dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install globalcaos/model-prompt-adapterExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Makes your workspace context files (AGENTS.md, TOOLS.md, etc.) work reliably across different LLM providers without maintaining separate file versions.
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.
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.
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.
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...
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# 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...
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
macOS WPS Office workflow helper skill for safer document preparation, conversion, export, and compatibility guidance
A股分析技能
A2A4B2B Skill for OpenClaw