ascendc-st-design

Design Ascend C operator tests via YAML-driven test plan and test-case generation.

11|51|Updated Mar 10, 2026
One-click install
npx skills add https://github.com/hw-native-sys/pypto-lib --skill ascendc-st-design
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ascendc-st-design
Source: https://github.com/hw-native-sys/pypto-lib/tree/main/.claude/skills/cannbot-skills/ascendc-st-design
Command: npx skills add https://github.com/hw-native-sys/pypto-lib --skill ascendc-st-design

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, yaml, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill enables systematic Ascend C operator test design by guiding you through calibrating operator data, drafting test plans, analyzing operator parameters and dependencies, extracting test factors, and generating test-case combinations based on aclnn guidelines.

Core Features & Use Cases

  • Supports building complete operator test workflows (calibration, factor extraction, constraint generation, solver config, and test-case synthesis) for aclnn-based ASCEND C operators.
  • Provides templates and scripts to produce plan.yaml, 04/05 factor constraints, and L0/L1 test cases aligned with standard acceptance criteria.
  • Useful in validating operator functionality and precision across diverse parameter spaces.

Quick Start

Run the prescribed scripts under skills/ascendc-st-design/scripts to generate factors, constraints, solver configs, and test cases for a given operator.

Frequently Asked Questions about ascendc-st-design

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design Ascend C operator tests for aclnn workflows?▼

Designing Ascend C operator tests involves orchestrating test plan generation, factor extraction, and test-case construction for aclnn workflows. This skill automates YAML-driven test artifact synthesis to validate operator functionality and precision.

What is factor extraction in Ascend C operator testing?▼

Factor extraction in Ascend C operator testing is the process of analyzing operator parameters and dependencies to derive test factors. These factors are then used to generate 04/05 factor constraints and plan test-case combinations across parameter spaces.

Can I automate test-case generation for Ascend C operators using YAML?▼

Yes, you can automate test-case generation for Ascend C operators using a YAML-driven workflow. By running provided scripts, the skill synthesizes L0/L1 test cases and solver configs from extracted factors and YAML constraints.

Does this skill support validating operator precision across diverse parameter spaces?▼

Yes, this skill supports validating Ascend C operator functionality and precision by planning coverage across diverse parameter spaces. It automates test-case synthesis based on aclnn guidelines to ensure comprehensive validation.

What do I need to generate L0 and L1 test cases for aclnn operators?▼

To generate L0 and L1 test cases for aclnn operators, you run the prescribed scripts provided by the skill. These scripts automate factor derivation, constraint generation, and test-case synthesis from your operator data and YAML configurations.

Why use YAML for Ascend C operator test workflows instead of manual scripting?▼

Using YAML for Ascend C operator test workflows enables structured, automated factor derivation and test-case synthesis. It standardizes plan generation, solver configs, and constraint creation, replacing manual scripting with reproducible, automated test artifact generation.