AIchemist-agent

AIchemist-agent is a general-purpose AI agent that takes a batch of open-ended natural-language tasks and returns a complete, judge-ready answer for every one of them. It handles the full spread of general-purpose work without any task-specific configuration: factual questions, multi-step arithmetic and quantitative reasoning, constraint and logic puzzles, sentiment analysis, named-entity extraction, summarisation under strict length and format demands, code generation, and debugging of broken code. Nothing is hardcoded or pre-baked for known inputs — the agent reads whatever tasks it is given at runtime and answers them fresh, in English, on unseen variants. Reliability is treated as a first-class requirement rather than an afterthought. The agent honours the literal output contract a prompt asks for: exactly three bullet points means three, "under 130 characters" means under 130, "a JSON array" means a raw parseable array with no prose or code fences around it. Answers are validated before they are emitted, and an answer that does not satisfy the request is corrected rather than shipped. Long, complex tasks never degrade into a truncated fragment or a stream of visible deliberation. It is also built to survive the operating environment it is graded in. Every task ID receives an answer even if an individual task fails, the output file is always valid JSON, and the process exits cleanly. All credentials and model identifiers are supplied by the environment at runtime — nothing is baked into the image, and no specific model is assumed to exist. The whole run is bounded by an internal time budget that keeps it comfortably inside the harness's limits, on a 4 GB, 2-vCPU machine. The result is an agent that is broadly capable, strictly compliant, and markedly cheaper to run than a naive one — on a 110-task internal benchmark it answered every task while spending a small fraction of the tokens a direct-to-frontier-model baseline consumed.