llm.log: Skill for Claude Code

.agents/skills/teach-impeccable/SKILL.md

teach-impeccable is a skill for Claude Code from lanesket/llm.log. It costs 33 tokens per session (603 once invoked), scanned A, a copy of teach-impeccable, MIT.

A one-time project setup that gathers the product's users, goals, brand style, and existing design patterns, then saves the results as guidance for future AI work.

In plain words
What is it for?
Use it to inspect the codebase and answer remaining questions about users, purpose, personality, emotions, and visual references before setting persistent design guidelines.
Why use it?
It gives later design tasks a shared understanding of the project instead of making them repeat basic context gathering or rely on guesses.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool; installed under .agents/ (shared by several agents).

This is lanesket/llm.log's own configuration. It tells Claude Code how to work on llm.log itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything llm.log configures →

Reuse

Borrowing it

Nothing to install: this file belongs to lanesket/llm.log. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/lanesket/llm.log/main/.agents/skills/teach-impeccable/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/lanesket/llm.log

Made for: Claude Code.

Wrote 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.

agentmods badge for teach-impeccable

README.md
[![agentmods](https://agentmods.dev/badge/skills/lanesket/llm.log/teach-impeccable/github.svg)](https://agentmods.dev/skills/lanesket/llm.log/teach-impeccable)
Your own site
<a href="https://agentmods.dev/skills/lanesket/llm.log/teach-impeccable"><img src="https://agentmods.dev/badge/skills/lanesket/llm.log/teach-impeccable/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.

agentmods 80×15 button for teach-impeccable

Your own site · 80×15
<a href="https://agentmods.dev/skills/lanesket/llm.log/teach-impeccable"><img src="https://agentmods.dev/badge/skills/lanesket/llm.log/teach-impeccable.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 603 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 91% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00033 $0.00603
Opus 5 $0.00016 $0.00302
Sonnet 5 $0.00007 $0.00121
Haiku 4.5 $0.00003 $0.00060

Measured 9d ago against content hash 6a19c62d6efd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

teach-impeccable 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 9d 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.

Origin

This is a copy

91% identical to teach-impeccable — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/teach-impeccable/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

STOP and call the AskUserQuestion tool to clarify. 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]

Read the full file on GitHub · 71 lines

Changes

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.

  1. 9d ago First seen · 71 lines · 33 tokens per session scan A 6a19c62d6efd

Subscribe to this mod's changes

teach-impeccable is a skill published in the GitHub repository lanesket/llm.log (22 stars, last pushed 5mo ago), licensed MIT. It adds 33 tokens to every session and 603 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to teach-impeccable, differing in 7 lines, and is treated as a copy.

Related

Other skills, from other repositories