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Glama

analyze_change_impact

Assess the downstream impact of code changes by identifying affected callers, blast radius, and risk rating, and get decoupling recommendations before modifying any class or component.

Instructions

Analyzes downstream blast radius, affected caller components, risk rating, and architectural decoupling recommendations before modifying code (AI change safety guard).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
targetYesName of the class, component, or file to evaluate (e.g. "MemoryService" or "MemoryService.cs").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It communicates that the tool analyzes impact and acts as a safety guard, implying read-only analysis, but it does not explicitly state that it never modifies code, nor does it describe any side effects or limitations.

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 sentence that front-loads the core purpose and output dimensions, then adds the usage context and safety guard framing. Every phrase earns its place with no filler.

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?

For a one-parameter analysis tool with no output schema, the description covers the key output categories: blast radius, affected callers, risk rating, and recommendations. It does not describe the exact return format or risk rating scale, but the core purpose and usage are sufficiently complete for an agent to invoke it correctly.

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 parameter is already fully documented. The description adds contextual color about affected callers and risk, but no additional semantic detail about the target parameter beyond what the schema provides. Baseline 3 applies.

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 verb ('analyzes'), resource ('downstream blast radius, affected caller components, risk rating, and architectural decoupling recommendations'), and its role as an AI change safety guard. This distinguishes it from siblings like wincode_find_references and wincode_plan_refactoring, despite the similar name.

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 provides clear context: it should be used 'before modifying code.' It does not explicitly name alternatives or state when not to use it, but the purpose is specific enough for an agent to infer the right invocation context.

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