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.
curl -O https://raw.githubusercontent.com/lanesket/llm.log/main/.agents/skills/teach-impeccable/SKILL.mdgit clone --depth 1 https://github.com/lanesket/llm.logWrote 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.
[](https://agentmods.dev/skills/lanesket/llm.log/teach-impeccable)<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.
<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>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00603 |
| Opus 5.5 | $0.00013 | $0.00241 |
| Sonnet 5.5 | $0.00007 | $0.00121 |
| Haiku 4.5 | $0.00003 | $0.00060 |
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 1mo 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.
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.
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]
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.
- 1mo ago First seen · 71 lines · 33 tokens per session scan A 6a19c62d6efd
teach-impeccable is a skill published in the GitHub repository lanesket/llm.log (25 stars, last pushed 6mo ago), licensed MIT. It adds 33 tokens to every session and 603 once invoked, about $0.0001 per session on Opus 5.5. 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.
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