cake

Plugin cake from marketplace cannbot in catman626/cannbot-skills. Commands read from the repo's manifest — 19 days ago.

Skills (19)

• ascend-call-generation

  Generate AscendC project scaffold (pybind, CMake, host code, kernel skeleton) from functional PyTorch for pure Vector operators. Use after functional-conversion, before dsl-baseline-generation.

• ascendc-evaluation

  Multi-case operator evaluation with precision testing and performance profiling, use when you want to evaluate the performance and correctness of your AscendC operator implementation.

• ascendc-op-debug

  Unified AscendC operator runtime debug skill. Diagnose precision errors, runtime crashes, hangs, and multicore inconsistencies using a hypothesis-driven protocol with 3-layer evidence (code review → log analysis → tools). Covers hypothesis patterns for Vector operators (cache line conflict, workspac

• cake-code-review

  Review AscendC kernel code for structural red-line violations (P0–P3) and algorithm correctness. Use after dsl-lowering, before ascendc-evaluation. Outputs rectification report; guides fix → recompile → unit test → system test.

• cake-docs-search

  Ascend C 开发资源检索技能。通过本地 API 文档索引、示例代码映射和在线文档兜底搜索定位开发资料，优先查本地、缺失时再查在线。当需要查询 API 用法、示例代码、兼容性信息、官方资料入口或定位文档来源时使用。本技能（含 scripts/ 脚本）源自 cannbot-skills 仓库（gitcode.com/cann/cannbot-skills）的 ops/ascendc-docs-search，重命名而来，为自研代码。

• cake-evo

  Evolutionary AscendC operator generation — spawn parallel variants with different optimization strategies and select the best. Use as the top-level orchestrator for multi-round kernel optimization. 触发：需要多轮并行进化以优化内核性能时。

• cake-review

  Comprehensive review of the entire kernel generation process after all stages complete. Analyzes problems encountered during generation, compile/environment issues, and skill/agent document quality. Produces a REVIEW.md in the kernel output directory. Use when a formal review of the kernel generatio

• code-performance-advisor

  Diagnose AscendC kernel performance bottlenecks from profiling data (msprof). Matches expert rules first, falls back to LLM analysis. Use when speedup is below target after correctness passes.

• dsl-baseline-generation

  Generate initial AscendDSL code (class structure, compute, tiling) from functional PyTorch for pure Vector operators. Use after ascend-call-generation creates the project scaffold.

• dsl-lowering

  Translate the operator DSL into AscendC code through multiple passes. Also used when diagnosing compilation errors.

• dsl-optimization

  Iteratively optimize AscendDSL code for performance — tiling tuning, vectorization, pipeline adjustments. Use after evaluation shows correctness passes but speedup is below target.

• functional-conversion

  Convert PyTorch nn.Module reference implementation to stateless functional API (module_fn + get_inputs). Use after reference-generation, before ascend-call-generation.

• git-version-management

  Git 版本管理 - 算子工作区初始化、逐阶段提交、worktree 并行隔离与审计追踪

• op-dashboard

  Generate self-contained interactive HTML dashboard (4 tabs: algo flow, UB tiling, precision, performance) from an AscendC operator output directory. Use when asked to visualize or report operator results. Works for both precision-pass and precision-fail states.

• op-desc-generation

  Generate operator description JSON (shapes, dtypes, attributes) from API description or user specification. First step in the cake agent pipeline.

• reference-generation

  Generate reference PyTorch implementation (nn.Module with get_init_inputs/get_random_inputs) from operator description JSON. Faithfully reproduces the Golden definition when provided. Use after op-desc-generation.

• remote-cann-development

  Unified remote NPU development — sync, exec, and test across multiple NPU backends (docker containers, hdspace cloud) via a single Python CLI. Use when: (1) syncing code to any remote NPU server (2) executing build/test commands on remote NPU (3) probing NPU platform info (4) managing multiple remot

• skill-trace

  Track skill invocations, durations, and outcomes during operator generation. Records which skills were called, their inputs/outputs, and correlates with final results. MUST use when: (1) Starting any skill step, (2) Completing any skill step, (3) Final summary to correlate skills with outcomes.

• task-progress

  Track and manage task progress via a PROGRESS.md. MUST use when: (1) Starting a new task or operator workflow, (2) Entering or completing any step/stage/substage, (3) After context compaction or reset — read PROGRESS.md first to recover state. Also call when the user asks about current progress or s

Subagents (3)

• cake-evo

  AscendC算子进化生成Agent - 通过并行生成和进化优化生成高性能内核

• cake-partial

  AscendC算子部分生成Agent - 从DSL生成开始到评估结束 (用于进化子任务)

• cake

  AscendC算子生成主编排Agent

Hooks (3)

• Stop

  bash ${CLAUDE_PLUGIN_ROOT}/hooks/check_eval_done.sh

• PostToolUse

  python3 ${CLAUDE_PLUGIN_ROOT}/hooks/debug_skill_advisor.py --event PostToolUse

• PostToolUseFailure

  python3 ${CLAUDE_PLUGIN_ROOT}/hooks/debug_skill_advisor.py --event PostToolUseFailure

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