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Documentation Index

Fetch the complete documentation index at: https://lab.pollack.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

Every benchmark defines a jury --- a cascade of judge tiers that evaluate the agent’s workspace. Judges come from the Agent Judge project. Benchmarks wire them together in benchmark.yaml.

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Cascaded Tiers

Tiers run in order. Each tier has a policy that determines whether evaluation continues:
PolicyBehavior
REJECT_ON_ANY_FAILIf any check fails, stop. Lower tiers are not evaluated.
ACCEPT_ON_ALL_PASSIf all checks pass, continue.
FINAL_TIERLast tier. Its result is the overall verdict.
This is how the code-coverage benchmark grades: 
jury:
  tiers:
    - name: build
      policy: REJECT_ON_ANY_FAIL
      checks:
        - type: maven-build
          goals: [clean, test]
    - name: coverage-preservation
      policy: REJECT_ON_ANY_FAIL
      checks:
        - type: coverage-preservation
    - name: coverage-improvement
      policy: ACCEPT_ON_ALL_PASS
      checks:
        - type: coverage-improvement
          min: 50.0
    - name: test-quality
      policy: FINAL_TIER
      checks:
        - type: test-quality-llm
          prompt: prompts/judge-practice-adherence.txt
          model: claude-sonnet-4-6
If the build fails (T0), coverage is never measured. If coverage regresses (T1), improvement is never checked. This prevents misleading scores from broken code.

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Built-in Judge Types

These are registered in JudgeFactory and available in any benchmark:
TypeModuleWhat it checks
file-existsagent-judge-coreA specific file exists in the workspace
file-contentagent-judge-coreFile content matches expected (exact or contains)
maven-buildagent-judge-exec./mvnw <goals> exits successfully
coverage-preservationagent-judge-execJaCoCo coverage >= baseline
coverage-improvementagent-judge-execJaCoCo coverage >= threshold
test-quality-llmagent-bench-agentsLLM evaluates test practice adherence

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file-exists

- type: file-exists
  path: hello.txt

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file-content

- type: file-content
  path: hello.txt
  expected: "Hello World!"
  match: EXACT    # or CONTAINS

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maven-build

- type: maven-build
  goals: [clean, test]

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coverage-improvement

- type: coverage-improvement
  min: 50.0       # Minimum instruction coverage percentage

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test-quality-llm

- type: test-quality-llm
  prompt: prompts/judge-rubric.txt   # Path relative to benchmark directory
  model: claude-sonnet-4-6
The LLM judge reads the prompt file, evaluates the workspace, and returns structured scores. Requires running via agent-bench-agents module (which has the Claude SDK dependency).

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Writing a Custom Judge

Judges implement the Judge interface from agent-judge-core: 
public class MyJudge implements Judge {
    @Override
    public Judgment judge(JudgmentContext context) {
        Path workspace = context.workspace();
        // Inspect the workspace...
        return Judgment.builder()
            .status(JudgmentStatus.PASS)
            .reasoning("Looks good")
            .build();
    }
}
Register it in JudgeFactory: 
factory.register("my-check", config -> new MyJudge());

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Benchmark YAML Schema

schema: bench.benchmark.v1
name: my-benchmark
version: "1.0"
description: "What this benchmark measures"
default-timeout: PT10M

jury:
  tiers:
    - name: tier-name
      policy: REJECT_ON_ANY_FAIL | ACCEPT_ON_ALL_PASS | FINAL_TIER
      checks:
        - type: <judge-type>
          # ... judge-specific config

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Task YAML Schema

Each task within a benchmark: 
schema: bench.task.v1
id: my-task
difficulty: easy | medium | hard
instruction: |
  What the agent should do.
timeout: PT10M        # Optional, overrides benchmark default
metadata:             # Optional, passed to judges
  key: value
setup:                # Optional, scripts run before agent
  - "command 1"
  - "command 2"
post:                 # Optional, scripts run after agent, before grading
  - "command 3"