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code-lens

code-lens

by j0hanz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Detect API Breaking Changes

detect_api_breaking_changes
Read-onlyIdempotent

Analyze code diffs to detect breaking API changes. Automatically identifies the programming language.

Instructions

Detect breaking API changes. Prerequisite: generate_diff. Auto-infer language.

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": "detect_api_breaking_changes"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoPrimary language (e.g. TypeScript, Python, JavaScript, Go, Rust, Java). Auto-infer from files.

Output Schema

NameRequiredDescriptionDefault
okYesWhether the tool completed successfully.
resultNoSuccessful result payload.
errorNoError payload when ok is false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.12.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds 'Auto-infer language' and a prerequisite, which are useful but not extensive behavioral context.

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?

Two sentences, front-loaded with the core purpose, and zero wasted words. Every sentence earns its place.

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?

With an output schema and annotations, the description covers the prerequisite and auto-infer behavior. It is adequate for a simple tool but could mention what the output contains.

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 echoes the auto-infer language behavior already in the schema's description, adding no new parameter-specific meaning.

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 'Detect breaking API changes', which is a specific verb and resource. However, it does not differentiate from sibling tools like analyze_pr_impact, which may also involve breaking change detection.

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 mentions 'Prerequisite: generate_diff', providing some usage context. However, it lacks explicit when-not-to-use guidance or alternatives, relying on implied context.

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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