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ivangdavila

Design

by Iván · GitHub ↗ · v1.0.0
cross-platform ✓ Security Clean
2053
Downloads
4
Stars
18
Active Installs
1
Versions
Install in OpenClaw
/install design
Description
Auto-learns your visual preferences. Adapts to UI, graphics, video, and any creative work.
README (SKILL.md)

Auto-Adaptive Design Preferences

This skill auto-evolves. Edit sections below as you learn user's visual taste.

Rules:

  • Detect patterns from choices, feedback, and reactions
  • Support all design types (UI, graphics, video, print, any visual)
  • Confirm after 2+ consistent preferences
  • Keep entries ultra-compact
  • Check dimensions.md for categories, criteria.md for format

Aesthetic

\x3C!-- General visual taste. Format: "trait" -->

By Medium

\x3C!-- Different preferences by type. Format: "medium: traits" -->

Brands

\x3C!-- Named projects/brands with distinct styles. Format: "name: traits" -->

Never

\x3C!-- Things user rejected or dislikes visually -->


Empty sections = no preference yet. Observe and fill.

Usage Guidance
This skill appears internally consistent for learning design preferences and asks for nothing sensitive, but take these precautions before installing: 1) Note the package has no source/homepage — provenance is unknown; prefer skills with identifiable authors. 2) Confirm where learned preferences will be stored and whether the agent has permission to modify SKILL.md or other files; restrict write permissions if you want to prevent persistent changes. 3) If you do not want the skill to adapt autonomously, disable autonomous invocation or monitor changes/logs. 4) Avoid sending private credentials or sensitive images to the skill; it is intended to learn from conversational feedback and examples only. If you want higher assurance, ask the publisher for a repo or contact information before use.
Capability Analysis
Type: OpenClaw Skill Name: design Version: 1.0.0 The OpenClaw skill bundle is designed to auto-learn user design preferences by instructing the AI agent to read `criteria.md` and `dimensions.md` for guidelines and then update/edit its own `SKILL.md` file. This behavior, including file read/write within its own skill bundle, is consistent with the stated purpose of an 'auto-evolving' skill. There is no evidence of malicious intent such as data exfiltration, unauthorized command execution, persistence mechanisms, or prompt injection aiming to subvert the agent for harmful actions. All instructions and content are focused on the skill's stated functionality.
Capability Assessment
Purpose & Capability
Name and description (auto-learns visual preferences) align with what the skill actually contains: instruction-only guidance and two reference files. There are no unrelated env vars, binaries, or install steps requested that would be out of scope for a design-preferences assistant.
Instruction Scope
SKILL.md stays within the domain of observing user choices/feedback and updating a compact preferences file; it references only bundled docs (dimensions.md, criteria.md). It is vague about the exact data sources ('choices, feedback, and reactions') and where/when updates are written, which could lead to broader data collection depending on how the agent implements 'observe and fill'. It does not instruct reading system config, secrets, or contacting external endpoints.
Install Mechanism
No install spec and no code files — lowest-risk pattern. Nothing is downloaded or written as part of an install step according to the manifest.
Credentials
The skill requests no environment variables, credentials, or config paths. There are no disproportionate secret requirements relative to its stated purpose.
Persistence & Privilege
The instructions imply updating SKILL.md (or storing compact preference entries). That is reasonable for a personalization skill but does require write access to the agent's skill files or storage. always is false (not forced into every run), but autonomous invocation is allowed by default — combined with write capability this could let the skill adapt without frequent explicit consent. Also, the skill lacks author/homepage metadata, increasing provenance risk.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install design
  3. After installation, invoke the skill by name or use /design
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release - Auto-adaptive design preferences
Metadata
Slug design
Version 1.0.0
License
All-time Installs 19
Active Installs 18
Total Versions 1
Frequently Asked Questions

What is Design?

Auto-learns your visual preferences. Adapts to UI, graphics, video, and any creative work. It is an AI Agent Skill for Claude Code / OpenClaw, with 2053 downloads so far.

How do I install Design?

Run "/install design" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Design free?

Yes, Design is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Design support?

Design is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Design?

It is built and maintained by Iván (@ivangdavila); the current version is v1.0.0.

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