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24 TEACH IMPECCABLE

Skill subhansh-dev/agent-maxxing/agent-meta/24-TEACH-IMPECCABLE

95+ agent skills, 19 UI components, 7 system prompts from Claude Fable 5, GPT-5.5, Gemini CLI & more. Self-fine-tune your agent: paste one prompt and it reads every skill, internalizes patterns, and becomes elite. Works with Claude Code, Codex, Cursor, OpenCode + 60 more agents.

Install
npx -y skills add subhansh-dev/agent-maxxing --skill 24-TEACH-IMPECCABLE

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 29 days oldThe repository was created 29 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.

SKILL.md

2.8 KB, 565 tokens by cl100k_base, as published. Nobody here has run it

Gather design context for this project, then persist it for all future sessions.

Step 1: Explore the Codebase

Before asking questions, thoroughly scan the project to discover what you can:

  • README and docs: Project purpose, target audience, any stated goals
  • Package.json / config files: Tech stack, dependencies, existing design libraries
  • Existing components: Current design patterns, spacing, typography in use
  • Brand assets: Logos, favicons, color values already defined
  • Design tokens / CSS variables: Existing color palettes, font stacks, spacing scales
  • Any style guides or brand documentation

Note what you've learned and what remains unclear.

Step 2: Ask UX-Focused Questions

ask the user directly to clarify what you cannot infer. Focus only on what you couldn't infer from the codebase:

Users & Purpose

  • Who uses this? What's their context when using it?
  • What job are they trying to get done?
  • What emotions should the interface evoke? (confidence, delight, calm, urgency, etc.)

Brand & Personality

  • How would you describe the brand personality in 3 words?
  • Any reference sites or apps that capture the right feel? What specifically about them?
  • What should this explicitly NOT look like? Any anti-references?

Aesthetic Preferences

  • Any strong preferences for visual direction? (minimal, bold, elegant, playful, technical, organic, etc.)
  • Light mode, dark mode, or both?
  • Any colors that must be used or avoided?

Accessibility & Inclusion

  • Specific accessibility requirements? (WCAG level, known user needs)
  • Considerations for reduced motion, color blindness, or other accommodations?

Skip questions where the answer is already clear from the codebase exploration.

Step 3: Write Design Context

Synthesize your findings and the user's answers into a ## Design Context section:

## Design Context

### Users
[Who they are, their context, the job to be done]

### Brand Personality
[Voice, tone, 3-word personality, emotional goals]

### Aesthetic Direction
[Visual tone, references, anti-references, theme]

### Design Principles
[3-5 principles derived from the conversation that should guide all design decisions]

Write this section to .impeccable.md in the project root. If the file already exists, update the Design Context section in place.

Then ask the user directly to clarify what you cannot infer. whether they'd also like the Design Context appended to .github/copilot-instructions.md. If yes, append or update the section there as well.

Confirm completion and summarize the key design principles that will now guide all future work.

Gives 0 of the 12 instructions most project setup skills give in 565 tokens

Counted across 999 of the 1,637 authors here whose files we hold, read 2026-08-07

  • ask one question at a timein 29 of 999, across 28 files
  • detect the package manager from lockfilesin 28 of 999, across 9 files
  • present findings to the userin 26 of 999, across 5 files
  • explore current repo statein 24 of 999, across 3 files
  • update the agent skills block in place if it existsin 24 of 999, across 3 files
  • install husky lint-staged and prettierin 23 of 999, across 4 files
  • create the lintstagedrc filein 22 of 999, across 3 files
  • commit all changed filesin 22 of 999, across 3 files
  • run lint-staged to verify it worksin 22 of 999, across 3 files
  • create the husky pre-commit filein 21 of 999, across 2 files
  • create a prettierrc file if missingin 21 of 999, across 2 files
  • initialize huskyin 21 of 999, across 2 files

Said here and by no other author read

  • ask the user to clarify unclear design context
  • ask to append the context to copilot instructions
  • append or update the section there if requested

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.