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list_design_options

Turn an idea into technology options plus fixed prompts for direct solutions, GitHub research, higher-level design breakdowns, reverse reasoning, and risk checks.

Instructions

给一个想法列出“技术选项 + 拓展视野固定位”。

除了具体技术选项,还会固定返回:

  • 直接给方案

  • 去 GitHub 找思路

  • 拆解上位设计

  • 反向梳理

  • 风险评估

这样用户/人可以选择从哪个角度推进,而不是只能选“懂不懂某个技术”。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ideaYes
domainNo
max_optionsNo
search_resultsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose one meaningful behavioral trait: the return always includes five fixed expansion slots in addition to dynamic options. That tells the agent what to expect in the output. It says nothing about read-only nature, side effects, permissions, or whether it triggers downstream calls.

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?

Purpose is front-loaded in the first sentence, followed by an efficient bulleted enumeration of the fixed slots. The closing sentence adds justification but is somewhat redundant with the earlier framing of choosing angles.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotations to lean on, so the description must carry the load. It explains the fixed slots but not the dynamic option format, and it leaves three of four parameters undocumented. For a tool with 4 params at 0% coverage, this is a substantive gap.

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

Parameters2/5

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

Schema description coverage is 0% and the description documents essentially only the 'idea' input implicitly. The domain, max_options (default 12), and search_results parameters are unexplained in both schema and description, leaving their semantics and interplay unclear.

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 states a concrete purpose: for a given idea, produce a list of technical options plus a fixed set of expansion perspectives (direct solution, GitHub ideas, upper-level design decomposition, reverse reasoning, risk assessment). This is more than a tautology and the listed slots map recognizably to sibling tools. It is slightly abstract about what a 'technical option' actually is, keeping it from a 5.

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?

It implies the usage pattern: present options so the user can choose which angle to pursue, rather than judging technical familiarity. That is useful implied guidance for a menu/entry-point tool. However, it never states when to call this versus the sibling tools it routes to, nor any prerequisites or exclusions.

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