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infer_architecture_tool

Scans a repository to detect its architectural pattern (REST API, CLI, library, web frontend), find entry points and modules, and save the hypothesis to reforge-state.json.

Instructions

Infer the architectural pattern of a repository.

Runs scan_repo, detects pattern (REST API, CLI tool, library, web frontend), identifies entry points and logical modules, stores the result in reforge-state.json under architecture_hypothesis, and returns the inference.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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 transparently describes the multi-step process (runs scan_repo, detects patterns, identifies entry points/modules), the side effect of storing results in reforge-state.json under architecture_hypothesis, and the return of the inference. This goes beyond a simple one-liner and gives the agent useful behavioral context.

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 concise at two sentences, with the purpose front-loaded. The second sentence is a dense list of steps, but it remains readable. Every sentence contributes to understanding the tool's behavior, though the structure could be improved with bullets or clearer separation of steps.

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 main behavior, side effect, and return value. Since an output schema exists, the return format is likely documented elsewhere. It could mention prerequisites or error cases, but for an analysis tool with one parameter and a clear process, it is fairly 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 description coverage is 0%, so the description must compensate. It indirectly clarifies the single parameter repo_path by referencing 'a repository,' but it does not explicitly define the parameter format or constraints. The meaning is inferable from context, but the description adds minimal explicit value beyond the schema's bare field name.

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 purpose: 'Infer the architectural pattern of a repository.' It specifies the resource (repository) and the action (infer), and distinguishes itself from siblings like scan_repo_tool by describing a higher-level analysis that builds on scan_repo.

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 by mentioning it runs scan_repo and returns an architectural inference, but it does not explicitly state when to use this tool versus alternatives or provide exclusions. The context suggests it is for deeper architectural analysis, but no explicit 'when' or 'when not' guidance is given.

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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