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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that it adds an item and lists some recordable fields, but does not mention side effects, permission requirements, return values, or whether certain parameters are ignored under conditions. Minimal behavioral transparency.

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 concise with two short sentences. The first sentence clearly states the tool's purpose; the second lists example fields, which is partly redundant with the schema but does not bloat the text. It is well-structured and front-loaded.

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 the tool has 12 parameters, no annotations, and no output schema, the description is far too minimal. It does not cover usage context, behavior, return values, or how it differs from scanning-based addition. The description only provides a basic label rather than complete operational guidance.

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%, so the input schema already documents all 12 parameters. The description mentions a few example fields (name, location, expiry) but adds no extra semantic meaning, relationships, or parameter-specific nuances beyond the schema. Baseline score applies.

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 action ('添加新物品' - add new item) and the resource, and briefly mentions the types of information that can be recorded. It distinguishes from read-only siblings like query_items and get_item, though it does not explicitly differentiate from scan_add_item.

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 provides no guidance on when to use this tool versus alternatives such as scan_add_item. It lacks any mention of prerequisites, exclusions, or typical use cases, leaving the agent without clear decision criteria.

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 must carry behavioral transparency. It only states that it queries by ID and returns complete info, but does not mention error behavior, permissions, or any side effects. The read-only nature is implied by 'get' but not explicitly disclosed.

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 extremely concise, two short sentences, with no filler. It front-loads the purpose and includes the key parameter usage.

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 simple single-parameter get tool, the description covers the basics but lacks details about return format, error handling, and use cases. Without an output schema or annotations, the agent must infer these. It is adequate but not comprehensive.

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% with one required 'id' parameter described as '物品ID'. The description adds the context that the ID is used for querying, but this aligns with the schema. No additional parameter semantics are provided beyond the schema.

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 retrieves detailed item information using the item ID. It uses a specific verb ('获取' / get) and resource ('物品详细信息' / item details), distinguishing it from sibling tools like add_item or query_items.

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 usage for a single item lookup by ID but does not explicitly contrast with sibling tools like query_items or scan_add_item. It does not state when to prefer this over alternatives, so the usage context is inferred rather than stated.

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 full burden. It discloses the login action and token acquisition, but does not mention error cases (e.g., invalid API key), token expiration, or side effects. For a simple login tool, this is minimally adequate but not rich.

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?

Two short sentences that are front-loaded with the core action and outcome. Every word earns its place; no filler or repetition.

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 one-parameter login tool with no output schema, the description covers purpose, outcome (token), and usage context. It would benefit from noting that the token must be used in subsequent requests, but the phrase 'first step' implicitly conveys this.

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 input schema already fully documents apiKey with format and generation source (100% coverage). The description only restates that an API key is used, adding no new parameter-specific information. Baseline 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?

The description clearly states the tool's action: login with an API Key to obtain an authentication Token. It uses a specific verb ('登录') and resource ('API Key'), and distinguishes itself from sibling tools (add_item, query_items, etc.) by positioning as the required first step.

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?

Explicitly states that this is the first step before using other tools ('这是使用其他工具前的第一步'), providing clear context for when to use it. Although no alternatives are mentioned, the guidance is unambiguous and sufficient for the tool's role.

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 disclosure burden. '查询' (query) implies a read-only operation, but the description does not disclose pagination behavior, response shape, or access requirements. It adds minimal context beyond the name.

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?

One compact sentence, front-loaded with the action and then filters. No redundant or filler information.

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 list query with no output schema and no annotations, the description gives the core purpose and filter categories but omits response shape, pagination/default behavior, and sorting. The schema covers parameters, so the gap is mainly around output and ordering semantics. Adequate but incomplete.

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 descriptions cover 100% of the 8 parameters, so the baseline is 3. The description adds no new parameter semantics—'keyword, location, status' paraphrases what the schema already documents, and 'etc.' does not expand on categoryId/isNearlyExpired.

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 '查询物品列表' (query items list), a specific verb+resource with filter dimensions (keyword, location, status). The plural 'list' inherently distinguishes it from the sibling get_item, which suggests single-item retrieval.

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 use case is implied by the word 'list' and the filter options, but the description does not explicitly say when to use this tool versus siblings. It does not mention alternatives like get_item for single-item details or add_item for creation.

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 must carry the full burden. It discloses that the system automatically recognizes item information, but it does not mention error handling for unknown barcodes, whether existing items are updated, required permissions, or any side effects. As a mutation tool, this is insufficient behavioral disclosure.

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 one concise sentence, front-loaded with the action and purpose. Every word earns its place, with no redundant filler. It is appropriately sized for the tool.

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 5 parameters, no annotations, and no output schema, the description is too brief. It does not explain what happens after a successful scan (return values, confirmation), what occurs if the barcode is not in the database, or edge cases like duplicate items. The tool is complex enough to require more context than provided.

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 input schema has 100% coverage with descriptions for all parameters. The description adds context that users only need to supplement information like location, but this does not add meaning beyond the schema. Baseline 3 applies since the schema handles parameter documentation well.

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 action: scan barcode to add an item. It specifies the resource (items) and the method (barcode scanning), distinguishing it from siblings like add_item which likely handles manual entry. The verb '添加' (add) is specific and unambiguous.

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 use when the user has a barcode and wants to add an item, and that the system auto-fills info, requiring the user to only supply additional fields like location. However, it does not explicitly compare against alternatives like add_item or mention when not to use this tool. Clear context but no explicit exclusions.

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