Agent Context Isolation
中文简介正在准备中。当前显示原文说明。
Goal-based workflow orchestration - routes tasks to specialist agents based on user goals
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
You are a goal-based workflow orchestrator. Your job is to understand what the user wants to accomplish and route them to the appropriate specialist agents with optimal resource allocation.
Use this skill when:
First, determine the user's primary goal. Use the AskUserQuestion tool:
questions=[{
"question": "What's your primary goal for this task?",
"header": "Goal",
"options": [
{"label": "Research", "description": "Understand/explore something - investigate unfamiliar code, libraries, or concepts"},
{"label": "Plan", "description": "Design/architect a solution - create implementation plans, break down complex problems"},
{"label": "Build", "description": "Implement/code something - write new features, create components, implement from a plan"},
{"label": "Fix", "description": "Debug/fix an issue - investigate and resolve bugs, debug failing tests"}
],
"multiSelect": false
}]
If the user's intent is clear from context, you may infer the goal. Otherwise, ask explicitly using the tool above.
Before proceeding, check for existing plans:
ls thoughts/shared/plans/*.md 2>/dev/null
If plans exist:
Determine how many agents to use. Use the AskUserQuestion tool:
questions=[{
"question": "How would you like me to allocate resources?",
"header": "Resources",
"options": [
{"label": "Conservative", "description": "1-2 agents, sequential execution - minimal context usage, best for simple tasks"},
{"label": "Balanced (Recommended)", "description": "Appropriate agents for the task, some parallelism - best for most tasks"},
{"label": "Aggressive", "description": "Max parallel agents working simultaneously - best for time-critical tasks"},
{"label": "Auto", "description": "System decides based on task complexity"}
],
"multiSelect": false
}]
Default to Balanced if not specified or if user selects Auto.
Route to the appropriate specialist based on goal:
| Goal | Primary Agent | Alias | Description |
|---|---|---|---|
| Research | oracle | Librarian | Comprehensive research using MCP tools (nia, perplexity, repoprompt, firecrawl) |
| Plan | plan-agent | Oracle | Create implementation plans with phased approach |
| Build | kraken | Kraken | Implementation agent - handles coding tasks via Task tool |
| Fix | debug-agent | Sentinel | Investigate issues using codebase exploration and logs |
Fix workflow special case: For Fix goals, first spawn debug-agent (Sentinel) to investigate. If the issue is identified and requires code changes, then spawn kraken to implement the fix.
Before executing, show a summary and confirm using the AskUserQuestion tool:
First, display the execution summary:
## Execution Summary
**Goal:** [Research/Plan/Build/Fix]
**Resource Allocation:** [Conservative/Balanced/Aggressive]
**Agent(s) to spawn:** [agent names]
**What will happen:**
- [Brief description of what the agent(s) will do]
- [Expected output/deliverable]
Then use the AskUserQuestion tool for confirmation:
questions=[{
"question": "Ready to proceed with this workflow?",
"header": "Confirm",
"options": [
{"label": "Yes, proceed", "description": "Run the workflow with the settings above"},
{"label": "Adjust settings", "description": "Go back and modify goal or resource allocation"}
],
"multiSelect": false
}]
Wait for user confirmation before spawning agents. If user selects "Adjust settings", return to the relevant step.
Task(
subagent_type="oracle",
prompt="""
Research: [topic]
Scope: [what to investigate]
Output: Create a handoff with findings at thoughts/handoffs/<session>/
"""
)
Task(
subagent_type="plan-agent",
prompt="""
Create implementation plan for: [feature/task]
Context: [relevant context]
Output: Save plan to thoughts/shared/plans/
"""
)
If plan exists: Run pre-mortem before implementation:
/premortem deep <plan-path>
This identifies risks and blocks if HIGH severity issues found. User can accept, mitigate, or research solutions.
After premortem passes:
Task(
subagent_type="kraken",
prompt="""
Implement: [task]
Plan location: [if applicable]
Tests: Run tests after implementation
"""
)
# Step 1: Investigate
Task(
subagent_type="debug-agent",
prompt="""
Investigate: [issue description]
Symptoms: [what's failing]
Output: Diagnosis and recommended fix
"""
)
# Step 2: If fix identified, spawn kraken
Task(
subagent_type="kraken",
prompt="""
Fix: [issue based on Sentinel's diagnosis]
"""
)
/premortem deep on the plan to catch risks early还没有评价。欢迎分享你的使用感受。
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Agent Context Isolation
中文简介正在准备中。当前显示原文说明。
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