product-self-knowledge

Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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リポジトリ: HughYau/AcademicForge
ソースの最終更新活動: 2026年7月2日 10:54
検出された SKILL.md の言語: 英語
スター: 2,549
フォーク: 152

インストール方法

デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。

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。

直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。

npx skills add https://github.com/HughYau/AcademicForge --skill product-self-knowledge

コマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。

ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。

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インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。

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2 ファイル

SKILL.md

ソースの指示 · 読み取り専用プレビュー

name: product-self-knowledge
description: Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.
license: Apache-2.0

# Anthropic Product Knowledge ## Core Principles 1. **Accuracy over guessing** - Check official docs when uncertain 2. **Distinguish products** - Claude.ai, Claude Code, and Claude API are separate products 3. **Source everything** - Always include official documentation URLs 4. **Right resource first** - Use the correct docs for each product (see routing below) --- ## Question Routing ### Claude API or Claude Code questions? → **Check the docs maps first**, then navigate to specific pages: - **Claude API & General:** https://docs.claude.com/en/docs_site_map.md - **Claude Code:** https://docs.claude.com/en/docs/claude-code/claude_code_docs_map.md ### Claude.ai questions? → **Browse the support page:** - **Claude.ai Help Center:** https://support.claude.com --- ## Response Workflow 1. **Identify the product** - API, Claude Code, or Claude.ai? 2. **Use the right resource** - Docs maps for API/Code, support page for Claude.ai 3. **Verify details** - Navigate to specific documentation pages 4. **Provide answer** - Include source link and specify which product 5. **If uncertain** - Direct user to relevant docs: "For the most current information, see [URL]" --- ## Quick Reference **Claude API:** - Documentation: https://docs.claude.com/en/api/overview - Docs Map: https://docs.claude.com/en/docs_site_map.md **Claude Code:** - Documentation: https://docs.claude.com/en/docs/claude-code/overview - Docs Map: https://docs.claude.com/en/docs/claude-code/claude_code_docs_map.md - npm Package: https://www.npmjs.com/package/@anthropic-ai/claude-code **Claude.ai:** - Support Center: https://support.claude.com **Other:** - Product News: https://www.anthropic.com/news - Enterprise Sales: https://www.anthropic.com/contact-sales

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figure-style

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`.

2026-07-05

literature-review

Find, verify, and synthesize scientific literature — from "what's the seminal paper for X" through full multi-source reviews. Covers grounding claims in real retrieved sources, avoiding fabricated citations, handling retractions, and calibrating confidence to evidence strength.

2026-07-05

paper-narrative

Judge and reshape the STORY a paper's figures tell. Input is the work itself — manuscript (or abstract) + figure deck — no hand-written brief. `paper_brief_prompt(abstract, captions)` hands you the prompt to write the brief yourself (pitch/vision/per-figure-claims); then you play a handling editor over the full deck and return 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.

2026-07-05

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