verl-feature-intelligence

Extract user-adjustable parameters from Verl examples into Chinese markdown docs and Excel ledgers.

Updated Jun 6, 2026
One-click install
npx skills add https://github.com/Kirrito-k423/AutoResearch --skill verl-feature-intelligence-kirrito-k423
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: verl-feature-intelligence
Source: https://github.com/Kirrito-k423/AutoResearch/tree/main/workspace-adapter/verl-feature-intelligence
Command: npx skills add https://github.com/Kirrito-k423/AutoResearch --skill verl-feature-intelligence-kirrito-k423

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve? Understanding which knobs Verl exposes to users requires manually reading dozens of example shell scripts and YAML files. This Skill automates that discovery by scanning Verl examples for environment variables, Hydra overrides, and CLI flags, then maintaining a Chinese-language parameter intelligence library with per-parameter explanations and an Excel ledger. ## Core Features & Use Cases - Automated Parameter Scanning: Parses examples/**/*.sh and examples/**/*.yaml for FOO=${FOO:-default} environment overrides, Hydra keys like actor_rollout_ref.*, and --flag arguments, classifying each as 配置, 算法, or 效率. - Per-Parameter Explanation Files: Generates and reuses markdown files under docs/verl/features/lists/ with Chinese explanation, common values, performance impact, accuracy impact, and evidence snippets. - Subagent Research Batches: Splits unresolved 待补充 parameters into batch files so subagents can research official Verl docs and repo docs, then re-runs the scan to absorb results. - Use Case: Point the scan script at a local Verl checkout to produce docs/verl/features/verl-example-parameters.xlsx listing every example parameter with category, Chinese explanation, common values, performance and accuracy impact, and example count. ## Quick Start Ask the agent to scan the local Verl repository examples and generate the Chinese parameter explanation library plus the Excel ledger under docs/verl/features.

Frequently Asked Questions about verl-feature-intelligence

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

FAQPage Schema
How do I extract all configurable parameters from Verl examples?▼

Run the scan_verl_features.py script with --repo pointing at a local Verl checkout. It parses examples shell scripts and YAML files for environment variable defaults, Hydra overrides, and CLI flags, then writes JSON, markdown, and Excel outputs under docs/verl/features.

How are Verl parameters categorized in the Excel ledger?▼

Parameters are classified into exactly three categories: 配置 for files, paths, logging, and checkpoint settings; 算法 for learning rate, KL, entropy, rollout n, and sampling parameters; and 效率 for batch sizes, parallelism, offload, recompute, and memory utilization knobs.

Does the scanner support NPU and Ascend-specific Verl scripts?▼

Yes. It detects NPU evidence from tokens like npu, ascend, torch_npu, hccl, and cann in file paths and script content, and prioritizes examples/ascend_extras and NPU profile scripts. NPU support is marked as 是, 部分, or 未知 based on evidence.

What happens when a parameter explanation is missing?▼

Parameters without explanations are marked 待补充 and listed in process/needs-research.txt. The make_research_batches.py script splits them into batch files so subagents can research official Verl docs and repo docs, then write back per-parameter markdown files.

Does the skill scan Verl source code to find features?▼

No. Source code is only used to explain parameter meanings or confirm value ranges. The feature list is built strictly from examples scripts and YAML files, so internal source capabilities are never listed as user-facing parameters without examples evidence.