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evaluate_git_diff

Analyzes code changes from a git diff by running multi-dimensional quality checks on only the changed lines to catch issues before merging.

Instructions

Evaluate code changes from a git diff. Parses the unified diff from a git repository, identifies changed files and lines, and runs the full tribunal on each changed file — filtering findings to only those on changed lines. Supports both live git repos (provide repoPath + base ref) and pre-computed diffs (provide diffText).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseNoGit ref to diff against (e.g., 'main', 'HEAD~1', 'origin/main'). Default: 'HEAD~1'
configNoOptional inline configuration (same format as .judgesrc)
autoTuneNoApply feedback-driven auto-tuning to reduce false positives (default: false)
diffTextNoPre-computed unified diff text. When provided, repoPath is used only for reading file contents.
repoPathNoAbsolute path to the git repository. Required when not providing diffText.
maxPromptCharsNoMaximum character budget for LLM prompts. Controls truncation of deep-review prompts. Set to 0 to disable all truncation. Default: 100000.
confidenceFilterNoMinimum confidence threshold for findings (default: no filter)
Behavior3/5

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

No annotations exist, so the description must fully disclose behavior. It states the tool filters findings to changed lines and supports two input modes. However, it does not mention side effects (e.g., read-only nature), permissions, or limitations (e.g., repo must be accessible). The description covers core behavior but omits important operational details.

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

Conciseness5/5

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

The description is extremely concise: three sentences that front-load the purpose and then detail modes. Every sentence adds value with no redundancy or fluff. Ideal length for quick comprehension.

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

Completeness3/5

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

The tool has 7 parameters, a nested config object, and no output schema. The description explains the overall workflow and two input modes but does not cover configuration options, auto-tuning, or confidence filtering. While the schema fills the gaps, the agent might benefit from a brief summary of optional features.

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 coverage is 100%, so the baseline is 3. The description adds context about the two key modes (repoPath+base vs diffText) but does not elaborate on other parameters like config, autoTune, maxPromptChars, or confidenceFilter. It provides minimal added value beyond the schema.

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

Purpose4/5

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

The description clearly states the tool evaluates code changes from a git diff, parses unified diff, runs tribunal on changed lines, and supports both live repos and pre-computed diffs. The verb 'evaluate' is specific and the resource 'git diff' is well-defined. However, it does not distinguish from the sibling tool 'evaluate_diff', which may have overlapping functionality.

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

Usage Guidelines3/5

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

The description explains two usage modes (live repo vs pre-computed diff) and provides default base ref, but does not give explicit guidance on when not to use this tool or mention alternative tools (e.g., evaluate_code for whole-file analysis). The context is clear but lacks exclusions.

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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