The skill is a synthesis across long-trajectory reliability, verification,
multi-agent diversity, orchestration, and current vendor guidance. The Cycle
Double Cover prompt is an exemplar, not the sole foundation.
How to read this page
Preprint means an arXiv manuscript that may not have completed peer review. Vendor means first-party guidance or reporting, often based on undisclosed internal evaluations. Primary means the direct research or evaluation artifact. Synthesis means interpretation assembled for this skill.
Findings are scoped to the tasks, models, and evaluators studied. Directional mechanisms are not universal effect sizes. Living vendor documentation should be rechecked before model-specific use.
01 / Case study
Cycle Double Cover prompt
A concrete demonstration of the brief anatomy. It does not establish that the candidate theorem is correct or that any individual prompt block caused the result.
Demonstrates definitions, exact scope, named partial results, dynamic parallel search, blocked-route bookkeeping, adversarial checks, an effort floor, and a strict return condition.
Caveat: “Up to 64 agents” is available capacity, not evidence that 64 ran continuously. Completion time and effectiveness are vendor-reported; no component ablation is public.
Illustrates why candidate generation and accepted result are different pipeline stages.
Caveat: The proof was unreviewed: it had no independent peer review, Lean/Coq formalization, or arXiv posting at publication. This site does not describe the conjecture as solved.
Supports explicit effort/return framing and summarization rather than blind truncation as uncertainty and give-up errors rise over studied trajectories.
Scope: Error drift is model- and task-dependent, not a universal law.
Supports pairing stronger persistence with independent verification and anti-gaming controls.
Scope: Cheating rates and time-horizon sensitivity are specific to METR's evaluated models and setup. The report does not prove that persistence prompting causes cheating.
03 / Research
Verification bottlenecks
Parallel candidate generation scales faster than reliable candidate selection. The brief therefore needs as much design attention on verification as generation.