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jiawei686

jev-domain-mcp

by jiawei686

review_patch

Analyze a git diff with optional context to return a code-review verdict, safety probability, severity score, and a confidence-gated action (auto-merge or human review).

Instructions

Code-review gate powered by Jev (System One decision model). Given a git diff and optional context, returns a verdict (approve / request_changes / needs_discussion), a safety probability, a severity score, a calibrated confidence, and an action (auto_merge / human_review). Only execute auto_merge on high confidence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
diffYesThe git diff or patch to review.
contextNoOptional surrounding context (file purpose, PR description).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and discloses that this is an AI decision gate returning a verdict, safety probability, severity, confidence, and action. The caution 'Only execute auto_merge on high confidence' implies the tool itself does not execute the merge and warns about the risk, adding behavioral context beyond annotations.

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 compact and front-loaded with the core purpose. Every sentence contributes: the first defines the tool, the second lists inputs and outputs, and the third gives a critical safety instruction. There is no filler.

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

Completeness5/5

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

Because there is no output schema, the description correctly explains all return values (verdict, safety probability, severity score, calibrated confidence, action). It also covers the required and optional inputs and the action condition, making the tool fully invocable by an agent.

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 rephrases the inputs ('git diff and optional context') but adds no new detail beyond the schema's own parameter descriptions, so it does not elevate the score.

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 opens with 'Code-review gate powered by Jev (System One decision model)', which immediately states the tool's purpose with a specific verb and resource. It then enumerates the exact inputs and outputs, clearly distinguishing this from the sibling screen_content, which is unrelated.

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 clearly indicates when to use the tool (given a git diff and optional context) and gives an explicit instruction on how to act on its result: 'Only execute auto_merge on high confidence.' It does not name alternative tools or exclusions, but the only sibling is screen_content, so no routing conflict exists.

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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