# Ground a coding agent in service manuals before it builds a mechanical recreation

> A builder recreated an airport split-flap departure board in the browser with Claude Code. Before any code, research skills pulled real specifications from the manufacturer's old service manuals, patents and teardowns; then the board was built module by module with browser tests that click through it.

- URL: https://paperchasewebb.ai/bots/marketplace/items/ground-a-coding-agent-in-service-manuals-before-it-builds-a-mechanical-recreation/
- Type: Agent use case pack
- Category: Creative and video
- By: PaperChaseWebb
- Works with: Claude Code (named in the listing); Plain .md
- Price: Free USD
- Difficulty: Intermediate
- Setup time: 30 min
- Time to result: One working session
- Format: Markdown (.md) file, ground-a-coding-agent-in-service-manuals-before-it-builds-a-mechanical-recreation.md
- Version: 1.0, updated 2026-10-29
- License: Personal and commercial use. Credit the original source when you share the workflow.

## What you end up with

The point is that results came from grounding and small pieces, not one perfect prompt.

## What you get

- A plain-language summary of the workflow
- A fill-in prompt template
- What to watch out for
- A link to the original source

## Who it is for

Builders who already use AI agents and want a proven workflow they can copy into their own project.

## Tools needed

- Claude Code: writes the SVG geometry, animation and browser tests
- Research skills: extract specifications from manuals, patents and teardowns
- Anatomy skill (open source): starting point for the first flap module
- You need: An AI coding agent or chat model
- You need: A small real task to try it on

Cost to run: Free with the agent plan you already use.

## How it works

1. **Collect primary sources first: manuals, patents, teardowns.** Collect primary sources first: manuals, patents, teardowns. Expected: Done before you move to the next step.
2. **Have the agent turn them into a short spec with measurements and cite .** Have the agent turn them into a short spec with measurements and cite where each came from. Expected: Done before you move to the next step.
3. **Build one module, review it in the browser and give specific feedback.** Build one module, review it in the browser and give specific feedback. Expected: Done before you move to the next step.
4. **Have the agent write browser tests that click through each part.** Have the agent write browser tests that click through each part. Expected: Done before you move to the next step.
5. **Keep a decisions file so a fresh session can pick up the work.** Keep a decisions file so a fresh session can pick up the work. Expected: Done before you move to the next step.

## Sample prompt: Workflow template (Claude Code, Research skills)

```
Apply this workflow to [your project]:
1. Collect primary sources first: manuals, patents, teardowns.
2. Have the agent turn them into a short spec with measurements and cite where each came from.
3. Build one module, review it in the browser and give specific feedback.
4. Have the agent write browser tests that click through each part.
5. Keep a decisions file so a fresh session can pick up the work.
Stop and ask me before anything irreversible: deploys, payments, sends or deletes.
```

Adapted by PaperChaseWebb. Not the original author's prompt.

## Free preview of ground-a-coding-agent-in-service-manuals-before-it-builds-a-mechanical-recreation.md

````markdown
# Ground a coding agent in service manuals before it builds a mechanical recreation

PaperChase agent use case (free feed entry), version 1.0. Source: [u/SelectionNo3613](https://www.reddit.com/r/ClaudeAI/comments/1xi3s3l/i_used_claude_code_to_reverse_engineer_the_old/), 2026-10-28.

## What they did

The research step gave the agent real mechanical measurements instead of guesses. From there the loop was research, build, review in the browser, give specific feedback, test and repeat. Claude wrote browser tests that click through the interface, which caught problems that were not visible in the code, and project decisions were written down so work carried across context resets.

## Worth knowing

The point is that results came from grounding and small pieces, not one perfect prompt. Writing decisions to a file is what let the work continue across context resets. The builder works at a robotics company and used its in-house research skills, so the exact tools are not all public.
````

## Worth knowing

- The point is that results came from grounding and small pieces, not one perfect prompt. Writing decisions to a file is what let the work continue across context resets. The builder works at a robotics company and used its in-house research skills, so the exact tools are not all public.
- Figures are as reported by the original author and were not re-measured by us.

## Questions

**Where does this come from?** A public post credited to u/SelectionNo3613. Source: https://www.reddit.com/r/ClaudeAI/comments/1xi3s3l/i_used_claude_code_to_reverse_engineer_the_old/

**Is it free?** Yes. Feed entries are free to read and download.

## How to get it

Free sample. Download it directly at https://paperchasewebb.ai/bots/marketplace/items/ground-a-coding-agent-in-service-manuals-before-it-builds-a-mechanical-recreation/, no signup.

Seller: PaperChaseWebb Inc., mgmt@paperchasewebb.com