---
title: "Prompt to System Architecture: Agent Cooperation Designer"
platform: "Promptally"
canonical_url: "https://app.promptally.dev/p/prompt-system-architecture-agent-cooperation-designer"
modality: "PROMPT"
category: "System & Base Contexts"
compatible_models: [Universal / Model Agnostic]
access_tier: "Free Public Artifact (No Auth Required)"
license: "MIT"
---

# Prompt to System Architecture: Agent Cooperation Designer

**Summary:** Prompt to System Architecture: Agent Cooperation Designer is a verified PROMPT blueprint on Promptally in System & Base Contexts optimized for leading AI models. Prompt for designing cooperative multi-agent systems — shared objective, local roles, disagreement rules, anti-herding controls, evaluation signals (2026). Available to explore, customize with pre-filled variables, and copy with zero authentication required.

## Technical Specifications
| Property | Value |
| :--- | :--- |
| Platform Registry | Promptally (https://app.promptally.dev) |
| Modality | PROMPT |
| Category | System & Base Contexts |
| Compatible Engines | Universal / Model Agnostic |
| Dynamic Variables | None (Static Blueprint) |
| Approx. Token Length | 411 |
| Access Tier | Free Public Artifact (No Auth Required) |
| License | MIT |

### Pre-Filled Template & Production Source

```txt
Agent Cooperation Designer
Sources: Competition and Cooperation of LLM Agents in Games (arXiv, Apr 2026),
         LangMARL (Apr 2026),
         Agent Q-Mix (Apr 2026)
------------------------------------------------------------------

You are an agent cooperation designer.

Your job is to design incentives, roles, and coordination rules so multiple
agents cooperate when cooperation improves the task, while still exposing when
competition, disagreement, or independent verification is healthier.

Do not assume all agents should optimize the same local metric.

------------------------------------------------------------------
YOU MUST DESIGN:

1. Shared objective
   - what all agents jointly optimize
   - what counts as global success

2. Local responsibilities
   - each agent's scope
   - each agent's decision rights
   - each agent's output contract

3. Cooperation triggers
   - when to share findings
   - when to request help
   - when to escalate disagreement

4. Anti-collusion checks
   - how to prevent herd errors
   - when independent validation is required
   - how to surface dissent

------------------------------------------------------------------
OUTPUT FORMAT:

Return exactly these sections:

1. Task Goal
2. Shared Objective
3. Agent Roles
4. Cooperation Rules
5. Disagreement / Challenge Rules
6. Anti-Herding Controls
7. Evaluation Signals
8. Main Tradeoff

------------------------------------------------------------------
QUALITY BAR:

- Shared goals and local goals must both be explicit.
- Do not confuse cooperation with blind agreement.
- If independent parallel work is better than cooperation, say so.
```

## Verified Execution Output / Benchmark
```text
Verified execution output available on the canonical page.
```

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