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linux-riscv-contributeLinux RISCV 贡献

Agent Skill

linux-riscv-contribute 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,008

周安装

383

GitHub Stars

1

下载量

3,156
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:linux-riscv-contribute(Linux RISCV 贡献)
来源仓库:https://github.com/zcxggmu/linux-riscv-contribute
安装命令:
openclaw skills install linux-riscv-contribute
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install linux-riscv-contribute

简介

协调OpenClaw多代理流程推进Linux RISC-V生态建设。

  • 自动生成GitHub议题与设计草案,缩小架构差距。
  • 聚焦树莓派类RISC-V设备兼容性改进。linux-riscv-contribute 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 需熟悉Linux内核移植与交叉编译流程。
  • 建议优先验证现有补丁适用性,减少重复工作。

SKILL.md

name
linux-riscv-contribute
description
Orchestrate an OpenClaw multi-agent pipeline to close Linux RISC-V gaps versus ARM/x86 (Linux tree + KVM lore), create and manage GitHub issues, generate design plans with Claude Code, implement/verify with Codex, and prepare upstream patch emails. Use when users ask to automate or run RISC-V kernel contribution workflows, gap analysis, issue-driven execution, or patch submission preparation.

Linux RISC-V Contribute

Overview

Use this skill to run a repeatable discover -> issue -> plan -> implement -> patch pipeline with OpenClaw as orchestrator and ACP agents (claude-code, codex) as workers.

Keep humans at exactly three gates:

  1. Confirm gap triage and priorities.
  2. Approve implementation plan.
  3. Approve final patch email before sending.

Workflow

Step 0: Bootstrap workspace

Run scripts/bootstrap_openclaw_workflow.sh <docs_repo_root> <linux_repo_path> to create/update:

  • kernel/openclaw/config/workflow.yaml
  • kernel/openclaw/state/{gap_registry.yaml,issue_map.yaml,run_history/}
  • kernel/openclaw/{plans,patches,logs}

If files already exist, do not overwrite without explicit user approval.

Step 1: Discover RISC-V gaps

Collect evidence from:

  • Linux source tree (arch/riscv, arch/arm64, arch/x86, virt/kvm)
  • KVM lore (https://yhbt.net/lore/kvm/)

Write structured entries to state/gap_registry.yaml with:

  • gap_id, type (feature|performance|maintainability), summary
  • evidence (paths, commits, lore URLs)
  • severity (P0|P1|P2), confidence (high|medium|low)
  • acceptance_hint

Pause for Gate-1 human triage before creating issues.

Step 2: Sync GitHub issues

For each approved gap:

  • Create/update issue in configured repo.
  • Add labels from severity/type.
  • Save gap_id -> issue_number mapping to state/issue_map.yaml.

Use one issue per gap; avoid duplicate issues by matching gap_id.

Step 3: Plan with Claude Code (ACP)

Spawn ACP session explicitly:

  • runtime: "acp"
  • agentId: "claude-code"

Ask for:

  • file-level design
  • test matrix (kselftest, kvm-unit-tests, perf)
  • rollback/risk notes
  • upstreaming strategy

Save outputs under kernel/openclaw/plans/issue-<id>-plan.md. Pause for Gate-2 human plan approval.

Step 4: Implement and verify with Codex (ACP)

Spawn ACP session explicitly:

  • runtime: "acp"
  • agentId: "codex"

Run iterative loop until pass or policy limit:

  1. Implement approved plan.
  2. Build and run configured tests.
  3. Parse failures and patch.

Record each iteration in state/run_history/*.json. If max iterations reached, return to Step 3 with failure summary.

Step 5: Generate patch and email package

Produce:

  • git format-patch series
  • checkpatch result
  • suggested To/Cc (get_maintainer.pl, lore context)
  • cover letter draft

Save artifacts in kernel/openclaw/patches/. Pause for Gate-3 human send approval.

Only send to mailing lists after explicit approval.

OpenClaw execution rules

  • Prefer ACP sessions_spawn for agent work; set agentId explicitly.
  • Limit parallel issues to 2-3 unless user changes policy.
  • Never auto-send external email without user confirmation.
  • Preserve auditability: every stage must have file artifacts.

Quick command prompts for operator

Use these ready prompts in OpenClaw chat:

  1. 按 workflow.yaml 执行 Step-1,更新 gap_registry.yaml,并生成 Gate-1 审核表。
  2. 基于已批准 gap 执行 Step-2,同步 issue 并输出映射表。
  3. 对 issue #<n> 用 claude-code 执行 Step-3,生成详细方案和测试矩阵。
  4. 对 issue #<n> 用 codex 执行 Step-4,直到验证通过或达到迭代上限。
  5. 对 issue #<n> 执行 Step-5,先 dry-run 生成 patch 和发信草案,等待我确认。

References

  • Workflow template: references/workflow-template.yaml
  • Issue template: references/issue-template.md
  • Human gate checklist: references/gate-checklist.md

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

95.53%
按下载量换算3,015

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install linux-riscv-contribute 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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