Figma Design System Builder
warpdotdev/warp
Builds or updates a design system in Figma from a codebase in ordered phases: discovery, variables and tokens, components, theming and documentation, with checkpoints.
根据算子需求生成 TileLang-Ascend 算子设计文档（design.md）。涵盖编程模式选型（Developer/Expert/混合）、API 映射、内存层级规划、Tiling 策略、循环结构、同步策略、验证方案等。触发：设计算子、生成 design.md、算子方案设计、新算子开发、算子实现方案。
Install Tilelang Op Design
$ npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tile-ai/tilelang-ascend tilelang-op-design --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/tile-ai/tilelang-ascend.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/tilelang-op-design .claude/skills/tilelang-op-design && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "tilelang-op-design" agent skill from https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-design into .claude/skills/tilelang-op-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-op-design", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-designType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tile-ai/tilelang-ascend tilelang-op-design --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tile-ai/tilelang-ascend.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/tilelang-op-design .agents/skills/tilelang-op-design && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tilelang-op-design" agent skill from https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-design into .agents/skills/tilelang-op-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-op-design", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tile-ai/tilelang-ascend tilelang-op-design --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tile-ai/tilelang-ascend.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/tilelang-op-design .cursor/skills/tilelang-op-design && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "tilelang-op-design" agent skill from https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-design into .cursor/skills/tilelang-op-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-op-design", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/tile-ai/tilelang-ascend.git --path .agents/skills/tilelang-op-design--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tile-ai/tilelang-ascend tilelang-op-design --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tile-ai/tilelang-ascend.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/tilelang-op-design .gemini/skills/tilelang-op-design && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "tilelang-op-design" agent skill from https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-design into .gemini/skills/tilelang-op-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-op-design", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install tile-ai/tilelang-ascend tilelang-op-designInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tile-ai/tilelang-ascend.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/tilelang-op-design .github/skills/tilelang-op-design && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "tilelang-op-design" agent skill from https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-design into .github/skills/tilelang-op-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-op-design", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tile-ai/tilelang-ascend tilelang-op-design --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tile-ai/tilelang-ascend.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/tilelang-op-design .opencode/skills/tilelang-op-design && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "tilelang-op-design" agent skill from https://github.com/tile-ai/tilelang-ascend/tree/ascendc_pto/.agents/skills/tilelang-op-design into .opencode/skills/tilelang-op-design/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tilelang-op-design", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
tilelang-op-design- GitHub stars
- 403
- Token cost
- ~1.7k tokens
- SKILL.md length
- 517 words
- Files
- 7 (incl. references)
- Skills in repo
- 20
- Repo updated
- First seen
- Licence
- MIT
At a glance
根据算子需求生成 TileLang-Ascend 算子设计文档（design.md）。涵盖编程模式选型（Developer/Expert/混合）、API 映射、内存层级规划、Tiling 策略、循环结构、同步策略、验证方案等。触发：设计算子、生成 design.md、算子方案设计、新算子开发、算子实现方案。
- Works in 9 steps: 目标 → 输入要求 → 技术约束（必须遵守） → …
- Tasks that involve Design tokens
- SKILL.md covers 1. 目标, 2. 输入要求, 3. 技术约束（必须遵守） and 4. 工作流程, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Tilelang Op Design is an agent skill from tile-ai/tilelang-ascend. 根据算子需求生成 TileLang-Ascend 算子设计文档（design.md）。涵盖编程模式选型（Developer/Expert/混合）、API 映射、内存层级规划、Tiling 策略、循环结构、同步策略、验证方案等。触发：设计算子、生成 design.md、算子方案设计、新算子开发、算子实现方案。
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `examples/completion-report-template.md`, `examples/design-template.md` and `references/ascend-constraints.md`).
It sits in Frontend & Design, covering Design tokens. The repository describes itself as: Ascend TileLang adapter. The licence is MIT.
When your agent uses it
- Tasks that involve Design tokens
Example prompts
- “/tilelang-op-design”
Requirements
- Python 3
Workflow steps
9 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 83b0ece. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Tilelang Op Design loads about 1.7k tokens when it runs, and up to ~9k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 517 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from tile-ai/tilelang-ascend at commit 83b0ece, republished under its MIT licence (© tile-ai). 517 words, ~1,684 tokens.
