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 agentmods add skills/w1ne/kernelcad-web/prepare-promptnpx skills add w1ne/kernelCAD-web --skill prepare-promptgit clone --depth 1 https://github.com/w1ne/kernelCAD-webWrote 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/w1ne/kernelcad-web/prepare-prompt)<a href="https://agentmods.dev/skills/w1ne/kernelcad-web/prepare-prompt"><img src="https://agentmods.dev/badge/skills/w1ne/kernelcad-web/prepare-prompt.svg" alt="Measured on agentmods" 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 | $0.00033 | $0.01244 |
| Opus 5 | $0.00016 | $0.00622 |
| Sonnet 5 | $0.00007 | $0.00249 |
| Haiku 4.5 | $0.00003 | $0.00124 |
Grade A, and why
prepare-prompt 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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
prepare-prompt
Purpose
A vague ask — "a wayfarer-style frame", "that bottle", "make the same one" — produces vague geometry. This sub-skill produces a Real Object Brief: a structured, numbered record of everything the reference communicates before any tool call touches the kernel.
The brief is written as a // Real Object Brief block at the top of the
.kcad.ts file, before any param() or geometry. It is the source of truth
for the entire build. Every downstream sub-skill reads from it.
Inputs
- The user's ask (text, photo path, or both).
- The reference photo(s) — can be one image showing one view, or several showing different angles. More views = fewer hidden-side guesses.
Output
A filled-in // Real Object Brief comment block, plus a list of open
questions if any critical fact (scale, material, hidden side) cannot be inferred.
The Real Object Brief format
Required sections, in this order:
// Real Object Brief
// Artifact: <human name> — <one-line description of what it is>.
// Reference: <relative path to the photo>.
// Scale: millimetres. <key dimension 1: name ~N mm>, <key dimension 2: name ~N mm>,
// <overall bounding box estimate>.
// Visible facts (from reference photo):
// - <Numbered or bulleted. Each item is a distinct visual element.>
// - <Separate form (silhouette) from surface (color, texture, gloss).>
// - <Include relative positions: "A is above B", "C spans the full width".>
// Hidden-side inference:
// - <What must exist that the photo does not show: case back, internal walls,
// fastener counterbores, mounting tabs, wire paths.>
// - <Infer from category: a pocket watch has a case-band, a mug has a handle
// undercut, a USB dongle has a PCB pocket.>
// Validation focus:
// - <The 3–5 visual cues you will check against each rendered view.>
// - <Name the view (front, top, right, iso) + what to check in it.>
Scale discipline
If the reference photo has a known scale object (a hand, a coin, packaging dimensions), record it:
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.
- 5d ago First seen · 138 lines · 33 tokens per session scan A 4baf255e62b7
prepare-prompt is a skill published in the GitHub repository w1ne/kernelCAD-web (18 stars, last pushed 7d ago), licensed MIT. It adds 33 tokens to every session and 1,244 once invoked, about $0.0002 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 2026-08-30.
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