Skip to main content
Glama

架构决策

architecture_decide

Evaluates product type, platform, features, and commercial intent to recommend an architecture plan, preventing premature coding decisions.

Instructions

根据产品类型、平台、功能、商业化意图判断架构方案。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_typeYes产品类型描述
platformYes目标平台
featuresYes功能列表
commercial_intentNo是否有商业化意图
expected_usersNo预期用户规模individual

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
decisionYes
technicalProfileNo
riskLevelYes
blockersYes
Behavior2/5

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

The description does not disclose behavioral traits beyond its purpose. It does not mention whether the decision is deterministic, what the output format is, or any side effects. With no annotations provided, the description carries the full burden but adds minimal behavioral insight.

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 sentence that efficiently conveys the core purpose. It is front-loaded and contains no redundant information, though it could be slightly more informative.

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?

Given the output schema exists, the description does not need to cover return values. However, it omits context about optional parameters and enum options, which would help an agent understand the decision basis better. It is 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?

The input schema has 100% description coverage for all parameters. The description simply lists parameter names without adding extra semantics or constraints, so it aligns with the baseline score of 3 for high-coverage schemas.

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 that the tool determines an architecture plan based on inputs like product type, platform, features, and commercial intent. It uses a specific verb ('judge') and resource ('architecture plan'), but does not explicitly differentiate from sibling tools, though the domain is distinct.

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 guidance is provided on when to use this tool versus alternatives. The description only states what it does, lacking context for choosing it over siblings like 'acceptance_generate' or 'debug_guide'.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/georgelue0321-vibe/product-spec-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server