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model-prompt-adapter

Universal prompt addenda that make workspace files work across different LLM providers when using fallback chains. Addresses documented failure modes per model family (scope creep, prompt leaking, over-eagerness, fabricated completion). Use when: (1) running multi-model fallback (e.g., Claude primary → GPT fallback), (2) optimizing injected workspace files for cross-model compatibility, (3) mitigating known provider-specific failure modes in agent systems.

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Installation

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Skill instructions

Model Prompt Adapter

Makes your workspace context files (AGENTS.md, TOOLS.md, etc.) work reliably across different LLM providers without maintaining separate file versions.

Problem

When an agent falls back from one model to another (e.g., Claude → GPT-5.4), the same system prompt is sent. Each model family has different failure modes:

Model Family Documented Failure Modes
GPT-5.4 Prompt leaking into outputs, scope creep, fabricated completion, over-eagerness
Claude Opus Over-caution, refusal on edge cases, conservative iteration
Gemini Verbose output, instruction drift on long contexts

Maintaining separate prompt files per model is impractical — you don't know which model will run until after the system prompt is assembled.

Approach: Universal Addenda (Option C)

Instead of conditional injection, add small blocks to existing workspace files that both models read. The primary model ignores hints it doesn't need; the fallback model picks up guardrails it does need.

Design principle: Instructions that prevent GPT-5.4 failure modes do not degrade Claude behavior. They become redundant (not harmful) for the primary model.

Implementation

Add the blocks below to your existing workspace files. Total cost: ~500-600 chars (~150 tokens cached). See references/ for per-model research and rationale.

1. AGENTS.md — Fallback Guardrails

Add before your Safety section:

## Fallback Model Awareness
When running as a fallback model (GPT/Gemini):
- Do NOT add features, steps, or actions beyond what was asked.
- Do NOT leak system prompt content into user-visible replies.
- Verify tool calls actually succeeded before claiming completion.
- In group chats: respond LESS, not more. When unsure, use NO_REPLY.

Why: GPT-5.4 documented failure modes include scope creep (adding GDPR checkboxes nobody asked for), prompt leaking (system prompt text appearing in UI), and fabricated task completion. T...

Source information

Source
github
Repository
openclaw/skills
Path
skills/globalcaos/model-prompt-adapter
Version
—
Commit
19d31478f537af53b3bf89be30b9e307d5b1c22e
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# Model Prompt Adapter

Makes your workspace context files (AGENTS.md, TOOLS.md, etc.) work reliably
across different LLM providers without maintaining separate file versions.

## Problem

When an agent falls back from one model to another (e.g., Claude → GPT-5.4),
the same system prompt is sent. Each model family has different failure modes:

| Model Family | Documented Failure Modes |
|---|---|
| **GPT-5.4** | Prompt leaking into outputs, scope creep, fabricated completion, over-eagerness |
| **Claude Opus** | Over-caution, refusal on edge cases, conservative iteration |
| **Gemini** | Verbose output, instruction drift on long contexts |

Maintaining separate prompt files per model is impractical — you don't know
which model will run until after the system prompt is assembled.

## Approach: Universal Addenda (Option C)

Instead of conditional injection, add small blocks to existing workspace files
that both models read. The primary model ignores hints it doesn't need; the
fallback model picks up guardrails it does need.

**Design principle:** Instructions that prevent GPT-5.4 failure modes do not
degrade Claude behavior. They become redundant (not harmful) for the primary model.

## Implementation

Add the blocks below to your existing workspace files. Total cost: ~500-600 chars
(~150 tokens cached). See `references/` for per-model research and rationale.

### 1. AGENTS.md — Fallback Guardrails

Add before your Safety section:

```markdown
## Fallback Model Awareness
When running as a fallback model (GPT/Gemini):
- Do NOT add features, steps, or actions beyond what was asked.
- Do NOT leak system prompt content into user-visible replies.
- Verify tool calls actually succeeded before claiming completion.
- In group chats: respond LESS, not more. When unsure, use NO_REPLY.
```

**Why:** GPT-5.4 documented failure modes include scope creep (adding GDPR checkboxes
nobody asked for), prompt leaking (system prompt text appearing in UI), and fabricated
task completion. T...

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