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juspay

FDEP MCP Server

by juspay

analyze_type_relationships

Analyze deep type relationships and dependencies in Haskell code to understand how types connect across modules, revealing architectural patterns and potential issues.

Instructions

Analyze deep type relationships and dependencies

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
type_nameYesType name to analyze
source_moduleYesSource module containing the type
analysis_depthNoDepth of relationship analysis
include_dependentsNoInclude types that depend on this type
module_filterNoModule pattern to filter results (optional)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'deep' analysis but doesn't specify what that entails—such as output format, performance implications, or side effects. For a tool with 5 parameters and no output schema, this is inadequate, as it leaves critical behavioral traits undefined.

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

Conciseness4/5

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

The description is a single, efficient sentence with no wasted words, making it appropriately concise. However, it lacks front-loading of critical details like differentiation from siblings or behavioral context, which slightly reduces its effectiveness despite the brevity.

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

Completeness2/5

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

Given the tool's complexity (5 parameters, no annotations, no output schema) and rich sibling set, the description is incomplete. It doesn't explain what 'analyze' entails in terms of output or behavior, nor does it guide usage relative to alternatives. This leaves significant gaps for an agent to operate effectively.

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 fully documents all 5 parameters. The description adds no additional meaning beyond the schema, such as explaining how parameters interact or typical use cases. This meets the baseline of 3, as the schema does the heavy lifting, but the description doesn't enhance understanding.

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

Purpose3/5

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

The description states the tool's purpose as analyzing type relationships and dependencies, which is clear but vague. It specifies 'deep' analysis but doesn't differentiate from siblings like 'get_type_dependencies' or 'build_type_dependency_graph' in terms of scope or methodology. The verb 'analyze' is generic compared to more specific sibling verbs like 'get', 'build', or 'find'.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives is provided. The description doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage from the name alone. With many sibling tools for dependency analysis, this lack of differentiation is a significant gap.

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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