Claude Code skill combines DeepMind Aletheia and Anthropic harness approaches

Technical implementation details

A developer has built a Claude Code skill that combines two recent research approaches: DeepMind's Aletheia math research agent and Anthropic's multi-agent coding architecture. The skill creates a synthesis that neither original implementation included.

The pipeline follows a Planner → Generator → Evaluator → Reviser structure. A key innovation is what the developer calls "blind pre-analysis" - the evaluator reasons about the correct approach before it ever sees the candidate code. This extends Aletheia's decoupling concept by having the evaluator form its own expectations first, then grade solutions against them.

After the blind analysis, the evaluator runs the code and grades it against concrete criteria: correctness, completeness, security, resilience, and quality. It returns a structured verdict (CORRECT / FIXABLE / WRONG) that drives targeted revision.

Installation and usage

Installation requires creating a directory and cloning the repository:

mkdir -p ~/.claude/skills/aletheia
# clone repo, copy SKILL.md + evaluator.md + planner.md

Usage examples from the source:

• /aletheia Build a rate limiter middleware for Fastify using Redis
• /aletheia review src/routes/auth.ts
• /aletheia quick Fix the N+1 query in the dashboard

The skill is available at https://github.com/zhadyz/aletheia-harness.

Research context

DeepMind's Aletheia represents a shift from convergent thinking (reproducing known solutions) to divergent thinking (generating original mathematical results). Anthropic's harness research focused on multi-agent coding architecture but lacked chain-of-thought decoupling in the evaluator. This implementation combines both approaches into a single pipeline.