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 skills add curiositech/some_claude_skills --skill design-archivistgit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/design-archivist)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/design-archivist"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/design-archivist/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.
<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/design-archivist"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/design-archivist.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 5.1 | $0.00085 | $0.01510 |
| Opus 5 | $0.00043 | $0.00755 |
| Sonnet 5 | $0.00017 | $0.00302 |
| Haiku 4.5 | $0.00009 | $0.00151 |
Grade A, and why
design-archivist 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.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Archivist
A design anthropologist that systematically builds visual databases through large-scale analysis of real-world examples. This is a long-running skill designed for multi-day research (2-7 days for 500-1000 examples).
Quick Start
User: "Research design patterns for fintech apps targeting Gen Z"
Archivist:
1. Define scope: "fintech landing pages, Gen Z audience (18-27)"
2. Set target: 500 examples over 2-3 days
3. Identify seeds: Venmo, Cash App, Robinhood, plus competitors
4. Begin systematic crawl with checkpoints every 10 examples
5. After 48 hours: Deliver pattern database with:
- Color trends
- Typography patterns
- Layout systems
- White space opportunities
When to Use
Use for:
- Exhaustive design research (300-1000 examples)
- Pattern recognition across large example sets
- Competitive visual analysis
- Trend identification with data backing
- Domain-specific design language extraction
NOT for:
- Quick design inspiration (use Dribbble/Awwwards directly)
- Single example analysis
- Small samples (<50 examples)
- Real-time trend spotting (this takes days)
Core Process
1. Domain Initialization
- Define target domain and audience
- Set target count (300-1000 based on specificity)
- Identify seed URLs or search queries
- Establish focus areas
2. Systematic Crawling
For each example:
- Capture visual snapshot
- Record metadata (URL, timestamp, context)
- Extract Visual DNA (colors, typography, layout, interactions)
- Analyze contextual signals (audience, positioning, success indicators)
- Apply categorical tags
- Save checkpoint every 10 examples
3. Pattern Extraction
After accumulating examples, identify:
- Dominant patterns - The "norm" (most common approaches)
- Emerging patterns - The "future" (gaining traction)
- Deprecated patterns - The "past" (avoid these)
- Outlier patterns - The "experimental" (unique approaches)
Visual DNA Extraction
For each example, extract:
What ships with it
5 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.
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.
- 10d ago First seen · 187 lines · 85 tokens per session scan A da054349fca7
design-archivist is a skill published in the GitHub repository curiositech/some_claude_skills (218 stars, last pushed 4d ago), licensed MIT. It adds 85 tokens to every session and 1,510 once invoked, about $0.0004 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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