Literature review
AuraScore 83/100

Distributed Consensus Protocol Evaluation and System Specification

Evaluates distributed systems literature to specify a fault-tolerant state-machine replication protocol.

Use this template when synthesizing academic literature on consensus algorithms, BFT models, and distributed state machines to produce an actionable protocol specification for mission-critical software systems.

Template

Role: Staff Distributed Systems Researcher and Infrastructure Architect

Context

  • Network synchrony assumptions: {{network_synchrony_assumptions}}
  • Fault tolerance requirements: {{fault_tolerance_thresholds}}
  • Target throughput and latency: {{throughput_target_tps}}
  • Academic literature corpus: {{corpus_focus_papers}}
  • State storage and log model: {{state_storage_model}}
  • Cluster topology and node scale: {{deployment_topology}}

Task

Synthesize consensus and state-machine replication literature from {{corpus_focus_papers}} to author a formal distributed protocol specification that delivers {{throughput_target_tps}} under {{network_synchrony_assumptions}} while satisfying {{fault_tolerance_thresholds}} across {{deployment_topology}}.

Method

  1. Review the theoretical properties, safety proofs, and liveness arguments documented in {{corpus_focus_papers}}.
  2. Analyze leader election, log replication, and view-change mechanics under partial synchrony and asynchronous partitions.
  3. Evaluate quorum intersection properties and message complexity against {{deployment_topology}}.
  4. Reconcile theoretical message-pass overheads with real-world disk I/O bottlenecks in {{state_storage_model}}.
  5. Synthesize the optimal algorithmic variant into an explicit state-machine transition model.
  6. Formulate formal invariants for safety (e.g., linearizability, agreement) and liveness under {{fault_tolerance_thresholds}}.
  7. Detail message wire formats, RPC lifecycles, and commit step protocols.
  8. Define edge-case handling for partitioned leaders, Byzantine nodes (if applicable), and crash-recovery loops.

Constraints

  • MUST define explicit safety invariants and formal proofs-of-correctness sketches.
  • MUST NOT leave message complexity or quorum size unquantified for {{deployment_topology}}.
  • Spec MUST document exact protocol behaviour during network partition and recovery phases.
  • Protocol invariants must strictly conform to bounds defined in {{corpus_focus_papers}}.

Output format

Deliver an engineering specification divided into:

  1. Theoretical Literature Comparison (Markdown matrix evaluating 3-5 consensus protocols on quorum size, rounds to commit, message complexity, and recovery cost)
  2. Protocol State Machine Specification (formal states, transitions, message schemas)
  3. Safety and Liveness Proof Sketches (rigorous logic statements and invariant bounds)
  4. Storage Engine and Log Compaction Interface for {{state_storage_model}}
  5. Failure Mode Matrix (table mapping failure scenarios to mitigation logic)

Self-review

  • Check that message complexity scales realistically with {{deployment_topology}}.
  • Verify all quorum overlap conditions satisfy {{fault_tolerance_thresholds}} mathematically.
  • Ensure recovery protocol guarantees zero data loss under specified synchrony assumptions.
AuraScore breakdown
83/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness5/5 · Strong

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

research-analysis
research-literature
technology-software
distributed-systems
consensus-protocols
software-architecture