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Anthropic visual style for plots, diagrams, slides, and web. Use when creating any visual output that should have Anthropic's look-and-feel — matplotlib charts, TikZ diagrams, HTML/CSS, or presentations.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
This skill should be used when the user asks to "commit and push", "commit push", "sync changes", "push changes", "commit and sync", or "update remote". Handles the full workflow of committing changes, pulling with rebase, and pushing to remote.
Sweep recent AI safety research from curated sources (Anthropic alignment science / red team, OpenAI, GDM, Apollo, Redwood, METR, FAR AI, Truthful AI, alphaxiv, arXiv) and surface items matching tracked topic terms (inoculation prompting, reward hacking, exploration hacking, metagaming, eval gaming, OOCR, scheming, alignment faking, sandbagging, etc.). Use when asked to "sweep AI safety", "what's new in alignment", "any recent papers on X", "weekly safety digest", or for staying current on AI safety literature.
Catch LLM-fabricated citations in BibTeX files. Verifies arXiv/OpenReview entries against live metadata (titles, first authors), then guides manual verification of authorless prose claims. Use before submitting papers, after any LLM-assisted citation generation, or when a reference smells off.
Fact-check prose claims in slides, reports, PDFs, and papers — statistics, comparatives, attributions, causal claims, quotes. Two-pass extract-then-verify protocol with strict numerical precision and a doc-only mode. Use when the user asks to "check the claims in this deck", "fact-check this report", "audit this PDF", "verify the numbers in these slides", or before publishing/shipping any externally-facing document with quantitative claims. Complements `check-bib-references` (which handles BibTeX entries) — this skill handles the prose around them.
Log a one-line knowledge gap to the project's gaps.md file. Use when the user is surprised by Claude's answer, says "I didn't know that", "wait what", or wants to record a misconception they just discovered. Format "I assumed X but actually Y". Personal misconception log — much higher learning signal than feedback memories.
Resurface a random sample of feedback memories for spaced-repetition review — "still true? changed? promote to global rule?". Use when user asks for feedback retrospective, weekly memory review, or to audit accumulated coaching corrections. Also good for periodic via /schedule.
SOC 職業分類に基づく
| name | anthropic-style |
| description | Anthropic visual style for plots, diagrams, slides, and web. Use when creating any visual output that should have Anthropic's look-and-feel — matplotlib charts, TikZ diagrams, HTML/CSS, or presentations. |
Use this skill when generating any visual output that should look Anthropic-branded: plots, charts, diagrams, slides, or web pages.
from anthro_colors import use_anthropic_defaults
use_anthropic_defaults()
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
# All plots now use Anthropic style automatically
This loads ~/.config/matplotlib/stylelib/anthropic.mplstyle which sets:
#FFFFFF)references/colors.md)Load the relevant reference for your output type:
| Domain | Reference | When |
|---|---|---|
| matplotlib | references/matplotlib.md | Python plots, charts, figures |
| Colors | references/colors.md | Color palette lookup for any domain — accent colors have AA text-tier variants; check it before coloring text (brand accents fail AA as text on Ivory) |
| HTML/CSS | references/web-css.md | Web pages, HTML artifacts |
| TikZ | references/tikz.md | LaTeX diagrams for papers |
| Annotations & layout | ~/.claude/docs/visual-layout-quality.md | Arrow anchoring, label placement in empty space, spacing minimums — read whenever adding annotations (callouts, gap markers, brackets) to any chart |
| Name | Hex | Use |
|---|---|---|
| DARK_ORANGE (BOOK_CLOTH) | #B86046 | Primary accent, first in cycle |
| GREY | #656565 | Secondary, neutral elements |
| DARK_BLUE | #40668C | Tertiary accent |
| SLATE (GREY_950) | #141413 | Text, axes |
| IVORY (GREY_050) | #FAF9F5 | Light backgrounds (brand) |
| CLAY | #D97757 | Warm accent |
| SKY | #6A9BCC | Cool accent |
| OLIVE | #788C5D | Nature/green accent |
Full palette with all 9 hue ramps (orange through red, 100-900 each) in references/colors.md.
All color values come from lib/plotting/anthro_colors.py — that file is the single source of truth. If a hex code here conflicts with that file, the file wins.