email-draft
Use when the user asks to draft, polish, translate, or reply to an email. Produces a clean draft with subject line, greeting, body, and sign-off, plus a…
Hope-native multi-agent coding orchestration: fan out only independent valuable work, enforce bounded scope and isolation, consume structured results progressively, steer or cancel, and keep synthesis with the main Agent.
$ npx -y skills add shiwenwen/hope-agent --skill ha-multi-agent-coding --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/ha-multi-agent-codingContext preview
The summary Claude sees to decide when to auto-load this skill.
Hope-native multi-agent coding orchestration: fan out only independent valuable work, enforce bounded scope and isolation, consume structured results progressively, steer or cancel, and keep synthesis with the main Agent.
name: ha-multi-agent-coding description: "Hope-native multi-agent coding orchestration: fan out only independent valuable work, enforce bounded scope and isolation, consume structured results progressively, steer or cancel, and keep synthesis with the main Agent." paths: ["*.rs", "*.ts", "*.tsx", "*.js", "*.jsx", "*.py", "*.go", "*.java", "*.kt", "*.swift", "*.c", "*.cpp", "*.h", "*.rb", "*.php", "*.sh"]
Use multiple Agents when parallel evidence or implementation meaningfully outweighs coordination cost. Do not make delegation the default for complex-looking work.
Good candidates:
Keep work with one Agent when:
Provide:
Do not re-delegate the entire parent assignment to one child. Children do not own final user communication or Goal closure.
ownership.
remain runtime-enforced. A child prompt cannot grant access.
Set explicit limits for fan-out count, depth, turns, tokens, and time. Respect runtime queues and backpressure. Never recursively create Workflow runs or an unbounded Agent tree.
The main Agent may choose based on task needs:
Background work must not block the user's conversation. Use runtime completion or checkpoint injection rather than polling loops.
The main Agent must:
1. Check which children completed, failed, timed out, or returned no evidence. 2. Resolve conflicts using source evidence, not majority vote. 3. Preserve partial failures and uncertainty. 4. Integrate or review writes in the parent worktree deliberately. 5. Run parent-level verification for the combined outcome.
"All Agents completed" is orchestration state, not a user result. Do not finish until the parent has synthesized and answered the actual task.
This skill decides delegation strategy. Use `ha-workflow-script` when execution must be durable, replayable, observable, or script-controlled. Simple bounded subagent work does not require a Workflow; a Workflow may use this strategy without surrendering its runtime contracts.
🦭 会记忆、能持续推进目标、会动态编排多 Agent 的跨端桌面 AI 助手,也可服务化常驻 NAS / 云端 | A cross-device desktop AI agent with memory, autonomous goals, dynamic workflows, and headless deployment
Repo: shiwenwen/hope-agent
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