Datasheet 代码同步
- 作者仓库星标 1
- 作者仓库 claude-skills
Datasheet Diff Reader
Overview
Compare two part datasheet revisions and flag electrical, timing, package, or lifecycle changes that matter.
Core Workflow
- Gather the full input corpus and normalize messy, repetitive, or partial artifacts into a usable working set.
- Cluster related items into themes, categories, or issue groups without flattening important differences.
- Extract the strongest signals, representative examples, and unresolved questions from each cluster.
- Produce a structured summary that is actionable for the next human or agent in the workflow.
Deliver
- A clear thematic summary or grouped output with representative evidence.
- The most important patterns, edge cases, and unknowns in the corpus.
- Actionable next steps, owners, or decisions when the task calls for them.
Guardrails
- Do not over-merge distinct issues just to simplify the summary.
- Preserve nuance when a cluster contains disagreement or uncertainty.
- Make the grouping logic legible enough that someone can audit it later.
- Avoid commands that actuate hardware, move robots, or change live controller state unless explicitly requested.
- 流狐分类
- 数据
- 作者声明 Agent
- 未找到明确声明；不据此推断已兼容或已测试
- 静态检查
- 88 / 100 · 启发式扫描，不代表运行安全
- 作者 / 版本 / 许可
- @00PrabalK00 · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- 未声明
- 底层运行要求
- 未声明
- 检测到的文件与系统行为
-
- 只读
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无（仅作为资料）
档案由构建时根据 SKILL.md 与安装命令自动衍生，可能与作者实际意图存在差异。
需要注意： 未限定 allowed-tools，默认拥有全部工具权限。
作者没有在当前 SKILL.md 中定义固定输出样例。Compare two part datasheet revisions and flag electrical, timing, package, or lifecycle changes that matter.
Gather the full input corpus and normalize messy, repetitive, or partial artifacts into a usable working set. Cluster related items into themes, categories, or issue groups without flattening important differences. Extract the strongest signals, representative…
A clear thematic summary or grouped output with representative evidence. The most important patterns, edge cases, and unknowns in the corpus. Actionable next steps, owners, or decisions when the task calls for them.
Do not over-merge distinct issues just to simplify the summary. Preserve nuance when a cluster contains disagreement or uncertainty. Make the grouping logic legible enough that someone can audit it later.
# Datasheet Diff Reader
## Overview
Compare two part datasheet revisions and flag electrical, timing, package, or lifecycle changes that matter.
## Core Workflow
1. Gather the full input corpus and normalize messy, repetitive, or partial artifacts into a usable working set.
2. Cluster related items into themes, categories, or issue groups without flattening important differences.
3. Extract the strongest signals, representative examples, and unresolved questions from each cluster.
4. Produce a structured summary that is actionable for the next human or agent in the workflow.
## Deliver
- A clear thematic summary or grouped output with representative evidence.
- The most important patterns, edge cases, and unknowns in the corpus.
- Actionable next steps, owners, or decisions when the task calls for them.
## Guardrails
- Do not over-merge distinct issues just to simplify the summary.
- Preserve nuance when a cluster contains disagreement or uncertainty.
- Make the grouping logic legible enough that someone can audit it later.
- Avoid commands that actuate hardware, move robots, or change live controller state unless explicitly requested.作者原文负责流程事实；流狐只索引当前章节、要点、文件与命令。
章节 -> Overview → Core Workflow → Deliver → Guardrails
要点 -> Compare two part datasheet revisions and flag electrical, timing, package, or lifecycle changes that matter. · 1. Gather the full input corpus and normalize messy, repetitive, or partial artifacts into a usable working set. · - A clear thematic summary or grouped output with representative evidence. · - Do not over-merge distinct issues just to simplify the summary.
文件/命令 -> 原文未列出明确文件或命令
内容 SHA-256 -> 4cdf1a13ab97
方法与流程
适用与边界
原文中的明确线索