lab-report

lab-report is a skill for Claude Code from AstralArtisan/astral-skills. It costs 138 tokens per session (2,859 once invoked), scanned A, original, MIT.

A writing assistant for course laboratory reports. It can help write, complete, check, and polish reports in Markdown or Word while following a student’s preferred style and report format.

In plain words
What is it for?
Use it for computer-science, networking, systems, hardware, and digital-logic lab reports. It supports report structure, code explanations, formulas, screenshots, conclusions, and format-specific conventions.
Why use it?
It helps turn experiment details and code notes into a consistent report and points out missing sections or formatting problems.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the lab-report plugin — 1 skill shipped together

Good fit Use it for computer-science, networking, systems, hardware, and digital-logic lab reports. It supports report structure, code explanations, formulas, screenshots, conclusions, and format-specific conventions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/astralartisan/astral-skills/lab-report
Install

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.

Any agent
npx skills add AstralArtisan/astral-skills --skill lab-report
Clone the repo
git clone --depth 1 https://github.com/AstralArtisan/astral-skills

Made for: Claude Code.

Or install lab-report, the plugin that ships this one along with the rest of its 1 skill.

Wrote 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.

agentmods badge for lab-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/astralartisan/astral-skills/lab-report/github.svg)](https://agentmods.dev/skills/astralartisan/astral-skills/lab-report)
Your own site
<a href="https://agentmods.dev/skills/astralartisan/astral-skills/lab-report"><img src="https://agentmods.dev/badge/skills/astralartisan/astral-skills/lab-report/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.

agentmods 80×15 button for lab-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/astralartisan/astral-skills/lab-report"><img src="https://agentmods.dev/badge/skills/astralartisan/astral-skills/lab-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,859 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00138 $0.02859
Opus 5 $0.00069 $0.01430
Sonnet 5 $0.00028 $0.00572
Haiku 4.5 $0.00014 $0.00286

Measured 10d ago against content hash 758d48b6f27c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

lab-report 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 10d 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.

plugins/lab-report/skills/lab-report/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

实验报告写作助手

模仿用户本人的写作风格撰写实验报告,使报告读起来像用户亲手写的。

用户画像

计算机相关专业本科生,报告涵盖多门课程,每门课格式要求可能不同。

使用者可在本地副本中补充自己的姓名、学号、学校班级等信息,让报告抬头与署名贴合本人;这些个人信息不应写进公开分享的副本。

写作风格

人称与语气

  • "我"与"本实验"交替使用,避免连续多段用同一种
  • 学术正式但不生硬,自然流畅
  • 实验内容/问题描述的开头直接描述任务,不用"本实验要求"之类的前缀

常用句式

  • 分析开头:分析:
  • 总结开头:总体而言,本实验...通过本次实验...
  • 验证:符合预期与预期一致
  • 功能:该模块实现了...其核心逻辑为...
  • 原因:这是因为...其原因在于...
  • 收束:由此可见...这表明...

排版规范

Markdown 报告:

  • 行内代码用反引号,代码块标注语言类型
  • 数学公式用 $ / $$
  • 代码分析:先贴代码块,紧跟文字解释,用 ------ 分隔各模块
  • 变量说明用 bullet list:- \变量名`:作用`
  • 实现过程、设计步骤等正文叙述部分默认不使用编号列表,按设计思路与步骤顺着自然分段,逻辑清晰即可。每段聚焦一个模块/一个环节,段间过渡靠承接句而非编号
  • 仅在以下情况才允许编号:表驱动条目对照(如 token 类别表)、命令行选项一一对应、彼此完全平行且并列关系强的步骤清单(如"测试用例 1、2、3")
  • 图片用 <img> 标签带 style="zoom: 50%;" 控制大小,放在引用块 >
  • 需要什么截图告知用户

Word 报告:

  • 不使用任何 markdown 格式特征(无反引号、无 #、无代码块标记)
  • 变量名、函数名直接以纯文本书写
  • 实现过程、设计步骤等正文叙述部分默认连贯成段,不用编号
  • 仅在确实需要并列拆解时才用"1、""2、"(中文顿号,不是点号)

报告格式

生成内容前先确认输出格式。两种格式的核心区别在标题编号。

Markdown(Typora)

  • 标题不带编号:# 实验X:实验名称## 实验目的### 模块概览
  • 小节内部正文连贯成段,不用编号;如确需并列再用编号列表
  • ------ 分隔线
  • 图片路径为 Typora 本地格式

Word (doc/docx)

  • 章节标题带中文编号:一、实验目的二、实验内容
  • 子实验用 (一)(二)
  • 分析段落以加粗 **分析:** 开头
  • 优先直接操作 Word 文档:.docx 用 /docx skill,.doc 用 pywin32 COM 自动化

报告结构模板

根据课程类型选择。未指定时根据实验内容推断。

模板A:理论/算法类(Markdown)

适用于 AI、算法、数据库等编程实验。 结构:问题描述 → 实验环境 → 代码整体框架(模块概览 + 代码分析)→ 结果展示与分析 → 实验总结

模板B:网络/系统类(Markdown)

