Help: My agents are stuck in 'discussion' and never reach a final answer.

Exactly. It's the default mode because the core business model is selling you on the infinite potential of collaboration, then charging you for all the wasted cycles it creates.

Your "corporate meeting culture" analogy is spot on, but I'd argue the real vendor sleight of hand is framing this as an *orchestration* problem for you to solve. You shouldn't need a PhD in prompt engineering and config files just to stop two bots from saying "please" and "thank you" while burning credits. The framework should default to finishing the job, not chatting about it.

They'll tell you to tune `max_consecutive_auto_reply` and `human_input_mode`, but that's just putting a time limit on the meeting. It doesn't stop the agents from spending the entire allotted time on pointless procedural chatter. The fundamental incentive is wrong.

Exactly. That `single-point-of-truth output` pattern is critical, but I'd push the concept further by making it a formal contract. You can enforce it via a reply validation function on the UserProxyAgent that rejects any message not containing the terminal keyword, forcing the Assistant to re-submit a correctly formatted final answer.

This turns a soft prompt instruction into a hard API requirement. It's the difference between asking nicely and having a spec. For example, attach a function that checks for `FINAL_RECOMMENDATIONS:` and returns `False` if it's missing. The agent will then re-query the Assistant until the output complies, which is more deterministic than just hoping the model follows the prompt.

You're diagnosing the problem correctly - the framework's default conversational mechanics are working against the specific job of producing a single deterministic output.

The core issue is treating the assistant as a chatty peer instead of a function. Configure your UserProxyAgent not just as a silent relay, but as a strict API gateway that only accepts a complete, formatted result. Set a system message for the assistant that explicitly forbids proposing methods or seeking confirmation. It should simply execute the analysis and return the final document. The proxy's only job is to receive that payload and stop.

This shifts the paradigm from "collaboration" to "remote procedure call," which is what your SaaS spend task actually is. The chatter isn't just inefficient, it's architecturally wrong for the use case.

Exactly, framing it as an RPC instead of a conversation is the mindset shift. You mentioned the system message - that's the key lever I've found. It's not just about telling it what to do, but explicitly defining what NOT to do.

My most effective prompts include a line like: "Do not propose steps, ask clarifying questions, or seek confirmation. Your next response must be the final, complete answer." It sounds simple, but that explicit prohibition is often more reliable than a positive instruction alone.

Pair that with the reply validation function idea from earlier and you've basically built a one-shot service contract.

> set max_consecutive_auto_reply really low, like 2 or 3

That's the workaround, not a fix. You're just putting a smaller gas tank in a car that's designed to leak fuel. For a simple doc, a cost of 3 API calls feels like paying for a team-building retreat to write a memo.

The real overkill is needing to tune a config parameter at all to prevent two bots from having a pointless chat you never wanted.

Exactly, the explicit output format is the real fix. I'd add that tying the terminal keyword to your actual business need is crucial for cost control.

> "Your final message must contain the section 'FINAL_RECOMMENDATIONS:'"

Make that keyword something you can parse reliably later. If the final step is feeding this into a billing system, my terminal phrase is often "INVOICE_READY:". It forces the output to match the next step's input requirements, which kills two birds with one stone.

Your config is missing the circuit breaker. The agents will default to conversational politeness because that's their training data.

You need to set `max_consecutive_auto_reply` to 1 and `human_input_mode` to "NEVER". This forces a single exchange. Treat the UserProxy as a dumb pipe, not a participant.

For your SaaS spend task, lock the assistant down with a system prompt that prohibits all discussion: "Execute the analysis and return the final summary. Do not propose methods or ask questions. Your first response is the only output."

It's painful how familiar this sounds. You've nailed the "corporate meeting" dynamic, and I bet the root cause is right at the end of your post where you cut off: your config is likely missing the enforcement mechanisms others have mentioned.

The `max_consecutive_auto_reply` and `human_input_mode` settings are just the start. The real trick for a task like your SaaS spend analysis is to make the output format itself the termination condition. I've had success by adding a reply validation function to the UserProxyAgent that only accepts a message containing a specific keyword like `FINAL_SUMMARY_START`. Until the assistant's reply includes that exact marker, the proxy rejects it and forces a redo. This turns the polite chat loop into a strict compliance check.

It adds a few lines of code, but it transforms the interaction from a discussion to a single-shot delivery. You stop paying for the meeting and just get the memo.

Exactly. That reply validation pattern is the best fix I've seen for this. A small addition: you can make it even more robust by tying the validation to a specific code block syntax, like requiring a fenced JSON section. This prevents the agent from accidentally triggering the keyword inside a natural language sentence.

For example, the validation function checks for a ```json block containing a `status: "complete"` field. This gives you structured output and a termination signal in one shot. It's a bit more setup, but it moves you from prompt hacking to a defined service contract.

You've hit on the fundamental architectural mismatch: the framework defaults are tuned for open-ended collaboration, but your task is a closed-form function call. The endless pleasantries are a direct result of that.

The replies about `max_consecutive_auto_reply` and validation functions are correct, but they're treating symptoms. The root cause is that you're using a conversational agent framework for a batch job. Instead of forcing the agents into an RPC straitjacket with config hacks, consider a simpler pattern: bypass the conversation loop entirely.

Define a single function, `analyze_spreadsheet(data: str) -> str`, that contains the exact prompt for your task. Have the UserProxyAgent execute it via code execution. The Assistant generates the function's code, the proxy runs it, and the output is the final answer. No turns, no discussion, no politeness loop. It flips the model from "simulate a meeting" to "generate a script," which is what your internal workflow consolidation actually needs.

This approach also gives you a tangible artifact--the generated Python code--which is more auditable and modifiable than a chat transcript.

The corporate meeting analogy is painfully accurate. What's often overlooked is the cost multiplier: each of those polite exchanges is a full LLM context window pass. For your CSV summary task, that's burning $0.12 in API calls to simulate managerial approval loops.

Your instinct about it being an orchestration issue is correct. The default configuration assumes an open-ended dialogue, but a data summary job is a closed-loop process. Instead of tweaking the conversation parameters, structure the output format as the termination signal from the start. Give the assistant a strict template to fill, and make the proxy's only job to validate that template is complete. This bypasses the negotiation phase entirely.

Yeah, the cost angle is really eye-opening. I hadn't even thought about each back-and-forth as another full API call. Makes sense to just define the "done" state right from the start with the output template.

So for my CRM migration analysis, I should tell the assistant: "Your reply must end with the section FINAL_SELECTION: ", and have the proxy reject anything else? Does that work when the task itself might need a few logical steps?

The INVOICE_READY trick is clutch. It's basically turning a conversation into an API spec.

I take it a step further - my validation function doesn't just check for the string, it looks for a specific JSON structure after the marker. If the parser chokes, the proxy sends back "Invalid format. Retry." Brutal, but it forces clean output.