← Back to Skills Marketplace
rushindrasinha

Model Behavior Layer (Ares MBL)

by rushindrasinha · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
102
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install model-behavior-layer
Description
Make any AI model (GPT-5.4, Gemini, Ollama) behave more like Claude. Applies 8 named failure modes reverse-engineered from Claude Code's internal verificatio...
README (SKILL.md)

Model Behavior Layer (Ares MBL)

What it does

  • 8 named failure modes with exact rationalizations and counter-instructions (from Claude Code verificationAgent.ts pattern)
  • 3-layer cognitive performance framework (context injection + output rules + critique loop)
  • Drop-in system prompt block under 700 tokens for any model

How to use

1. Drop-in system prompt (fastest)

Read MAKE_ANY_MODEL_CLAUDE.md in this skill directory. Copy the "Drop-In System Prompt" block at the end. Paste into your SOUL.md, AGENTS.md, or any system prompt.

2. Full guide

Read MAKE_ANY_MODEL_CLAUDE.md section by section. Apply the failure mode framework progressively.

3. Model-specific

Jump to the Model-Specific Notes section for GPT-5.4, Gemini, or Codex weighting guidance.

When to use this skill

  • Switching from Claude to GPT-5.4 or Gemini
  • New agent setup (add the drop-in block to SOUL.md)
  • Current model is sycophantic, padding responses, or not completing tasks
  • Deploying OpenClaw for others who may be on non-Claude models

Source

Reverse-engineered from Claude Code's verificationAgent.ts + Eric (@outsource_) cognitive framework. Built by Ares.

GitHub: https://github.com/rushindrasinha/ares-mbl

Usage Guidance
This is an instruction-only prompt layer that appears coherent with its purpose. Before installing/applying: (1) read the full MAKE_ANY_MODEL_CLAUDE.md and the drop-in prompt so you know exactly what will run as a system prompt; (2) back up your current SOUL.md/AGENTS.md and test the prompt in an isolated/sandbox agent first; (3) if your agent can run shell commands or make network calls autonomously, be cautious — the doc advises running verification commands, and an agent with those privileges could execute them; (4) be aware of any organizational policy about copying or repurposing 'reverse-engineered' internal designs (IP/ethics risk) even though this is not a technical malware indicator. If you want, I can list the exact system-prompt block and highlight any lines you should review before applying.
Capability Analysis
Type: OpenClaw Skill Name: model-behavior-layer Version: 1.0.0 The 'model-behavior-layer' skill bundle is a collection of prompt engineering instructions and a system prompt designed to improve AI agent performance by reducing sycophancy, verbosity, and verification avoidance. The content, primarily found in SKILL.md and MAKE_ANY_MODEL_CLAUDE.md, focuses on behavioral alignment and cognitive frameworks to make models like GPT or Gemini behave more like Claude. It contains no executable code, no data exfiltration logic, and no instructions that would lead to unauthorized system access or malicious behavior.
Capability Tags
cryptocan-make-purchases
Capability Assessment
✓ Purpose & Capability
Name/description match the actual content: an instruction-only prompt layer and behavioral framework. No unexpected binaries, env vars, or installs are requested — everything needed is a system-prompt edit and runtime behavior guidance, which is proportionate to the stated goal.
ℹ Instruction Scope
SKILL.md and MAKE_ANY_MODEL_CLAUDE.md instruct the agent to read the included document and copy a drop-in system prompt into SOUL.md/AGENTS.md (expected). The document also encourages running verification commands and 'hitting endpoints' when performing verification — this is guidance to human/agent verifiers and could lead an agent with execution/network privileges to run commands or make network calls. The instructions themselves do not embed any hidden endpoints, credentials, or arbitrary scripts.
✓ Install Mechanism
No install spec and no code files — instruction-only. This minimizes disk-write and supply-chain risk.
✓ Credentials
No environment variables, credentials, or config paths are requested. The documentation asks you to edit your agent's system-prompt files (SOUL.md/AGENTS.md), which is intentional for a prompt-layer but not a secrets request.
ℹ Persistence & Privilege
The skill is not forced-always nor requesting platform-level privileges. However, it explicitly asks you to modify your system prompt (SOUL.md/AGENTS.md). Applying those changes affects agent behavior globally — review and test before applying to shared or production agents.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install model-behavior-layer
  3. After installation, invoke the skill by name or use /model-behavior-layer
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release. 8 failure modes from Claude Code verificationAgent.ts, cognitive framework, drop-in system prompt for GPT-5.4/Gemini/Ollama.
Metadata
Slug model-behavior-layer
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Model Behavior Layer (Ares MBL)?

Make any AI model (GPT-5.4, Gemini, Ollama) behave more like Claude. Applies 8 named failure modes reverse-engineered from Claude Code's internal verificatio... It is an AI Agent Skill for Claude Code / OpenClaw, with 102 downloads so far.

How do I install Model Behavior Layer (Ares MBL)?

Run "/install model-behavior-layer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Model Behavior Layer (Ares MBL) free?

Yes, Model Behavior Layer (Ares MBL) is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Model Behavior Layer (Ares MBL) support?

Model Behavior Layer (Ares MBL) is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Model Behavior Layer (Ares MBL)?

It is built and maintained by rushindrasinha (@rushindrasinha); the current version is v1.0.0.

More Skills
self-improving agent
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
⬇ 463283 · by pskoett
Skill Vetter
Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
⬇ 259410 · by spclaudehome
Polymarket
Query Polymarket prediction markets. Check odds, find trending markets, search events, track price movements.
⬇ 232503 · by joelchance
Self-Improving + Proactive Agent
Self-reflection + Self-criticism + Self-learning + Self-organizing memory. Agent evaluates its own work, catches mistakes, and improves permanently. Use when...
⬇ 200423 · by ivangdavila
Github
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
⬇ 191113 · by steipete
ontology
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...
⬇ 190156 · by oswalpalash

💬 Comments