Skill: zcxggmu/linux-riscv-contribute (version 1.0.0)

--- 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`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)