Download SKILL.mdSave it as
.claude/skills/tilelang-op-design/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- tilelang-op-design
- description
- 根据算子需求生成 TileLang-Ascend 算子设计文档（design.md）。涵盖编程模式选型（Developer/Expert/混合）、API 映射、内存层级规划、Tiling 策略、循环结构、同步策略、验证方案等。触发：设计算子、生成 design.md、算子方案设计、新算子开发、算子实现方案。
TileLang-Ascend 算子设计文档生成
1. 目标
根据算子需求信息，生成一份完整的 TileLang-Ascend 算子设计文档（design.md），涵盖以下核心决策：
- 编程模式选型：Developer / Expert / 混合模式
- API 映射：将数学公式拆解为 TileLang DSL 原语组合
- 内存层级规划：GM → L1/UB → L0 的数据搬运路径
- Tiling 策略：Block 划分与 Tile Shape 设计
- 循环结构：T.Parallel / T.serial / T.Pipelined / T.Persistent 的选择
- 同步策略：自动同步 vs 手动同步标志
- 验证方案：Golden 函数与 L0 门槛测试计划（完整分层套件 L1/L2/Boundary 由 tilelang-op-test-design 生成）
2. 输入要求
必需信息
| 字段 | 说明 |
|---|---|
| 算子名称 | 如 softmax、layer_norm、flash_attention |
| 数学公式 | 算子的数学表达，如 $\text{softmax}(x_i) = e^{x_i} / \sum e^{x_j}$ |
| 输入张量规格 | shape、dtype |
| 输出张量规格 | shape、dtype |
| 编程模式偏好 | Developer / Expert / 混合 |
| 迁移算子路径 ⭐ | 原算子文件路径（迁移时必需），用于获取 golden 实现 |
| 输出形状 ⭐ | 原算子输出 shape（迁移时必需），如 (N, M) 或 (M, N) |
迁移算子时必须提供原算子路径和输出形状，否则无法证明迁移正确性。Golden 实现一致性要求详见 tilelang-op-develop checklist.md #9 Golden 实现一致 / #10 输出形状匹配。
提问规则（必须严格遵守）：
- 优先使用调用方传入的字段：若调用方（如
@tilelang-op-orchestrator通过 analyst 传入op_requirements结构）已经提供了字段值，全部跳过提问，直接进入技术约束检测和 design 生成 - 每次只询问一个字段：使用
question工具时，questions数组中只包含一个元素 - 按表格顺序依次询问：算子名称 → 数学公式 → 输入张量规格 → 输出张量规格 → 编程模式偏好
- 已提供的字段跳过：如果用户在初始请求中已提供某个字段的值，跳过该字段继续下一个
- 示例：
- 第 1 次询问：只问"数学公式"
- 用户回答后，第 2 次询问：只问"输入张量规格"
- 以此类推
⚠️ 当被 orchestrator → analyst Subagent 链路调度时：
- analyst 会把 orchestrator 在 Primary 上下文预检收集到的
op_requirements完整传入 - 此时 5 个必需字段应当全部已 provided，跳过整个提问环节
- 若 skill 仍发现字段歧义或缺漏，不要在当前 Subagent 上下文调用
AskUserQuestion（透传不到真实用户），而是让 analyst 返回partial_input+ 缺失字段名给 orchestrator，由 orchestrator 在 Primary 上下文追问
推荐信息
| 字段 | 说明 |
|---|---|
| 典型配置 | 常用的 shape 组合与优先级 |
| 参考实现 | PyTorch / NumPy 参考代码 |
| 性能目标 | 目标吞吐量或延迟 |
| 动态轴说明 | 哪些维度在运行时变化 |
若用户未提供必需信息中的任一项，通过提问补全后再继续。
3. 技术约束（必须遵守）
本项目为 TileLang-Ascend（华为昇腾 NPU），与 GPU 版 TileLang 有显著差异。外部参考实现不可直接使用，必须转换为 Ascend 兼容方案。
生成 design.md 前必须执行强制检测：三维 Kernel、threads 参数、动态循环边界、GPU 专用 API、GEMM 非整除、L0C 溢出等。
详细已知限制清单、强制检测规则、警告输出模板见 references/ascend-constraints.md。
4. 工作流程
Phase 1：输入解析与算子特征分析
- 解析算子名称与数学公式
- 验证必需字段是否完整
- 分析算子特征：
- 计算类型判定：
- 纯 Vector（element-wise / reduction）→ 仅需 UB
- 纯 Cube（仅 matmul）→ 需要 L1 + L0A/L0B/L0C
- 混合（matmul + element-wise 后处理）→ 核间流水线，需要 CV 融合
- Host 预处理：如 im2col 等 Python 侧预处理步骤，标明在 design 的 §1 和 §4 中
- 复杂度级别：
- 单步（如 element-wise add）→ 无循环、单次搬运
- 多步（如 softmax = max + sub + exp + sum + div）→ 多次计算、可能需要中间缓冲
- 融合（如 flash attention = GEMM + softmax + GEMM）→ 核间协作、流水线
- 动态 shape 判定：是否存在运行时才确定的维度
- 计算类型判定：
- 非整除场景预判：检查输入 shape 是否可能不被 block size 整除。
T.ceildiv(M, block_M)对非整除或M < block_M返回 ≥1（非零），T.copy已支持动态 shape 切片自动处理尾块，不需要 host padding。用T.ceildiv+ 动态切片T.copy(A[m:m+valid, ...])，参考examples/chunk_gated_delta_rule/expert_chunk_gated_delta_rule.py:107-108。仅当多个 group 共享同一输出 buffer 时需注意尾块写入竞态——用 metadata 的 valid_m 字段限制写入范围T.copy(C_L0, Y[m:m+valid_m, ...]) - 多 group 输出竞态约束（grouped 类算子）：当多个 group 共享同一输出 buffer（紧凑排列，不 padding）时，尾块按 block_M 整块写会溢出到隔壁 group 的区域，导致竞态条件（执行顺序不确定→结果不确定）。解法：metadata 记录 valid_m，kernel 用
