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audit_judge

Run all available checks on judge outputs to assess quality and identify which probes require missing variants for complete evaluation.

Instructions

Run every check this data supports, and say what's missing for the rest.

The "I have an eval log, is my judge okay?" entry point. Runs the free probes unconditionally, adds calibration and the human-controlled probes if gold labels are supplied, and reports which probes need variants you haven't generated yet — with the command to generate them.

Args: path: judge outputs. gold_path: human labels. Without these, roughly half the checks are unavailable, and the ones that need a quality control will say so rather than reporting a confounded number. judge_family: e.g. "claude". scale_min/scale_max: declared rubric bounds. verbose: full evidence for every finding (long).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
verboseNo
gold_pathNo
scale_maxNo
scale_minNo
judge_familyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that free probes run unconditionally and calibration probes are added with gold labels, but it does not explicitly state whether the tool has side effects, requires specific permissions, or is idempotent. Since no annotations are provided, the description carries the full burden, and this lack of detail leaves some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary sentence, context paragraph, and Args list. It is clear and to the point, though slightly verbose for the context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, conditional behavior) and the presence of an output schema, the description covers the overall workflow, including what happens under different conditions and what the output contains (reports missing probes with generation commands). It is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description's Args section adds meaning to all six parameters, explaining the purpose of each (e.g., gold_path enables half the checks, verbose provides full evidence). This compensates for the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool runs every check supported by the data and reports what's missing, positioning it as the entry point for auditing a judge. It distinguishes itself from siblings like bias_probe and calibrate_judge by specifying its comprehensive check-running role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description specifies when to use (when you have an eval log and need to check if the judge is okay) and provides conditional behavior (gold labels trigger additional checks). However, it does not explicitly state when not to use or compare with alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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