GoAI Moat Market Intel Brief

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

No annotations are provided, so the description carries the behavioral burden. It does disclose what the returned brief contains (focus, signals, action list, data sources), which adds value beyond the output schema. It doesn't mention side effects, permissions, or freshness/recency behavior, but as a retrieval operation the content disclosure is reasonable.

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 compact sentence that front-loads the action and packs the full output structure into a parenthetical list. Zero wasted words; every element earns its place.

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?

For a low-complexity tool with one optional, fully documented parameter and an output schema, the description covers the essentials. The main gap is lack of differentiation from sibling tools, which prevents a 5.

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 description coverage is 100% — the lone 'issue' parameter is fully documented with format examples and default behavior. The description adds no parameter-level detail, but with full schema coverage, the baseline of 3 is appropriate.

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: '返回周报摘要' (returns weekly brief summary) and enumerates the contents (焦点 + 本周信号 + 行动清单 + 数据来源). The tool name and content list make the purpose unmistakable, though it doesn't explicitly contrast with list_topics or search_intel.

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?

No guidance on when to use this tool versus its siblings. The parameter schema adds 'leave blank returns the latest issue,' which is parameter-level usage, but the description itself gives no context for choosing between get_latest_brief, list_topics, and search_intel, and no exclusions.

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

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

No annotations are provided, so the description carries the behavioral burden. It clearly discloses that this is a listing operation and what kinds of data are returned, and '列出' implies read-only behavior. However, it does not explicitly state side-effect safety, access constraints, freshness, or any limitations beyond the listed fields.

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 a single front-loaded sentence with no filler. Every phrase adds value: the resource is named, the returned content is itemized, and the intended purpose is stated compactly.

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?

Given that this is a zero-parameter listing tool and an output schema exists, the description covers enough of what an agent needs: what is listed and what fields to expect. The main missing element is usage context relative to the siblings, but that gap is minor because the empty input schema removes any invocation risk.

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 and the schema coverage is 100%, so there is nothing for the description to elaborate on. The baseline 4 applies: no parameter information is needed because no parameters exist.

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 states a specific verb (列出/list) and resource (情报库的主题索引 / intelligence topic index), and enumerates what the index contains: slug, meaning, key data, and suggested search terms. It is clearly distinct from the siblings in name and function, though it does not explicitly contrast itself with them.

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 explicit guidance on when to use this tool versus search_intel or get_latest_brief. The phrase '帮 Agent 快速定位' implies a discovery/orientation use case, but no conditions, exclusions, or alternative routing are provided.

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

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

With no annotations, the description carries the full burden and does disclose key behavior: any matching word returns results, results with more matching words rank higher, and both Chinese and English keywords are supported. It does not mention no-match outcomes or pagination, but the presence of an output schema covers return structure.

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 compact: two sentences, with the core purpose front-loaded and details on matching/ranking in the second. The parenthetical examples are useful but add some length; overall there is no fluff or redundant content.

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?

For a search tool with only two parameters and an output schema, the description covers the essential context: the database scope, result format (sourced entries), query syntax, and matching/ranking behavior. It does not discuss error conditions or edge cases, but these are not critical for typical search usage given the output schema and simple parameter set.

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 100%, so the baseline is 3. The description adds meaning beyond the schema by explaining that multiple space-separated terms work with OR logic and that ranks improve with more matches, and by giving language support examples. This enriches the query parameter's semantics beyond its schema description.

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 states a specific action (keyword/topic search) over a defined resource (verified 'overseas×AI' intelligence database) and mentions the return of sourced entries. Examples and the OR/ranking behavior further clarify its function, which clearly distinguishes it from siblings like get_latest_brief and list_topics.

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?

The description implies when to use the tool—when a keyword/topic search is needed—and gives example queries, but it does not explicitly contrast it with get_latest_brief or list_topics or state when not to use it. Usage guidance is implied through the search purpose, but no exclusions or alternative references are provided.

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