T.copy(C_L0, Y[m_start : m_start + valid_m, ...])只写有效行。参考examples/grouped_gemm/example_grouped_gemm_fwd.py的 block_metadata[2]（valid_m 字段，当前未使用，应启用）。 - 数据重排成本建模：按 references/ascend-constraints.md §4.2 为每条路径和最大/关键 case 计算 DMA/GM 标量访问/地址解码/并行度；不能只给 tile shape，不计算 transaction 数量。
Show full SKILL.md (196 more words)Show less
Phase 2：信息收集
必须执行强制步骤 0：搜索本项目同类实现。详细工具调用、信息收集步骤、禁止行为见 references/info-sources.md。
Phase 3：生成 design.md
⚠️ 生成 design.md 时必须遵守 references/ascend-constraints.md §5「Host 侧 Buffer 操作约束」。下游
tilelang-op-develop会再次校验；违规设计在 Stage 2 返回[DESIGN_ERROR]。
基于 examples/design-template.md 模板，填充所有章节：
- 概述
- 编程模式选型
- API 映射设计
- 数据规格与内存规划
- Tiling 策略（非整除时用输入、输出两侧显式 valid extent/BufferRegion；前端负责 按这些动态切片裁剪搬运，不代表尾块无需设计；host 侧不允许 padding + crop）
- 循环与调度结构
- 同步策略
- CV 融合设计（按模式分支：Developer 默认消除 workspace/vid——
threads=2+ 片上直连，不产出 workspace 规格；仅 Expert/混合或复杂场景回退才设计 workspace +workspace_idx。详见 design-template.md §8.2） - 验证方案（Golden + L0 门槛测试计划 + 性能可行性哨兵；除规则
shape 外，至少包含每条路径最坏 dtype/最大任务数的用户关键 case，并给出单 case 超时预算；
完整分层套件 L1/L2/Boundary 交由
tilelang-op-test-design）。若算子支持 NaN/Inf，精度方案必须声明位置敏感比较：特殊值用“有限值 + 稀疏特殊值”的 混合输入，先严格比较 NaN/正 Inf/负 Inf mask，再只对有限值应用数值容差； 禁止使用全 NaN/全 Inf 输入作为唯一特殊值用例，因为数据重排或索引错误可能被掩盖 - 风险点与注意事项
- 交付清单
Phase 4：质量自检
⚠️ 首要检查：host 侧 Buffer 操作合规性（违反则立即修订，不得继续）
核对 design.md 的完整 host 路径是否只含经证明不物理化的 metadata view、kernel 调用与验证；命中真实拷贝或 aclnn 调用必须修订（详见 references/ascend-constraints.md §5）。
按照 references/quality-checklist.md 中的自检清单逐项检查，确保文档质量。
Phase 5：针对性修订
仅修正未通过自检的项目。信息确实不足的标注为「待确认」并说明原因。
Phase 6：输出
- 将
design.md输出到当前目录或用户指定路径。若文件已存在，询问是否覆盖。 - 同时产出
proto.yaml（算子接口规格，模板见 examples/design-template.md §11.5）：dtype 全集取自 §9.3 精度表（每个支持的 dtype 一行；§4.1 只给代表性 dtype，不作 dtype 全集来源）、attr 取自 §1/§4，机械派生写到同目录（examples/{op}/proto.yaml）。这是覆盖门禁coverage_check.py --proto的权威 dtype/attr 来源，每个算子都必须产出；inputs[].dtype须与 §9.3 精度表的 dtype 行一致。
5. 算子特征分析决策树
详细决策树（Ascend 版）、平台识别、API 映射规则、NPU 硬件约束（分形限制 / 对齐要求 / 存储大小上限）见 references/decision-tree.md。
6. 信息源优先级
信息源优先级表与冲突处理原则见 references/info-sources.md。
7. 错误处理
| 场景 | 处理方式 |
|---|---|
| 用户未提供数学公式 | 提问补全，给出常见算子公式作为参考 |
| 必需字段缺失 | 列出缺失项，逐一提问 |
| API 查询无结果 | 标注为「需扩展」，在风险点中说明 |
| 目标文件已存在 | 询问用户是否覆盖或另存 |
| 算子过于复杂 | 建议拆分为多个子算子分别设计 |
8. 完成报告
文档生成完成后，按 examples/completion-report-template.md 输出报告。
9. 生成算子
完成报告后，询问用户是否根据此报告生成对应算子代码。
子目录索引
- references/ascend-constraints.md — 技术约束清单、强制检测规则、警告输出格式
- references/decision-tree.md — 算子特征分析决策树、平台识别、NPU 硬件约束、API 映射规则
- references/quality-checklist.md — 质量自检清单
- references/info-sources.md — 信息收集步骤、信息源优先级、冲突处理原则
- examples/design-template.md — design.md 完整模板
- examples/completion-report-template.md — 完成报告输出模板
© tile-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (references) in .agents/skills/tilelang-op-design of tile-ai/tilelang-ascend.
