AI-powered adeno-associated virus (AAV) vector design for gene therapy including capsid engineering, promoter selection, and tropism optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Translate Figma designs into production-ready application code with 1:1 visual fidelity. Use for Figma URLs, node IDs, implementation requests, or components that must match Figma specs; use the local `figma` skill for general Figma MCP context and setup.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill provides a structured workflow for translating Figma designs into production-ready code with pixel-perfect accuracy. It ensures consistent integration with the Figma MCP server, proper use of design tokens, and 1:1 visual parity with designs.
https://figma.com/design/:fileKey/:fileName?node-id=1-2
:fileKey is the file key1-2 is the node ID (the specific component or frame to implement)figma-desktop MCP: User can select a node directly in the Figma desktop app (no URL required)Follow these steps in order. Do not skip steps.
When the user provides a Figma URL, extract the file key and node ID to pass as arguments to MCP tools.
URL format: https://figma.com/design/:fileKey/:fileName?node-id=1-2
Extract:
:fileKey (the segment after /design/)1-2 (the value of the node-id query parameter)Note: When using the local desktop MCP (figma-desktop), fileKey is not passed as a parameter to tool calls. The server automatically uses the currently open file, so only nodeId is needed.
Example:
https://figma.com/design/kL9xQn2VwM8pYrTb4ZcHjF/DesignSystem?node-id=42-15kL9xQn2VwM8pYrTb4ZcHjF42-15When using the figma-desktop MCP and the user has NOT provided a URL, the tools automatically use the currently selected node from the open Figma file in the desktop app.
Note: Selection-based prompting only works with the figma-desktop MCP server. The remote server requires a link to a frame or layer to extract context. The user must have the Figma desktop app open with a node selected.
Run get_design_context with the extracted file key and node ID.
get_design_context(fileKey=":fileKey", nodeId="1-2")
This provides the structured data including:
If the response is too large or truncated:
get_metadata(fileKey=":fileKey", nodeId="1-2") to get the high-level node mapget_design_context(fileKey=":fileKey", nodeId=":childNodeId")Run get_screenshot with the same file key and node ID for a visual reference.
get_screenshot(fileKey=":fileKey", nodeId="1-2")
This screenshot serves as the source of truth for visual validation. Keep it accessible throughout implementation.
Download any assets (images, icons, SVGs) returned by the Figma MCP server.
IMPORTANT: Follow these asset rules:
localhost source for an image or SVG, use that source directlylocalhost source is providedTranslate the Figma output into this project's framework, styles, and conventions.
Key principles:
Strive for pixel-perfect visual parity with the Figma design.
Guidelines:
Before marking complete, validate the final UI against the Figma screenshot.
Validation checklist:
User says: "Implement this Figma button component: https://figma.com/design/kL9xQn2VwM8pYrTb4ZcHjF/DesignSystem?node-id=42-15"
Actions:
kL9xQn2VwM8pYrTb4ZcHjF and nodeId=42-15get_design_context(fileKey="kL9xQn2VwM8pYrTb4ZcHjF", nodeId="42-15")get_screenshot(fileKey="kL9xQn2VwM8pYrTb4ZcHjF", nodeId="42-15") for visual referenceprimary-500, primary-hover)Result: Button component matching Figma design, integrated with project design system.
User says: "Build this dashboard: https://figma.com/design/pR8mNv5KqXzGwY2JtCfL4D/Dashboard?node-id=10-5"
Actions:
pR8mNv5KqXzGwY2JtCfL4D and nodeId=10-5get_metadata(fileKey="pR8mNv5KqXzGwY2JtCfL4D", nodeId="10-5") to understand the page structureget_design_context(fileKey="pR8mNv5KqXzGwY2JtCfL4D", nodeId=":childNodeId") for each major sectionget_screenshot(fileKey="pR8mNv5KqXzGwY2JtCfL4D", nodeId="10-5") for the full pageResult: Complete dashboard matching Figma design with responsive layout.
Never implement based on assumptions. Always fetch get_design_context and get_screenshot first.
Validate frequently during implementation, not just at the end. This catches issues early.
If you must deviate from the Figma design (e.g., for accessibility or technical constraints), document why in code comments.
Always check for existing components before creating new ones. Consistency across the codebase is more important than exact Figma replication.
When in doubt, prefer the project's design system patterns over literal Figma translation.
Cause: The design is too complex or has too many nested layers to return in a single response.
Solution: Use get_metadata to get the node structure, then fetch specific nodes individually with get_design_context.
Cause: Visual discrepancies between the implemented code and the original Figma design. Solution: Compare side-by-side with the screenshot from Step 3. Check spacing, colors, and typography values in the design context data.
Cause: The Figma MCP server's assets endpoint is not accessible or the URLs are being modified.
Solution: Verify the Figma MCP server's assets endpoint is accessible. The server serves assets at localhost URLs. Use these directly without modification.
Cause: The project's design system tokens have different values than those specified in the Figma design. Solution: When project tokens differ from Figma values, prefer project tokens for consistency but adjust spacing/sizing to maintain visual fidelity.
The Figma implementation workflow establishes a reliable process for translating designs to code:
For designers: Confidence that implementations will match their designs with pixel-perfect accuracy. For developers: A structured approach that eliminates guesswork and reduces back-and-forth revisions. For teams: Consistent, high-quality implementations that maintain design system integrity.
By following this workflow, you ensure that every Figma design is implemented with the same level of care and attention to detail.
This skill is written to stay usable across GitHub Copilot, Claude Code, and Codex.
$CODEX_HOME/skills/figma-implement-design and restart Codex after major changes.Preferred MCP Server: Figma MCP
figma-implement-design outside its documented task boundary.Before claiming the figma-implement-design workflow succeeded:
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概要と使いどころ
AI-powered adeno-associated virus (AAV) vector design for gene therapy including capsid engineering, promoter selection, and tropism optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Improve the clarity and voice of AI-assisted academic writing (papers, theses, rebuttals) and
日本語の概要は準備中です。原文の説明を表示しています。
12-agent academic paper writing pipeline. 11 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure/rebuttal-audit). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, audit my rebuttal, check my response draft, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見, 評估回覆, 논문 작성, 초록 작성, 논문 수정, 논문 계획을 도와줘, 심사 의견 반영, 답변서 점검, AI 사용 고지.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic writing framework for philosophy and interdisciplinary academic papers from optimized outline to submission-ready manuscript. Use when users want to: (1) write a paper from a detailed outline, (2) ensure quality control during writing, (3) maintain consistency across chapters, (4) prepare a submission-ready manuscript, or (5) systematically execute a planned paper. Triggered by phrases like 'write the paper from this outline,' 'compose the full manuscript,' 'execute the outline,' or when users have completed strategic planning (academic-paper-strategist skill) and are ready to write. Takes optimized outline as input; outputs complete manuscript with iterative quality checks.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-perspective academic paper review with dynamic reviewer personas. Runs a 5-seat, role-separated review panel (Journal-Fit Reviewer + 3 peer-review roles + Devil's Advocate) with field-specific expertise; role separation is not a claim of independent error processes. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy, 審查論文, 論文審查, 模擬審查, 同儕審查, 幫我審這篇, 以審查人角度評估, 審查者校準, 논문 심사, 동료 심사, 모의 심사, 심사자 관점에서 평가, 심사자 보정.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.
日本語の概要は準備中です。原文の説明を表示しています。