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framework_nodes

Identify critical hub modules in Swift codebases by combining structural importance (SIR) and connectivity, returning a ranked list of framework nodes.

Instructions

Identify framework-like (hub) modules using SIR + module connectivity.

A "framework node" is a module that is both:

Structurally important (high SIR/PageRank — central to the graph)
Highly connected (calls/imports many modules — orchestrator/hub role)

Framework score = 0.6 × normalized SIR + 0.4 × normalized connectivity, both auto-computed on first call. High-scoring modules are critical hubs: architecturally central AND complex in their interactions.

:param top: Number of top framework-like modules to return (default 20). :return: Markdown-formatted ranking table of framework nodes.

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": "framework_nodes"
  }
}

Input Schema

Name	Required	Description	Default
`top`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 10, 2026

TDQS

A4/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the scoring formula, notes that values are auto-computed on first call (implying potential caching), and describes the output format as a Markdown table. This is transparent about computation and return type, though it doesn't mention side effects or data freshness.

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 structured with a clear opening line, a definition, the formula, and a return note. It's front-loaded with the core purpose and avoids unnecessary fluff. It's slightly longer than strictly necessary, but each sentence contributes meaningful information.

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?

Given the tool's simplicity (one parameter) and the presence of an output schema, the description is fairly complete. It explains the algorithm, output format, and performance note about auto-computation. It doesn't cover edge cases or usage examples, but for this tool, the essentials are covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter `top` is explicitly explained in the description with its purpose and default value. Even though the schema itself has no description, the tool description provides full semantic meaning, going beyond what the schema alone offers. This fully compensates for the 0% schema description coverage.

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 the tool's purpose: identifying framework-like (hub) modules using SIR and connectivity. It defines what a framework node is and provides a specific scoring formula. While it doesn't explicitly differentiate from siblings like centrality or rank_nodes, the unique combination of SIR and connectivity makes it distinct.

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 when to use the tool (when you need to find architecturally central and highly connected hub modules) but does not explicitly mention alternatives or when not to use it. It provides context about high-scoring modules being critical hubs, but lacks exclusionary guidance compared to sibling tools.

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