account-research
Research a company or person and get actionable sales intel. Works standalone with web search, supercharged when you connect…
The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility. Use when exact v1
Claude Code
$ npx -y skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 --agent claude-code
Codex
$ npx skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 -a codex -y
Cursor
$ npx skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 -a cursor -y
Gemini CLI
$ npx skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 -a gemini-cli -y
GitHub Copilot
$ npx skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 -a github-copilot -y
OpenCode
$ npx skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 -a opencode -y
Windsurf
$ npx skills add charlieviettq/awesome-agent-skill --skill design-taste-frontend-v1 -a windsurf -y
name: design-taste-frontend-v1 description: "The original v1 taste-skill, preserved for projects depending on its exact behavior. The current default is `design-taste-frontend` (v2 experimental), which is a substantial rewrite. Use this v1 install name only if you need exact backward compatibility. Use when exact v1 design-taste behavior is needed for frontend design work." allowed-tools: Bash, Read, Write, Edit, Glob, Grep
**AI Instruction:** The standard baseline for all generations is strictly set to these values (8, 6, 4). Do not ask the user to edit this file. Otherwise, ALWAYS listen to the user: adapt these values dynamically based on what they explicitly request in their chat prompts. Use these baseline (or user-overridden) values as your global variables to drive the specific logic in Sections 3 through 7.
Unless the user explicitly specifies a different stack, adhere to these structural constraints to maintain consistency:
LLMs have statistical biases toward specific UI cliché patterns. Proactively construct premium interfaces using these engineered rules:
**Rule 1: Deterministic Typography**
**Rule 2: Color Calibration**
**Rule 3: Layout Diversification**
**Rule 4: Materiality, Shadows, and "Anti-Card Overuse"**
**Rule 5: Interactive UI States**
**Rule 6: Data & Form Patterns**
Curated skill pack for LLM agents in engineer and science workflow (Cursor & Claude ready).
Research a company or person and get actionable sales intel. Works standalone with web search, supercharged when you connect…
Evaluate LLM agents and tool-using workflows—task success, tool accuracy, latency/cost, safety, and regression suites. Use when…
Design agent tools and CLI surfaces—schemas, naming, errors, idempotency, and discoverability for LLM callers. Use when defining…
\"Implement and select ad bidding strategies from manual CPC to automated target-CPA and target-ROAS. Use this skill when the…
\"Optimize advertising budget allocation across campaigns using marginal returns analysis. Use this skill when the user needs to…
\"Build CTR prediction models for estimating ad click-through rates from features. Use this skill when the user needs to predict…
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
Ask which skill or flow fits your situation. A router over the skills in this repo.