tentra

get_quality_hotspots

Identify code files needing refactoring by ranking them based on complexity, recent changes, and test coverage gaps.

Instructions

Rank files by a composite score of cyclomatic complexity × churn × (1 - test coverage). Top refactor candidates.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_quality_hotspots"
  }
}

Input Schema

Name	Required	Description
`repo_id`	No	Repo ID (uses latest snapshot)
`snapshot_id`	No	Specific snapshot ID
`top_n`	No	Max hotspots to return, ranked by churn × complexity × (1-coverage)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.0Apr 18, 2026

TDQS

A3.7/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the ranking behavior and the composite score formula, which is valuable. However, it does not cover other behavioral traits such as performance characteristics, error handling, or data freshness (e.g., how 'latest snapshot' is determined). The description adds some context but leaves gaps in behavioral disclosure.

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 a single, efficient sentence that is front-loaded with the core purpose ('Rank files by a composite score...') and ends with the outcome ('Top refactor candidates'). There is zero waste, and every word earns its place, making it highly concise and well-structured.

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?

Given the tool's complexity (ranking based on multiple metrics) and lack of annotations and output schema, the description is somewhat complete but has gaps. It explains the ranking logic but does not describe the return format (e.g., structure of ranked files), error cases, or dependencies. For a tool with no output schema, more detail on outputs would be beneficial, though the purpose is clear.

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 schema already documents all parameters thoroughly. The description does not add any additional meaning or semantics beyond what the schema provides (e.g., it doesn't explain parameter interactions or provide examples). Baseline 3 is appropriate as the schema does the heavy lifting.

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 the tool's purpose with a specific verb ('Rank files') and resource ('files'), and it distinguishes itself from siblings by focusing on a composite score of cyclomatic complexity × churn × (1 - test coverage) to identify top refactor candidates. This is more specific than general analysis tools like 'analyze_codebase' or 'lint_architecture'.

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 implies usage for identifying refactor candidates based on a specific metric, but it does not explicitly state when to use this tool versus alternatives like 'list_god_nodes' or 'find_similar_code'. It provides context but lacks explicit guidance on exclusions or direct comparisons with sibling tools.

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