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 commands/alwkala/tidyfactor-design/studygit clone --depth 1 https://github.com/alwkala/tidyfactor-designWhat 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 | $0.00000 | $0.01027 |
| Opus 5 | $0.00000 | $0.00513 |
| Sonnet 5 | $0.00000 | $0.00205 |
| Haiku 4.5 | $0.00000 | $0.00103 |
Grade A, and why
study 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 2d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command: study — Design DNA Extraction & Competitive Analysis
Runtime entry point for extracting design DNA from a live URL, screenshot, or reference site. Part of the Discovery lifecycle phase.
When to use
- Before starting any new design project (run
study→ thenbrief→ theninit) - When reverse-engineering a competitor's design language
- When a client says "make it feel like [reference]"
Dispatch Steps
- Load
memory/06-quality-bar.md— anti-slop awareness (so the study doesn't praise AI patterns). - Load
memory/01-design-schools.md— classify the reference into a design movement. - Execute the DNA extraction protocol below.
- Output a diagnosis report — user decides next step.
DNA Extraction Protocol
Input
One of:
- Live URL → browse the page, capture computed styles, screenshot sections
- Screenshot / image → visual analysis only (less precise on exact hex values)
- Multiple URLs → cross-reference to find the shared design language
Extraction Axes (6 Dimensions)
| Axis | What to extract | How to extract |
|---|---|---|
| Macrostructure | Section rhythm, hero type, scroll behavior | Map each viewport-height section, note sticky/parallax/pinned |
| Color Anchor | Primary, surface, text, accent colors | Computed styles from getComputedStyle() on buttons, headers, body, backgrounds — NOT visual guesses from screenshots |
| Type Pairing | Heading family, body family, weight usage | <link> and @font-face declarations, NOT visual matching |
| Spacing System | Base unit, scale pattern, section gaps | Measure actual padding/margin values on key containers |
| Motion Register | Entrance style, scroll interaction, transition timing | Observe scroll behavior, hover states, page transitions |
| Component DNA | Card style, button shape, nav pattern, footer pattern | Classify against the catalogs in memory/14-nav-footer-catalog.md |
Critical Rules
- Sample computed styles (actual rendered hex values from buttons, headers, body text) — never guess from a screenshot's visual impression.
- Extract font family names from
<link>/@font-facedeclarations — never from visual matching. - Do NOT extract layout structure — the reference site's section order is not a design token; the engine's layout archetypes (
memory/13-layout-archetypes.md) own that decision. - Do NOT extract literal copy text — voice rules transfer (tone, banned words), literal sentences don't.
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.
- 2d ago First seen · 99 lines · 0 tokens per session scan A fdd088b1e4d5
study is a command published in the GitHub repository alwkala/tidyfactor-design (5 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,027 tokens. 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.
Other commands, from other repositories
github-issue
Create a GitHub issue from a natural language description.
test
Hello world test command.
discover
Run a full user research cycle — persona creation, empathy mapping, and journey mapping for a product or feature.
coograph-verify
Verify that the described work is complete and correct. Provide evidence for every claim. You verify — you do not implement or fix style.
api-gen
Generate REST API endpoints with routes, validation, error handling, and tests.
component-gen
Generate React or Vue components with prop types, styling, accessibility, and tests.