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

No annotations are provided, so the description carries the full burden. It usefully discloses the shape of the returned content (需求、步驟、程式碼與常見錯誤 / requirements, steps, code, common errors), which tells the agent what a result contains. It says nothing about permissions, rate limits, or how the tutorial is selected, leaving real gaps for a no-annotation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence that front-loads the verb and resource before listing topics and output contents. No filler, though the parenthetical topic list is long enough to slightly blunt the core purpose.

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

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

With no output schema, the description does describe the return payload (requirements, steps, code, common errors), which is helpful. However, a two-parameter tool with an undocumented id parameter and no usage routing leaves the agent guessing on inputs and on when to pick this over its four lookup-style siblings.

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

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

Schema coverage is only 50%: q has a description ('關鍵字，例如 MCP、llms.txt') but id has none. The description never explains the parameters or how q and id relate — e.g., whether id retrieves a specific tutorial while q is a keyword search. It does not compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (取得...教學 / 'get implementation tutorials') and enumerates the covered topics (MCP servers, llms.txt, FAQPage JSON-LD, robots.txt, x402, token counting). This distinguishes it from conceptual siblings like explain_term and compare_concepts, though it never names those alternatives explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance. The agent must infer from the resource name that this is for step-by-step implementation guides rather than definitions (explain_term), topic lists (list_topics), or glossary lookups (search_glossary). No prerequisites or exclusions are stated.

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