---
title: Task Implementor Guide
description: Use the Task Implementor custom agent to execute implementation plans with precision and tracking
sidebar_position: 6
author: Microsoft
ms.date: 2026-01-24
ms.topic: tutorial
keywords:
- task implementor
- rpi workflow
- implementation phase
- github copilot
estimated_reading_time: 4
---
The Task Implementor custom agent transforms planning files into working code. It executes plans task by task, tracks all changes, and supports stop controls for review between phases.
## When to Use Task Implementor
Use Task Implementor after completing planning when you need:
* β‘ **Precise execution** following the plan exactly
* π **Change tracking** documenting all modifications
* βΈοΈ **Stop controls** for review between phases
* β
**Verification** that success criteria are met
## What Task Implementor Does
1. **Reads** the plan phase by phase, task by task
2. **Loads** only needed details using line ranges
3. **Implements** code following workspace conventions
4. **Tracks** changes in a changes log
5. **Verifies** success criteria before marking complete
6. **Pauses** at stop points for your review
> [!NOTE]
> **Why the constraint matters:** Task Implementor has one job: execute the plan using patterns documented in research. No time wasted rediscovering conventions, no "creative" decisions that break existing patterns. Just verified facts applied methodically.
## Output Artifacts
Task Implementor creates working code and a changes log:
```text
.copilot-tracking/
βββ changes/
βββ {{YYYY-MM-DD}}-<topic>-changes.md # Log of all changes made
```
Plus all the actual code files created or modified during implementation.
## How to Use Task Implementor
### Step 1: Clear Context and Open the Plan
π΄ **Start with `/clear` or a new chat** after Task Planner completes.
After clearing, open your plan file (`.copilot-tracking/plans/<topic>-plan.instructions.md`) in the editor before invoking Task Implementor. This ensures the agent can locate and follow the plan without relying on chat history.
> [!TIP]
> Context management is an engineering practice, not a ritual. Clearing context removes accumulated tokens that cause the model to ignore its instructions. See [Context Engineering](context-engineering.md) for the full explanation.
### Step 2: Select the Custom Agent
1. Open GitHub Copilot Chat (`Ctrl+Alt+I`)
2. Click the agent picker dropdown
3. Select **Task Implementor**
### Step 3: Reference Your Plan
Use `/task-implement` to start execution. The prompt automatically locates the plan and switches to Task Implementor. Alternatively, provide the path to your plan file directly.
### Step 4: Set Stop Controls
Choose your review cadence:
* `phaseStop=true` (default): Pause after each phase
* `taskStop=true`: Pause after each task
* Both false: Run to completion
### Step 5: Review and Continue
At each stop point:
1. Review the changes made
2. Verify code compiles and lints
3. Approve or request adjustments
4. Continue to next phase/task
## Example Prompt
```text
/task-implement
```
Or reference a specific generated prompt:
```text
/implement-blob-storage
```
## Understanding Stop Controls
### Phase Stop (Default: true)
Pauses after completing all tasks in a phase:
```text
Phase 1: [x] Task 1.1, [x] Task 1.2 β STOP for review
Phase 2: [ ] Task 2.1, [ ] Task 2.2
```
### Task Stop (Default: false)
Pauses after each individual task:
```text
Phase 1: [x] Task 1.1 β STOP
[ ] Task 1.2
```
## Tips for Better Implementation
β
**Do:**
* Review changes at each stop point
* Run linters and validators
* Check that success criteria are met
* Ask for adjustments before continuing
β **Don't:**
* Skip reviewing changes
* Ignore failing tests or lints
* Rush through all phases without checking
## The Changes Log
Task Implementor maintains a changes log with sections:
```markdown
## Changes
### Added
* src/storage/blob_client.py - Azure Blob Storage client class
### Modified
* src/pipeline/config.py - Added blob storage configuration
### Removed
* (none this implementation)
```
## At Completion
When all phases are complete, Task Implementor provides:
1. **Summary** of all changes from the changes log
2. **Links** to planning files for reference
3. **Recommendation** to proceed to review
## Common Pitfalls
| Pitfall | Solution |
|-------------------------|---------------------------------------------------------------------------------|
| Plan not found | Complete Task Planner first |
| Skipping reviews | Use phaseStop=true for important changes |
| Not running validations | Check lint/test after each phase |
| Context issues | Use `/clear` before starting; see [Context Engineering](context-engineering.md) |
## Next Steps
After Task Implementor completes:
1. **Clear context** using `/clear` or starting a new chat
2. **Review** using `/task-review` to switch to [Task Reviewer](task-reviewer.md)
3. **Address findings** from the review before committing
4. **Commit** your changes with a descriptive message
5. **Clean up** planning files if no longer needed
> [!TIP]
> Use the **β
Review** handoff button when available to transition directly to Task Reviewer with context.
For your next task, you can start the RPI workflow again with Task Researcher.
---
<!-- markdownlint-disable MD036 -->
*π€ Crafted with precision by β¨Copilot following brilliant human instruction,
then carefully refined by our team of discerning human reviewers.*
<!-- markdownlint-enable MD036 -->microsoft/hve-core
Publicmirrored fromhttps://github.com/microsoft/hve-coreAvailable
docs/rpi/task-implementor.md
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