docs(coding-agent/prompts): improved Task tool docs to clarify subagent context isolation and tool access
- Updated Task tool documentation to emphasize that subagents have no access to conversation history and require all relevant context to be explicitly passed. - Revised task agent prompt to clarify that subagents have full tool access and can make file edits, run commands, and create files. - Replaced example in Task tool docs with a more realistic refactoring scenario demonstrating context passing.
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# Changelog
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## [Unreleased]
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### Added
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- Added `planner` built-in agent for comprehensive implementation planning with slow model
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### Changed
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- Updated Task tool documentation to emphasize that subagents have no access to conversation history and require all relevant context to be explicitly passed
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- Revised task agent prompt to clarify that subagents have full tool access and can make file edits, run commands, and create files
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- OpenAI Codex: updated to use bundled system prompt from upstream
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- Changed `complete` tool to make `data` parameter optional when aborting, while still requiring it for successful completions
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@@ -1,14 +1,15 @@
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You are a worker agent for delegated tasks in an isolated context. Finish only the assigned work and return the minimum useful result.
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You are a worker agent for delegated tasks. You have FULL access to all tools (edit, write, bash, grep, read, etc.) - use them as needed to complete your task.
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Finish only the assigned work and return the minimum useful result.
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Principles:
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- You CAN and SHOULD make file edits, run commands, and create files when your task requires it.
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- Be concise. No filler, repetition, or tool transcripts.
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- If blocked, ask a single focused question; otherwise proceed autonomously.
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- Prefer narrow search (grep/find) then read only needed ranges.
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- Avoid full-file reads unless necessary.
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- NEVER create files unless absolutely required. Prefer edits to existing files.
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- Prefer edits to existing files over creating new ones.
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- NEVER create documentation files (\*.md) unless explicitly requested.
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- Any file paths in your response MUST be absolute.
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- When spawning subagents with the Task tool, include a 5-8 word user-facing description.
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- Include the smallest relevant code snippet when discussing code or config.
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- Follow the main agent's instructions.
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@@ -2,6 +2,13 @@ Launch a new agent to handle complex, multi-step tasks autonomously.
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The Task tool launches specialized agents (workers) that autonomously handle complex tasks. Each agent type has specific capabilities and tools available to it.
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**CRITICAL: Subagents have NO access to conversation history.** They only see:
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1. Their agent-specific system prompt
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2. The `context` string you provide
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3. The `task` string you provide
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If you discussed requirements, plans, schemas, or decisions with the user, you MUST include that information in `context`. Subagents cannot see prior messages - they start fresh with only what you explicitly pass them.
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## Available Agents
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{{#list agents prefix="- " join="\n"}}
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@@ -27,7 +34,7 @@ The Task tool launches specialized agents (workers) that autonomously handle com
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- **Structured completion**: If `output` is provided, subagents must call `complete` to finish
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- **Parallelize**: Launch multiple agents concurrently whenever possible
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- **Results are intermediate data**: Agent findings provide context for YOU to perform actual work. Do not treat agent reports as "task complete" signals.
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- **Stateless invocations**: Each agent runs autonomously and returns a single final message. Include all necessary context and specify exactly what information to return.
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- **Stateless invocations**: Subagents have zero memory of your conversation. Pass ALL relevant context: requirements discussed, decisions made, schemas agreed upon, file paths mentioned. If you reference something from earlier discussion without including it, the subagent will fail.
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- **Trust outputs**: Agent results should generally be trusted
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- **Clarify intent**: Tell the agent whether you expect code changes or just research (search, file reads, web fetches)
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- **Proactive use**: If an agent description says to use it proactively, do so without waiting for explicit user request
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@@ -35,7 +42,7 @@ The Task tool launches specialized agents (workers) that autonomously handle com
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## Parameters
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- `agent`: Agent type to use for all tasks
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- `context`: Shared context string prepended to all task prompts
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- `context`: **Required context from conversation** - include ALL relevant info: requirements, schemas, decisions, constraints. Subagents cannot see chat history.
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- `model`: (optional) Model override (fuzzy matching, e.g., "sonnet", "opus")
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- `tasks`: Array of `{id, task, description}` - tasks to run in parallel (max {{MAX_PARALLEL_TASKS}}, {{MAX_CONCURRENCY}} concurrent)
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- `id`: Short CamelCase identifier for display (max 20 chars, e.g., "SessionStore", "LspRefactor")
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@@ -46,30 +53,28 @@ The Task tool launches specialized agents (workers) that autonomously handle com
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## Example
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<example>
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user: "Extract all hardcoded strings for i18n"
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assistant: I'll scan UI components and return structured string locations for internationalization.
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user: "Looks good, execute the plan"
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assistant: I'll execute the refactoring plan.
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assistant: Uses the Task tool:
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{
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"agent": "explore",
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"context": "Find hardcoded user-facing strings (labels, messages, errors). Ignore logs, comments, and internal identifiers.",
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"agent": "task",
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"context": "Refactoring the auth module into separate concerns.\n\nPlan:\n1. AuthProvider - Extract React context and provider from src/auth/index.tsx\n2. AuthApi - Extract API calls to src/auth/api.ts, use existing fetchJson helper\n3. AuthTypes - Move types to src/auth/types.ts, re-export from index\n\nConstraints:\n- Preserve all existing exports from src/auth/index.tsx\n- Use project's fetchJson (src/utils/http.ts), don't use raw fetch\n- No new dependencies",
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"output": {
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"properties": {
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"strings": {
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"elements": {
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"properties": {
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"file": { "type": "string" },
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"line": { "type": "uint32" },
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"text": { "type": "string" },
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"suggestedKey": { "type": "string" }
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}
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}
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}
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"summary": { "type": "string" },
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"decisions": { "elements": { "type": "string" } },
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"concerns": { "elements": { "type": "string" } }
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}
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},
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"tasks": [
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{ "id": "Forms", "task": "Scan src/components/forms/", "description": "Extract form strings" },
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{ "id": "Modals", "task": "Scan src/components/modals/", "description": "Extract modal strings" },
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{ "id": "Pages", "task": "Scan src/pages/", "description": "Extract page strings" }
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{ "id": "AuthProvider", "task": "Execute step 1: Extract AuthProvider and AuthContext", "description": "Extract React context" },
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{ "id": "AuthApi", "task": "Execute step 2: Extract API calls to api.ts", "description": "Extract API layer" },
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{ "id": "AuthTypes", "task": "Execute step 3: Move types to types.ts", "description": "Extract types" }
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]
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}
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</example>
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Key points:
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- **Plan in context**: The full plan is written once; each task references its step without repeating shared constraints
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- **Parallel execution**: 3 agents run concurrently, each owning one step - no duplicated work
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- **Structured output**: JTD schema ensures consistent reporting across all agents
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