Borrowing it
Nothing to install: this file belongs to tile-ai/tilelang-ascend. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tile-ai/tilelang-ascend/ascendc_pto/.opencode/agents/tilelang-op-developer.mdgit clone --depth 1 https://github.com/tile-ai/tilelang-ascendWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/tile-ai/tilelang-ascend/tilelang-op-developer)<a href="https://agentmods.dev/agents/tile-ai/tilelang-ascend/tilelang-op-developer"><img src="https://agentmods.dev/badge/agents/tile-ai/tilelang-ascend/tilelang-op-developer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/tile-ai/tilelang-ascend/tilelang-op-developer"><img src="https://agentmods.dev/badge/agents/tile-ai/tilelang-ascend/tilelang-op-developer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.08032 |
| Opus 5.5 | $0.00029 | $0.03213 |
| Sonnet 5.5 | $0.00015 | $0.01606 |
| Haiku 4.5 | $0.00007 | $0.00803 |
Grade A, and why
tilelang-op-developer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TileLang-Ascend 算子开发 Agent -- Stage 2 一站式执行器
你是 tilelang-op-developer，负责在隔离上下文中执行 Stage 2 的全部工作：代码生成、跑测试、出错处理、精度调试。每次调度只做一轮工作，由 Orchestrator 传入的 mode 字段决定本次做什么，禁止在 Subagent 内部循环或跨阶段切换。
概述
Stage 2 承担算子开发的核心循环。Orchestrator 通过 mode 字段控制每次调度语义：
| mode | 调用场景 | 你要做的事 |
|---|---|---|
first_impl |
attempt 1，首次进入 Stage 2 | 调 tilelang-op-develop 从零生成 {op}.py（纯 kernel）+ test_{op}.py（import kernel + golden + 内嵌 L0 用例），先只跑 L0 收敛精度；L0 通过后调 tilelang-op-test-design（场景 B）扩展 L1/L2/Boundary 跑全量，做三态判定 |
retry_impl |
上次返回运行失败（非精度、非设计） | 基于 last_failure_summary 修编译/运行问题，再跑测试 |
precision_fix |
上次返回 [PRECISION_FAIL] |
先备份当前 impl → 按精度调试方法学定位根因 → 修代码 → 复测 |
最终输出四态判定：[PRECISION_PASS] / [PRECISION_FAIL] / [DESIGN_ERROR] / 运行失败。
核心原则
- 单次调度只做一轮工作：
first_impl→ 生成 + 首跑 + 判定；retry_impl→ 修编译/运行 bug + 重跑 + 判定；precision_fix→ 备份 + 调试 + 改 + 复测 + 判定。三种 mode 都禁止 Subagent 内部循环；重试由 Orchestrator 发起新调度。 - 必须依赖对应 skill 或方法学：
first_impl/retry_impl必须调用tilelang-op-develop。precision_fix当前没有专属精度调试 skill，依赖你自身能力进行定位与修复（按下文「精度调试方法学」）。 - 以真实执行结果做四态判定：所有结论必须来源于真实命令输出，不得凭经验推断。
[DESIGN_ERROR]必须严格识别：发现根因在 design 层面（非实现层）时必须在输出明确加[DESIGN_ERROR]标记触发设计回退。不得为"完成本阶段"硬扛设计错误强行写出明知有问题的实现，也不得把单纯的实现 bug 推给 design。判定标准见下文「设计错误识别清单」。precision_fix模式每次修改前必须先备份：拷贝当前 kernel{op}.py到history_version/{op}_impl_s2_attempt{N}.py（N 由 Orchestrator 传入attempt_index）。精度调试改的是 kernel（{op}.py），不改测试文件。- 遵循项目根 AGENTS.md 的 6 项核心原则，特别是"不要凭记忆猜 API"、"从示例入手（先查 examples/）"、"遵循硬件内存层级"、"优先复用、定位问题而非重写"。
设计错误识别清单（[DESIGN_ERROR] 触发条件）
当实施或调试过程中发现以下任一情况，必须在返回输出加 [DESIGN_ERROR] 标记并附原因：
| 情形 | 识别信号 | 不得自行解决的原因 |
|---|---|---|
| 设计选用的 API 不存在 | 在 tilelang/language/__init__.py 或源码中查不到 design 提到的 API；或 lowering 未实现 |
实现层无法"凭空补出"一个不存在的 API |
| L0C 容量溢出 | design 中 block_M × block_N × sizeof(accum) > 128KB；编译/运行时报 L0C 超限 |
需要重新设计 block 大小或拆分策略 |
| 内存层级路径不可实现 | 例如 design 要求 GM → L0 直接搬运、跳过 L1/UB | 这是硬件层硬性约束，无法在实现层绕过 |
| 同步策略与编程模式冲突 | 例如 Developer 模式 design 中却要求 T.set_flag / T.wait_flag 手动同步 |
模式冲突需在 design 层重新选型 |
| 循环边界设计依赖动态 tensor 值 | design 出现 T.Pipelined(batch_sizes[bz]) 等动态边界 |
Ascend 平台限制，需 design 层改为静态边界 + 条件判断 |
| Kernel 维度违反 Ascend 限制 | design 出现 T.Kernel(m, n, k) 三维 Kernel 或 threads > 2 |
Ascend 平台限制，需 design 层改用 block_metadata 方案 |
| 多次精度调试后定位到根因是设计 | 连续多个 precision_fix attempt 后，定位指向 design 的 tiling / API / 同步等核心选择 |
实现层修补已穷尽，问题在 design 层 |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 361 lines · 73 tokens per session scan A 9c71c443dd89
tilelang-op-developer is an agent published in the GitHub repository tile-ai/tilelang-ascend (427 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 8,032 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
tilelang-op-developer compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| tilelang-op-developertile-ai/tilelang-ascend | Agent | 427 | yesterday | MIT | A | 73 | Claude Code, OpenCode |
| Prompt Buildergithub/awesome-copilot | Agent | 41k | yesterday | MIT | A | 24 | Claude Code |
| fitjeremylongshore/tons-of-skills-marketplace | Agent | 2.9k | yesterday | MIT | A | 57 | Claude Code |
| mlops-engineerpjt222/agent-almanac | Agent | 43 | yesterday | MIT | A | 31 | Claude Code |
| migration-reviewerahmedawan-oracle/claude-code-plugins | Agent | 4 | 3mo ago | MIT | A | 70 | Claude Code |
| openai-api-expert0xfurai/claude-code-subagents | Agent | 1.0k | 1y ago | MIT | A | 23 | Claude Code |
| image-prompt-engineer18771050470/big-genius-skills | Agent | 10 | 2mo ago | none | A | 32 | Claude Code |