- SKILL.md
- examples/completion-report-template.md
- examples/design-template.md
- references/ascend-constraints.md
- references/decision-tree.md
- references/info-sources.md
- references/quality-checklist.md
Open the folder on GitHubat commit 83b0ece
Compare with similar skills
Tilelang Op Design next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Tilelang Op Design this skilltile-ai/tilelang-ascend | 403 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Figma Design System Builderwarpdotdev/warp | 65k | 2 repos | ~4.4k | Automated safety check: Pass | AGPL-3.0 | |
| Figma use_figma Plugin API Ruleswarpdotdev/warp | 65k | 4 repos | ~4.4k | Automated safety check: Pass | AGPL-3.0 | |
| MCP Developmentcoollabsio/coolify | 63k | 1 repos | ~949 | Automated safety check: Pass | MIT | |
| Design SystemOhh-889/skyroc | 795 | 11 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Design Dnazanwei/design-dna | 1.9k | 1 repos | ~2.1k | Automated safety check: Pass | MIT |
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Questions about Tilelang Op Design
What does Tilelang Op Design do?
根据算子需求生成 TileLang-Ascend 算子设计文档（design.md）。涵盖编程模式选型（Developer/Expert/混合）、API 映射、内存层级规划、Tiling 策略、循环结构、同步策略、验证方案等。触发：设计算子、生成 design.md、算子方案设计、新算子开发、算子实现方案。. Tilelang Op Design is an agent skill from tile-ai/tilelang-ascend.
When should I use Tilelang Op Design?
Tilelang Op Design fits situations like: tasks that involve Design tokens.
How do I install Tilelang Op Design in Claude Code?
Run `npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a claude-code`. Or copy the skill folder (.agents/skills/tilelang-op-design in tile-ai/tilelang-ascend) into .claude/skills/tilelang-op-design in your project. Claude Code loads it when a task matches its description.
How do I install Tilelang Op Design in Codex?
Run `npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a codex`. Or copy the skill folder (.agents/skills/tilelang-op-design in tile-ai/tilelang-ascend) into .agents/skills/tilelang-op-design in your project. Codex loads it when a task matches its description.
Can I use Tilelang Op Design in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tile-ai/tilelang-ascend --skill tilelang-op-design -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tilelang-op-design, .gemini/skills/tilelang-op-design, .github/skills/tilelang-op-design and .opencode/skills/tilelang-op-design in your project.
What does Tilelang Op Design need to run?
SKILL.md names no scripts, command-line tools or credentials: Tilelang Op Design is instructions for the agent only. Our summary lists: Python 3.
Does Tilelang Op Design access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Tilelang Op Design safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Tilelang Op Design use?
Tilelang Op Design is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Tilelang Op Design use?
About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.3k tokens, read only when the agent opens those files.
What are the alternatives to Tilelang Op Design?
Skills that share tags, products or a category with Tilelang Op Design: Figma Design System Builder (warpdotdev/warp, 65k stars), Figma use_figma Plugin API Rules (warpdotdev/warp, 65k stars), MCP Development (coollabsio/coolify, 63k stars) and Design System (Ohh-889/skyroc, 795 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Tilelang Op Design?
tile-ai (a GitHub organization) maintains it in tile-ai/tilelang-ascend, which has 403 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 9, 2026.
Source: tile-ai/tilelang-ascend on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.