Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Compose one publication-grade multi-panel figure. Entry from a one-line claim + data refs, OR from an existing figure via `derive_outline_task(png)`. Runs a per-figure loop: outline (12-col grid, per-panel ask + label_budget) → fan-out one Task subagent per panel (each loads `figure-style`) → tile + stamp letters → adversarial composite review with two-tier feedback (Tier-1 outline_revisions / Tier-2 per-panel violations) → regen affected panels, ≤3 rounds. Kernel exposes panel_task / compose_figure / compose_crops / composite_review_task / derive_outline_task (import by absolute path). For one standalone plot use `figure-style`; for whole-paper figure ordering use `paper-narrative`.
Publication-grade figure correctness and legibility rules. Load before drawing any plot and call `apply_figure_style()` — sets a role-mapped font-size ladder, outward ticks, frameless legends, and 300-dpi output. The skill is a checklist, not a house look: data fidelity (claim-titles tested against every row, excluded data never enters summaries), label economy (floor and ceiling), colour threading, chart-choice-by-data-shape, layout, and a render-then-verify QA loop (bbox collision + per-panel perceptual check). Ships helpers: focal_palette, bar_with_points, strip_with_median, end_of_line_labels, panel_letter, set_frame, panel_crops. For multi-panel figures load `figure-composer`; for whole-paper figure arc load `paper-narrative`.
Find, verify, and synthesize STEM literature across every field — from "what's the seminal paper for X" through full multi-source reviews. Treats journal articles, arXiv/preprints, and conference proceedings as first-class; grounds every claim in a retrieved source, never fabricates DOIs, checks for superseded/withdrawn/refuted work, calibrates confidence to evidence strength (including SOTA/reproduction/ablation caveats for CS and ML), and emits a tidy DOI-pinned BibTeX reference list. Pairs with the deep-researcher agent.
Judge and reshape the STORY a paper's figures tell. Input is the work itself — manuscript (or abstract) + figure deck — no hand-written brief. `derive_paper_brief_task(abstract, captions)` builds the prompt whose JSON is pitch/vision/per-figure-claims; a handling-editor reviewer on the full deck returns hook_verdict (would Fig 1 make me send this for review?), arc (hook→mechanism→evidence→application), figure_moves (panels in the wrong figure), missing_panels (concrete analyses to RUN), kill_list, and boldest_defensible_fig1. Hands per-figure claims to `figure-composer`. Load when writing or revising a paper.
Use this skill when the user has attached or pointed to a PDF, paper, report, or other document and the answer needs content from more than one place in it: summarize the methods or any other section, compare sections, find where a topic is discussed, read a value or label off a figure or chart, or find/list/extract every instance of something across the whole document (datasets, benchmarks, citations, figures, table rows, accession numbers — including appendices). It parses the PDF once in Python: pdf_pages (pages as persistent text), pdf_outline (TOC), and prepare/assemble helpers that fan whole-doc relevance scans / per-page maps / structured extraction out over Task subagents so the pages never fill your own context. Complementary to the built-in Read(pages=...), which attaches ≤20 PDF pages as ephemeral vision dropped after one turn — reach for this skill for persistent text, whole-doc sweeps, and structured extraction Read can't do. For PDF creation/manipulation use reportlab/pypdf directly. Deps: pip i
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.