envi-classic-lab-automation

envi-classic-lab-automation is a skill for Codex from xuedai-mayi/envi-classic-remote-sensing. It costs 130 tokens per session (2,083 once invoked), scanned A, original, MIT.

An automation guide for completing remote-sensing experiments in ENVI Classic 5.6 and producing a checked lab report. ENVI Classic is software for analysing satellite and other remote-sensing images.

In plain words
What is it for?
Use it to automate ENVI 5.6 experiments, capture each required interface step, validate the evidence, and create a Word or PDF report.
Why use it?
It organises the experiment, records inputs and steps, and requires real screenshots so the final report can be checked against the work performed.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to automate ENVI 5.6 experiments, capture each required interface step, validate the evidence, and create a Word or PDF report.

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Install with agentmods
npx agentmods add skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation
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 xuedai-mayi/envi-classic-remote-sensing --skill envi-classic-lab-automation
Clone the repo
git clone --depth 1 https://github.com/xuedai-mayi/envi-classic-remote-sensing

Made for: Codex.

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 envi-classic-lab-automation

README.md
[![agentmods](https://agentmods.dev/badge/skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation/github.svg)](https://agentmods.dev/skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation)
Your own site
<a href="https://agentmods.dev/skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation"><img src="https://agentmods.dev/badge/skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation/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 envi-classic-lab-automation

Your own site · 80×15
<a href="https://agentmods.dev/skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation"><img src="https://agentmods.dev/badge/skills/xuedai-mayi/envi-classic-remote-sensing/envi-classic-lab-automation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,083 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 $0.00130 $0.02083
Opus 5 $0.00065 $0.01042
Sonnet 5 $0.00026 $0.00417
Haiku 4.5 $0.00013 $0.00208

Measured 11d ago against content hash d609b6e192aa, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

envi-classic-lab-automation 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 11d 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.

skills/envi-classic-lab-automation/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ENVI Classic 遥感实验全流程

目标是交付真实完成的实验与可核验报告,而不是只写一份看似完整的文字。以 ENVI Classic 5.6(64 位)为首选执行环境;每一个实验操作步骤都必须有自己的真实界面截图。

截图原真性是硬约束:报告只能插入 MCP 捕获或用户明确提供的原始截图文件。禁止使用 Python、Pillow、OpenCV 或其他图像处理方式裁剪、标注、拼接、增强或重绘截图。需要对照时,在 Word 中将两个独立原图对象左右或上下排版,不生成新的合成位图。

必须使用的能力

  1. 先使用 envi-classic MCP 完成环境检查、受控启动、老师输入登记、步骤计划冻结、GUI 操作、截图和证据校验。
  2. 报告写作阶段必须加载并遵循现有 remote-sensing-report Skill。不要在本 Skill 中另造一套报告生成器。
  3. 输入含 PDF、DOC/DOCX 或最终要求 PDF 时,同时使用相应的 PDF/文档 Skill 解析、生成、渲染和检查。

如果 envi-classic MCP 不可用,或 remote-sensing-report Skill 不存在,明确报告依赖缺失并停止在证据包阶段;不得假装已经自动操作 ENVI 或生成最终报告。

工作流

执行前完整阅读 workflow.mdevidence-schema.md。需要编写或调试 GUI 配方时,再阅读 gui-recipes.md

如果任务是“实验九 图像锐化”,还必须读取 experiment-9-image-sharpening.md,使用其中 38 个阶段作为最低截图集合。

如果任务是“实验十 数字形态学处理”,还必须读取 experiment-10-digital-morphology.md,以其中阶段为最低截图集合。该预设刻意比旧成品更细,补足旧成品把多项腐蚀、膨胀、开运算、闭运算合并成少量截图的问题。

1. 盘点输入

  • 把老师提供的实验数据、实验指导书和报告模板视为三类必需输入。学生草稿、旧报告和参考成品都不是生成流程的必需输入。
  • 识别全部数据文件(包括 ENVI 原始数据与 .hdr 配对文件)、已有结果、学生信息、输出要求和可选参考成品。
  • 保留原始文件;所有新输出写入新的运行目录或带明确后缀的成品文件。
  • 从指导书提取:实验目的、原理、操作步骤、参数、输出文件、结果分析要求、思考题。
  • 从模板提取:封面字段、标题层级、字体字号、页眉页脚、目录、图表题注和固定段落。
  • 启动会话后立即调用 envi_classic_register_inputs,登记三类老师输入及哈希;之后不得替换输入。

2. 先建“步骤—截图”检查表

在启动 ENVI 前,把指导书拆成有序 stage_id。每个可独立叙述的操作都必须对应唯一截图,不得等操作结束后再猜步骤。

至少覆盖:

  • 数据打开或输入波段选择;
  • 菜单路径与工具窗口;
  • 每一次参数、核模板、角度、阈值、公式或变量映射设置;
  • 输出文件名、目录和格式设置;
  • 运算完成后的结果窗口;
  • 原始影像与各处理结果的视觉对比;
  • 指导书要求的统计、剖面、直方图或评价指标。

同一个操作同时包含“参数设置”和“结果查看”时,拆成两个阶段。禁止用同一截图代替多个阶段。

检查表完成后、任何 GUI 截图之前,调用 envi_classic_set_stage_plan 冻结完整阶段、证据类型、必填参数键和预期窗口。冻结后不得为通过验收而删减阶段或调低截图数。

3. 实机执行与逐步留证

  1. 调用 envi_classic_health_check,确认目标确为 ENVI Classic 5.6 64 位。
  2. 调用 envi_classic_launch,保存 session_id 与运行目录。
  3. envi_classic_list_menu_items 发现真实菜单,不凭记忆猜名称。
  4. 原生菜单使用 envi_classic_invoke_menu;自绘对话框使用受限 envi_classic_run_recipe
  5. 每完成检查表中的一个阶段,立即调用 envi_classic_capture_evidence,写清:
    • 唯一 stage_id
    • 可直接用作图题的中文 caption
    • 实际操作和菜单路径;
    • 全部关键参数;
    • 能唯一匹配的 ENVI 窗口标题。
  6. 每个结果文件生成后调用 envi_classic_register_output,登记文件、哈希和必要统计。

Read the full file on GitHub · 117 lines

Files

What ships with it

7 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.

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. 11d ago First seen · 117 lines · 130 tokens per session scan A d609b6e192aa

Subscribe to this mod's changes

envi-classic-lab-automation is a skill published in the GitHub repository xuedai-mayi/envi-classic-remote-sensing (1 stars, last pushed 1mo ago), licensed MIT. It adds 130 tokens to every session and 2,083 once invoked, about $0.0006 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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