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Get architecture

get_architecture
DestructiveIdempotent

Get a clear architecture overview of any codebase: compact summary by default, or request specific aspects like dependencies, clusters, and routes. Scope analysis to a directory prefix for targeted insights.

Instructions

Get high-level architecture overview. DEFAULT (no aspects) is a compact summary — overview counts, languages, packages, entry_points; request more via aspects:[...] (structure, dependencies, routes, hotspots, boundaries, layers, clusters, file_tree) or ["all"]. 'clusters' runs Leiden community detection over the call/import graph, surfacing the de-facto modules (label, member count, cohesion score, representative top_nodes, binding packages/edge_types) — the real architectural seams, which often cut across the folder layout. Optional path scopes analysis to nodes under that directory prefix (file_path).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoOptional directory prefix to scope architecture (e.g. apps/hoa)
aspectsNoAspects to include. 'all' = everything; 'overview' = compact summary (all except file_tree); omit = all. 'cycles' is opt-in ONLY (never via all/overview): it scans the whole call graph for circular CALLS dependencies (SCCs of size > 1).
projectYes
Behavior1/5

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

The description describes a read-only analysis tool, but annotations mark destructiveHint:true and readOnlyHint:false. This is a direct contradiction, as the description never mentions any destructive or mutating behavior. Per the rubric, this scores 1.

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?

Every sentence adds value: it front-loads the core purpose, then efficiently explains defaults, aspects, clusters, and path scoping. There is no filler; the length is justified by the tool's complexity.

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?

The description covers the most important behaviors: defaults, aspect selection, cluster specifics, path scoping, and cycles. Given the tool's complexity and lack of output schema, it could benefit from describing typical return structure, but it provides enough detail for a high-level overview tool.

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 description adds substantial meaning beyond the schema: it explains the default behavior when no aspects are provided, the semantics of each aspect (especially clusters with its algorithm and output fields), optional path scoping, and the opt-in nature of cycles. This far exceeds the brief schema descriptions.

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 opens with 'Get high-level architecture overview,' a specific verb+resource statement. It clearly explains the tool's purpose and contrasts with siblings by focusing on architecture analysis rather than graph queries or code snippets.

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 usage when an architecture overview is needed and details how to request aspects, but it does not explicitly state when to use this tool over alternatives or provide exclusions. The context is clear but lacks direct alternative differentiation.

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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