atelier: An atelier for your Agent: spec-driven workflows, deep thinking, and code quality

by martinffx · Claude Skill · ★ 50

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install atelier

bunx @martinffx/atelier@latest init
bunx @martinffx/atelier@latest init --all

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 70/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsagentic-codinganthropicclaude-codeclaude-skillscode-reviewcodexcodex-skillopencodeprompt-engineering

Quick Facts

Stars50
Forks5
LanguageTypeScript
CategoryClaude Skill
LicenseMIT
Quality Score70/100
Last Updated2026-11-07
Created2026-01-11
Platformsclaude-code, codex, node
Est. Tokens~16k

About atelier

Atelier An atelier is the private workshop or studio where a principal master and a number of assistants, students, and apprentices can work together producing fine art or visual art released under the master's name or supervision. Wikipedia A personal development toolkit for AI agents - spec-driven development, code quality, deep thinking, and ecosystem patterns.

Compatible Skills

These tools work well together with atelier for enhanced workflows:

  • Conductor-for-all — semantic(0.50)+complementary+rare_topics+same_lang+similar_pop+shared_platform (67%)
  • don-cheli-sdd — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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