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get_architecture_overview

Retrieve a high-level architecture overview grouped by semantic layers—Core, Services, UI, Infra, and Tests—to understand a workspace's structure.

Instructions

High-level architecture overview grouped by semantic layers (Core, Services, UI, Infra, Tests).

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_architecture_overview"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspacePathNoOptional workspace root path.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.80.5

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the grouping taxonomy (a useful output-structure hint) but says nothing about whether the call is read-only, whether it scans or requires an existing index, how large the response might be, or how deep the 'high-level' view goes. For a no-annotation tool this leaves major gaps.

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?

A single front-loaded sentence with no filler, and the layer taxonomy is placed where it is immediately visible. It is a fragment rather than a full sentence, but nothing is wasted.

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?

There is no output schema, so the description is the only source of return-value information; it does communicate the grouping by semantic layers, which is the key structural fact. It still does not explain what each layer entry contains or how this differs from the near-identically named architecture siblings, leaving the definition only minimally complete.

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% for the single optional workspacePath parameter, and its schema description already explains it as an optional workspace root path. The description adds no additional meaning about defaults or path semantics, so the baseline 3 applies.

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 names the resource (architecture overview) and specifies the shape of the result: grouped by semantic layers Core, Services, UI, Infra, Tests. That is concrete enough to know what the tool returns. It does not, however, distinguish itself from siblings like get_architecture_map or get_architecture_view, which sound extremely similar.

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?

There is no when-to-use guidance at all: no mention of when this overview is preferable to get_architecture_map, get_architecture_view, or export_architecture_diagram, and no prerequisites such as whether the workspace must be indexed first. The agent must infer usage from the name alone.

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