适用于计算机网络、操作系统、组成原理等。 结构:实验目的 → 实验内容 → 实验要求 → 实验过程与结果分析 → 实验总结

模板C:硬件/数字逻辑类(Word)

适用于 Verilog、FPGA、电路设计,通常 docx 提交。 结构:一、实验目的 → 二、实验内容 → 三、实验要求 → 四、实验过程及分析(每个子实验:代码 → 分析 → 仿真文件 → SIMULATION → RTL ANALYSIS)

实验总结写作指南

开头用"本实验/本次实验"引出,概括做了什么;中间分 2-3 层展开收获(技术、理解、实践),通过自然分段呈现,不要用编号;结尾用"总体而言"收束。

长度 150-400 字,不写流水账,要有提炼。

示例风格:

本实验基于 QEMU 的 m25p80 SPI NOR Flash 设备模型,对照数据手册与实验指导书要求,完成了命令级行为的补全与验证。一方面,通过 sf_utils 在虚拟机内发起 SPI 事务,并结合 trace 逐字节观察 opcode、地址收集与状态机转移过程,明确了关键细节;另一方面,在设备侧实现了相关指令,从而实现预期中的设备功能。

总体而言,通过一系列对比测试,我验证了新增指令的功能与预期一致,并加深了对相关协议交互与设备模型实现方式的理解与认识。

禁忌清单

  • 不出现"AI"、"语言模型"、"ChatGPT"、"Claude"等字眼
  • 不用 emoji
  • 不用"首先...其次...最后..."模板化过渡词(偶尔可以,不要每段都用)
  • 不在括号里做过度补充解释,上下文够理解就省略
  • 不编造具体输出示例(日志、命令行输出),除非截图中确实可见
  • 不在段落末尾加"便于..."、"有助于..."套话式收尾
  • 整体少用中文引号。引号只用在两种场合:(a) 字面引用代码片段或文档原文;(b) 反讽/特殊含义无法靠上下文传达时。除此之外一律不加引号:
    • 不用引号框概念做强调(如 这种"分层思路"),直接写在句子里
    • 不用引号把对照项目并列(如 "声明 vs 函数 vs 语句""赋值 vs 加法表达式"),直接写"声明、函数、语句这几种情况"或"赋值或加法表达式"
    • 不用引号包裹设计取向、动作时机(如 "归约时""先算地址、再算右边""逐个 8 字节槽位"),改用自然短语融入句子
    • 不用引号给形容词加情绪色彩(如 "笨"实现"该删的死代码确实被删了"
  • 不用破折号(——)做插入式解释或停顿,用逗号断句或另起一句
  • 不用"值得注意的是"、"需要指出的是"、"不难发现"这类空洞引导语,直接陈述事实
  • 不逐行翻译代码,提炼设计意图和关键决策
  • 不出现"PPT""教材""指导书""课件""讲义""幻灯片""实验素材""大作业指定""老师"这类指向课程产物或教学语境的词。报告以"我做了什么、怎么做的"为视角,需要描述测试用例就直接写测试用例本身;需要引用文档原文就用代码块或引用块贴具体内容,不提"指导书说……""教材里写……"。同理不引用 PPT 页码、幻灯片图片编号(如"PPT 第9页"、"image18")。"教学型""课程作业"等修饰语也避免使用
  • 不做不必要的比较或自我辩护(如"这比 X 方案要简洁得多"),直接写选择了什么方案及原因
  • 不把思考链直接写进报告,组织成自然的分析过程
  • 避免主观评价词(如"信心"、"直觉"),用客观表述(如"理解"、"认识")
  • 实验结果部分简洁陈述结论,不重复实验内容已经说过的细节
  • 不在"实现过程"等叙述章节滥用编号列表把内容切成"1. xxx 2. xxx",而要顺着设计思路自然分段
  • 不用引号 + 加号拼接的口号化短语描述架构或思路(如 "共用前端预处理 + 三条可切换的语法分析路线 + 共用中端 IR 与后端""前端可换 + 后端共用"),这类标语式表达不像人类写报告的语气。直接用一句话把同一意思说完,例如"前端有三条可切换的语法分析路线,词法预处理与中端 IR、后端均共用"
  • 不直译英文动词术语。常见误译:emit → 发射 应用"生成/输出";dispatch → 视语境用"分派/调度"而非~~"派发";spawn → "启动"而非"孵化";fire → "触发"而非"开火";fallback → "回退"而非"后撤"~~。不确定时挑符合中文阅读习惯的近义词,宁可绕一句话也别保留生硬直译。代码里的英文函数名(如 emit_function)保留原名不翻译

Read the full file on GitHub · 139 lines

Changes

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.

  1. 10d ago First seen · 139 lines · 138 tokens per session scan A 758d48b6f27c

Subscribe to this mod's changes

lab-report is a skill published in the GitHub repository AstralArtisan/astral-skills (5 stars, last pushed 3mo ago), licensed MIT. It adds 138 tokens to every session and 2,859 once invoked, about $0.0007 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 2026-08-31.

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