Handoff Prompt Generator

Generate optimized handoff prompts for different LLM agents and handoff types.

Handoff Types

1. Sub-Task/Parallel Handoff

For delegating a portion of work to another agent within the same project:

• Agent has access to same codebase/files
• Shared context exists
• Task is scoped subset of larger work
• May run in parallel with other agents

2. Fresh Start Handoff

For handing off to an agent starting with a new context:

• Agent starts with no prior context
• Needs project orientation
• Requires state files and entry points
• May be a new session or different model

Workflow

1. Identify target model - Ask which model family will receive the handoff
2. Identify handoff type - Sub-task/parallel or fresh start
3. Gather context - Collect essential information for the handoff
4. Generate prompt - Apply model-specific patterns from references
5. Review and refine - Ensure prompt is complete and well-scoped

Model-Specific References

Read the appropriate reference based on target model:

Universal Handoff Components

Every handoff prompt should include:

Required

• Objective: Clear, specific goal
• Scope/Boundaries: What is and isn't in scope
• Output Format: Expected deliverable structure
• Constraints: What not to do, limitations

For Fresh Start Handoffs (add these)

• Project Context: Essential background
• Entry Points: Key files to read first
• Current State: What's done, what remains
• State Files: Progress tracking files to check

For Sub-Task Handoffs (add these)

• Dependencies: Files, APIs, or prior outputs needed
• Artifact References: Shared state or outputs
• Coordination Notes: How this task fits with parallel work

Quick Templates

Sub-Task Handoff (Universal)

<task_handoff target="[MODEL]">
<objective>[Specific, atomic goal]</objective>
<context>[Only what's needed for THIS task]</context>
<dependencies>[Files, APIs, prior outputs needed]</dependencies>
<scope>
  <include>[What to do]</include>
  <exclude>[What NOT to do]</exclude>
</scope>
<output>
  <format>[Structure of deliverable]</format>
  <location>[Where to save/return results]</location>
</output>
<coordination>[How this fits with parallel work]</coordination>
</task_handoff>

Fresh Start Handoff (Universal)

<fresh_context target="[MODEL]">
<project>
  <name>[Project name]</name>
  <overview>[1-2 sentence description]</overview>
  <entry_points>[Key files to read first]</entry_points>
</project>
<state>
  <completed>[What's done]</completed>
  <remaining>[What needs to be done]</remaining>
  <state_files>[progress.txt, tests.json, etc.]</state_files>
</state>
<task>
  <objective>[Specific goal]</objective>
  <success_criteria>[How to verify completion]</success_criteria>
</task>
<constraints>
  [Scope limits]
  [What not to do]
</constraints>
<output>
  <format>[Expected structure]</format>
  <verification>[How to validate results]</verification>
</output>
</fresh_context>

Model-Specific Adjustments

After generating the base prompt, apply these adjustments:

GPT-5.2/Codex

• Use CTCO framework (Context → Task → Constraints → Output)
• Add <reasoning_effort> tag (minimal/low/medium/high)
• For fresh handoffs, format as AGENTS.md

Claude Opus 4.5/Sonnet 4

• Avoid word "think" for Opus 4.5 (use consider/evaluate)
• Add explicit action mode (proactive vs conservative)
• Include parallel execution guidance
• Reference git for state tracking

Gemini 3 Pro/Flash

• Add thinking_level (LOW/MEDIUM/HIGH)
• Include anchoring phrase ("Based on the above...")
• Avoid broad negatives; be specific
• Note: keep temperature at 1.0

Best Practices

1. Minimize context - Include only what's essential for the task
2. Be explicit - State goals clearly; don't rely on inference
3. Scope tightly - Prevent overlap with parallel tasks
4. Include verification - How will the agent know it succeeded?
5. Reference artifacts - Point to shared state rather than duplicating
6. Match model style - Use patterns the target model responds to best