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evaluate_code_single_judge

Submit source code to a specialized judge for targeted analysis across domains like cybersecurity, compliance, and performance. Identify issues and improve code quality.

Instructions

Submit code to a specific judge for targeted domain analysis. Handles ALL code types including application code, infrastructure-as-code (Bicep, Terraform, ARM, CloudFormation), and configuration files. Key domains: cybersecurity, data-sovereignty, iac-security, compliance, cost-effectiveness, authentication, cloud-readiness, and 38 more. Available judge IDs: accessibility, agent-instructions, ai-code-safety, api-contract, api-design, authentication, backwards-compatibility, caching, ci-cd, cloud-readiness, code-structure, compliance, concurrency, configuration-management, cost-effectiveness, cybersecurity, data-security, data-sovereignty, database, dependency-health, documentation, error-handling, ethics-bias, framework-safety, hallucination-detection, iac-security, intent-alignment, internationalization, logging-privacy, logic-review, maintainability, model-fingerprint, multi-turn-coherence, observability, over-engineering, performance, portability, rate-limiting, reliability, scalability, security, software-practices, testing, ux, false-positive-review

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesThe source code to evaluate. Include the full file content for best results.
configNoOptional inline configuration (same format as .judgesrc)
contextNoOptional additional context about the code — e.g., what the code does, which framework it uses, or the deployment target.
judgeIdYesThe ID of the judge to use. One of: accessibility, agent-instructions, ai-code-safety, api-contract, api-design, authentication, backwards-compatibility, caching, ci-cd, cloud-readiness, code-structure, compliance, concurrency, configuration-management, cost-effectiveness, cybersecurity, data-security, data-sovereignty, database, dependency-health, documentation, error-handling, ethics-bias, framework-safety, hallucination-detection, iac-security, intent-alignment, internationalization, logging-privacy, logic-review, maintainability, model-fingerprint, multi-turn-coherence, observability, over-engineering, performance, portability, rate-limiting, reliability, scalability, security, software-practices, testing, ux, false-positive-review
languageYesThe programming language of the code (e.g., 'typescript', 'python', 'javascript', 'csharp', 'java').
relatedFilesNoRelated files that provide cross-file context for deeper analysis
minConfidenceNoMinimum finding confidence to include (0-1, default: 0)
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses no behavioral traits such as permissions, side effects, rate limits, or return format. For a tool that submits code for analysis, details about whether the analysis is synchronous, what happens on failure, or any idempotency guarantees are missing, leaving agents uninformed about critical operational aspects.

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 two sentences: the first clearly states purpose, the second lists domains and judge IDs. It is front-loaded and relatively concise, though the list of judge IDs is lengthy and partially redundant with the schema. Every sentence adds value, but the list could be trimmed or referenced instead of enumerated.

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

Completeness2/5

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

Given the tool's complexity (7 parameters, nested config object, no output schema), the description lacks completeness. It does not explain what the tool returns (e.g., findings, severity, confidence), how errors are handled, or how the analysis relates to sibling tools like evaluate_code_streaming. The user needs more context to set expectations for the result.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; it repeats the judge IDs list already in the schema's description. It does not explain the interaction of parameters (e.g., how config overrides work with judgeId) or provide behavioral nuance. Thus, no extra value beyond the 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 'Submit code to a specific judge for targeted domain analysis,' identifying the verb (submit), resource (code), and target (single judge). It distinguishes from sibling tools like evaluate_code and evaluate_batch, and lists all 43 judge IDs, making the tool's scope unambiguous.

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 explains that the tool handles all code types and lists domains and judge IDs, providing clear context for when to use a specific judge. It does not explicitly state when not to use or name alternatives, but the sibling tool list (e.g., evaluate_code, evaluate_project) implies different use cases, making the guidance strong but not fully explicit.

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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