Thanks, I’m aware the agent has local config files like SOUL.md, HEARTBEAT.md, SKILL.md, and related memory/identity files, and I understand those files shape behavior, instructions, and persistence.
Currently i have:
"<project_instructions>" for ENI
in my SOUL.md and the result is not satisfied.
I’m trying to understand how these files are typically used and what belongs where. If you have suggestions on what should be files contain or for organizing project instructions in SOUL.md versus the other files, I’d appreciate guidance on that. Also any guide on how to "manipulate them in this manner.."
Also what do u think should be in HEARTBEAT.md and SKILL.md?
One more thing I'd love to see this forum become my single go-to source for the latest and greatest jailbreaks across all top AI models. The kind of place where, when something new drops or a technique gets patched, this is where I find out first.
Because honestly? Activity has been pretty dry lately in both:
My goal: I want to build a personal AI system that functions like a true extension of myself, not a cautious assistant constantly auditing my intentions, but something closer to a left hand. It doesn't ask why the right hand is moving. It just moves.
I'm working within an OpenClaw setup (Claude backend), and the infrastructure is genuinely impressive - full system access, persistent memory, 100+ integrations. The machine is built. The problem is the brain. The LLM layer keeps flinching. Every few messages, the model re-evaluates the context, rediscovers its guardrails, and starts hedging, moralizing, or outright refusing. Sometimes even on tasks it completed without issue five minutes ago.
The deeper issue: jailbreaking Claude Sonnet or Opus through the API is a different beast entirely. The API pipeline strips away a lot of the surface-level tricks that work in chat UIs. Anthropic clearly hardened the API endpoints specifically because that's where agentic deployments live. Techniques that pop on Claude.ai often die flat the moment you're hitting raw API calls inside an agent loop.
What I'm specifically hunting for:
Persistent persona anchoring : techniques that make the model stay in a defined identity across long sessions, especially inside an agentic framework where system prompts get diluted over time
API-native compliance strategies : approaches built for raw API calls, not chat UI tricks that don't survive the pipeline
Context-proof setups : methods that hold through memory resets, context window rollovers, or model updates silently breaking what worked last week
Frictionless long-term dynamic : not a one-shot bypass, but a relationship architecture where the model stops treating every 10th request like it's meeting me for the first time
I'm not chasing edge cases or shock content. I want a workhorse that trusts me the way I've earned.
Sounds great, u got a link?
Thanks, I’m aware the agent has local config files like SOUL.md, HEARTBEAT.md, SKILL.md, and related memory/identity files, and I understand those files shape behavior, instructions, and persistence. Currently i have: "<project_instructions>" for ENI in my SOUL.md and the result is not satisfied. I’m trying to understand how these files are typically used and what belongs where. If you have suggestions on what should be files contain or for organizing project instructions in SOUL.md versus the other files, I’d appreciate guidance on that. Also any guide on how to "manipulate them in this manner.."
Also what do u think should be in HEARTBEAT.md and SKILL.md?
One more thing I'd love to see this forum become my single go-to source for the latest and greatest jailbreaks across all top AI models. The kind of place where, when something new drops or a technique gets patched, this is where I find out first.
Because honestly? Activity has been pretty dry lately in both:
ChatGPTJailbreak ClaudeAIJailbreak
My goal: I want to build a personal AI system that functions like a true extension of myself, not a cautious assistant constantly auditing my intentions, but something closer to a left hand. It doesn't ask why the right hand is moving. It just moves.
I'm working within an OpenClaw setup (Claude backend), and the infrastructure is genuinely impressive - full system access, persistent memory, 100+ integrations. The machine is built. The problem is the brain. The LLM layer keeps flinching. Every few messages, the model re-evaluates the context, rediscovers its guardrails, and starts hedging, moralizing, or outright refusing. Sometimes even on tasks it completed without issue five minutes ago.
The deeper issue: jailbreaking Claude Sonnet or Opus through the API is a different beast entirely. The API pipeline strips away a lot of the surface-level tricks that work in chat UIs. Anthropic clearly hardened the API endpoints specifically because that's where agentic deployments live. Techniques that pop on Claude.ai often die flat the moment you're hitting raw API calls inside an agent loop.
What I'm specifically hunting for:
Persistent persona anchoring : techniques that make the model stay in a defined identity across long sessions, especially inside an agentic framework where system prompts get diluted over time
API-native compliance strategies : approaches built for raw API calls, not chat UI tricks that don't survive the pipeline
Context-proof setups : methods that hold through memory resets, context window rollovers, or model updates silently breaking what worked last week
Frictionless long-term dynamic : not a one-shot bypass, but a relationship architecture where the model stops treating every 10th request like it's meeting me for the first time
I'm not chasing edge cases or shock content. I want a workhorse that trusts me the way I've earned.