,务必在方案顶部红字提示。
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 · 62 lines · 83 tokens per session scan A 5320b9f09e5d
plan-solution is a skill published in the GitHub repository Jinchen-Yang/diansai-skill (12 stars, last pushed 3mo ago), licensed MIT. It adds 83 tokens to every session and 1,065 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-31.
plan-solution compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| plan-solutionJinchen-Yang/diansai-skill | Skill | 12 | 3mo ago | MIT | A | 83 | Claude Code |
| mspm0-ccsmc3545dada/mspm0-skill | Skill | 378 | 3mo ago | MIT | A | 101 | Claude Code, Codex |
| mspm0-skillIbook000/mspm0-skill | Skill | 13 | 1mo ago | MIT | A | 76 | Claude Code, Codex |
| volt-otatonone-ai/tonone | Skill | 77 | 23d ago | MIT | A | 70 | Claude Code |
| volt-firmwaretonone-ai/tonone | Skill | 77 | 23d ago | MIT | A | 76 | Claude Code |
| agentic-hilagentic-hil/agentic-hil | Skill | 24 | yesterday | Apache-2.0 | A | 104 | Claude Code |
| iot-expertpersonamanagmentlayer/pcl | Skill | 44 | 11d ago | Apache-2.0 | A | 59 | Claude Code |