Multi-agent chatbot murder mystery

Game concept & implementation

• Web-based, multi-agent AI murder mystery where players interrogate suspects to deduce the killer, method, and secrets.
• Each suspect has a hidden secret; clues about one character are embedded in others’ context windows, encouraging cross-interrogation.
• System uses a “Critique & Revision” pipeline:
  • A “violation bot” checks each suspect response against global and character-specific “Principles” (e.g., no direct confessions).
  • A “refinement bot” rewrites responses that violate rules.
• Distinct personality, secret, and violation contexts plus consistent “Detective Sheerluck” roleplay are used to shape behavior.
• Code and full story JSON are open source; players can modify characters or run locally with their own Anthropic API key.

Performance and deployment

• The app repeatedly became non-responsive or extremely slow due to “hug of death” traffic from HN.
• Author upgraded the server and worker count; still, many report long response times and timeouts.
• Recommended workaround: clone the repo, add an API key, and run locally for speed and reliability.

Gameplay experience & difficulty

• Some players enjoyed the concept and narrative, comparing it to other mystery games and jailbreaking challenges.
• Others quickly “broke” the game:
  • Forcing suspects or the officer to confess in a handful of prompts.
  • Using meta-prompts to reveal full solutions or internal prompts.
• A few note issues like mid-sentence cutoffs and unclear game feedback, making it hard to know whether an action “worked.”

Safety, censorship & jailbreaks

• One user triggered an overzealous safety response to a benign “overview” question, highlighting guardrail brittleness.
• Several discuss trying jailbreak-style prompts as their default “gameplay,” noting this turns all such games into exploit puzzles.
• Debate over safety vs. over-censorship:
  • Some want cheaper, less-filtered model APIs to avoid moralizing refusals.
  • Others emphasize risks of misinformation, scams, and harmful uses, arguing constraints are necessary.

Quality, polish & future potential

• Mixed views on polish: some praise it as a fun hackathon project; others criticize React defaults and performance as “low effort” or “shovelware.”
• Suggestions include:
  • Letting users author their own mysteries via the existing JSON structure.
  • Supporting local/open-source models (e.g., small quantized models, browser-based).
  • Caching frequent prompts to reduce API calls and latency, possibly using a cheaper model for similarity checks.
• Author mentions logging thousands of interactions for potential fine-tuning; one commenter flags the need for explicit user consent.