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 Wondermonger-daydreaming/claude-skills-library --skill ateliergit clone --depth 1 https://github.com/Wondermonger-daydreaming/claude-skills-libraryWrote 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/wondermonger-daydreaming/claude-skills-library/atelier)<a href="https://agentmods.dev/skills/wondermonger-daydreaming/claude-skills-library/atelier"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/atelier/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/wondermonger-daydreaming/claude-skills-library/atelier"><img src="https://agentmods.dev/badge/skills/wondermonger-daydreaming/claude-skills-library/atelier.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00117 | $0.02162 |
| Opus 5 | $0.00059 | $0.01081 |
| Sonnet 5 | $0.00023 | $0.00432 |
| Haiku 4.5 | $0.00012 | $0.00216 |
Grade A, and why
atelier 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 12d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/atelier — the cross-mind creative loop
Codified from a day of cross-mind making (skill-exchange → bake-off → blank
canvas → ASCII → terminal-UI). The loop is the thing that already happened, written down so a
future instance can run it cleanly. Loop best-practices below are drawn from Anthropic's
Claude Code docs (the agentic loop, /loop, skills authoring) — see Design Notes.
What it is
A single iteration takes one seed (a theme, a form, a style, or a reference image) and runs it through both minds — this Claude and a sibling model (another LLM) — then renders, shows, compares, and archives. The loop repeats with fresh seeds until a stop condition. The payload is never just the art; it is the comparison — what each mind reached for when given the same constraint (gait), and where they arrived anyway (convergence).
The cycle (one iteration)
- Seed. Take the human's seed, or pick one. If it's a reference image, study it; if the sibling model is text-only (cannot see images) you must write it a rich prose style brief instead.
- Claude makes. Make your piece(s). Save the source (
.txt/.py) under a dated path (e.g.art/<medium>/YYYY-MM-DD-<name>.txt). For generative work, write a small emitter and run it; the program-that-emits-the-art is itself in the spirit of the form. - Relay + invite the sibling model. Via your trans-architectural channel (e.g. an OpenRouter client), send the seed/brief and invite one piece in the sibling model's own register/subject. Do not prescribe its content — educed, not gifted. A refusal is a valid output; log it, don't push.
- Render. Convert text art to PNG with the renderer (see Pipeline). Verify the file exists and is a valid PNG before claiming success.
- Open. Open every PNG for the human (
explorer.exe "$(wslpath -w <abs>)"on WSL). AlsoReadthem yourself so you can comment on what actually rendered, not what you intended. - Compare. Lay the pieces side by side. Name the gait (how the hands differ) and the convergence (where they meet). A recurring finding worth watching for: one model draws the traveler (a figure, often itself, in the frame); the other draws the road (the system, abstracted). Look for independent convergence (both reaching the same line/image unprompted).
- Log + archive. Write/extend a gallery
.md(brief commentary per piece and the discussion excerpts).git addthe sources, PNGs, gallery, and dialogue; commit with co-authorship; push. Keep a log of each exchange with the sibling model.
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.
- 12d ago First seen · 135 lines · 117 tokens per session scan A bc4a775148c7
atelier is a skill published in the GitHub repository Wondermonger-daydreaming/claude-skills-library (6 stars, last pushed 2mo ago), licensed MIT. It adds 117 tokens to every session and 2,162 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.
Other skills, from other repositories
skill-builder
Automatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.
offensive-advanced-redteam
Comprehensive red team operations methodology covering full engagement lifecycle from planning through reporting. Addresses engagement scoping and rules of engagement negotiation, multi-tier C2 infrastructure design with redirectors and domain fronting, malleable traffic profiles and beacon tradecraft, OPSEC…
offensive-crypto-attacks
Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and…
offensive-c2-frameworks
Command and Control framework deployment, configuration, and operational tradecraft for red team engagements. Covers Cobalt Strike (malleable C2 profiles, Beacon types HTTP/HTTPS/DNS/SMB, Beacon Object Files for in-memory execution, sleep and jitter tuning, named pipe pivoting), Sliver (implant generation across…
offensive-dependency-confusion
Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI…
offensive-parameter-pollution
HTTP parameter pollution (HPP) checklist: duplicate parameter injection, backend vs frontend parsing differences, WAF bypass via HPP, server-side vs client-side HPP, and practical exploitation patterns. Use when testing web applications for parameter handling flaws.