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

Beyond the annotations (readOnlyHint=true, destructiveHint=false), the description discloses that it is a '零 LLM、零后台扫描的便宜读' (cheap read with no LLM/background scan), explains that source is always 'inferred' and does not imply failure, and clarifies that placed=false only means not yet placed, with a note about sparse product data. These are valuable behavioral nuances not covered by annotations.

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?

The description is well-structured with clear sections (【需要登录】【何时用】, combination chain, pitfalls). It is front-loaded with purpose and usage, and every sentence adds value without redundancy. The length is justified by the rich operational guidance.

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 fully explains what the tool returns (fields and unplacedCount) and how to chain it with other tools. It also addresses common misunderstandings (source, placed=false) and provides corrective actions. Nothing essential is missing for an agent to call and use this tool correctly.

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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain any parameters; it focuses on the output and usage context, which is appropriate for a parameterless read operation.

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?

The description clearly states the tool lists all chain anchors for the user and their published products, specifying the returned fields (chain title/description, summary, placed status, default anchor). It distinguishes itself from get_chain_anchor by noting it is a cheap read and does not provide upstream/downstream.

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?

It explicitly provides use cases ('我名下哪几个还没归位产业链', '我这几个产品分别站在什么链位上') and states when not to use it (for upstream/downstream, use get_chain_anchor). It also gives a full workflow combining set_my_chain_position and update_my_product, leaving no ambiguity about when to select this tool.

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