購物比價紀錄

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

With no annotations, the description must carry behavioral disclosure, and it does describe the returned metrics (current low, per-store quotes, 90-day stats) — useful since there is no output schema. However, it says nothing about auth requirements, rate limits, caching, or whether prices are live, leaving meaningful behavioral gaps.

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 tightly-packed sentence that front-loads the core result (current lowest price) before the secondary metrics. No wasted words.

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, annotation-free read tool with no output schema, the description adequately conveys what the agent will receive (current minimum, per-store quotes, 90-day stats). Only the omission of usage routing and behavioral caveats keeps it from being fully complete.

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% and the only parameter 'id' is documented with an example (pchome:DYAJCH-1900JLHPE) in the schema itself. The description adds no further meaning about the id format or provider prefix, so the baseline 3 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 states a specific verb+resource (取得單一商品...價格) and enumerates exactly what is returned: current lowest price, per-store quotes, and 90-day min/max/average. The word '單一' (single) implicitly distinguishes it from the list/search siblings, but it does not name an alternative, so it stops short of full sibling differentiation.

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?

Usage is only implied: the required 'id' makes clear you need a known product id, but the description never says when to choose this over search_products or list_price_drops, nor how to obtain the id. There are no explicit when-to-use or exclusion statements.

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 behavioral burden and says nothing beyond the bare operation. It doesn't state that this is a read-only operation, whether results are paginated, how many categories are typical, or in what order they come.

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 short sentence with no filler, appropriately sized for a zero-parameter list tool. It is terse rather than padded.

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 no-arg list tool this is close to sufficient, but with no output schema and no annotations, the description could have said what the categories look like or whether they map to category IDs used elsewhere.

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 takes zero parameters, so the baseline is 4. There are no inputs whose semantics the description needs to clarify.

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 (列出商品分類), which is unambiguous on its own. It does not explicitly distinguish itself from siblings like search_products, but the resource is narrow enough that overlap is unlikely.

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 indication of when to use this versus search_products or the other siblings, and no prerequisites or context. Usage is only implied by the verb 'list'.

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 filter thresholds, which is useful, but says nothing about ordering (e.g., sorted by drop percentage), result limits, pagination, or whether it is a read-only listing — for a zero-annotation tool this is a notable gap.

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 with no filler, and the core filter criteria are front-loaded. Nothing is wasted, though the brevity is also what leaves the gaps elsewhere.

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 annotations, no output schema, and an undocumented parameter, the description should do more work than it does. It never explains result ordering, count, or the category filter, so an agent still lacks information needed to invoke it confidently.

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 0% and the description never mentions the single `category` parameter or its allowed enum values. The enum values are self-describing in the schema, but the description adds no meaning about how category narrows the result set, leaving the parameter semantics undocumented.

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) and resource (降價/創新低的商品) with concrete thresholds (3% drop, 30-day low), so the agent knows exactly what set is returned. It does not, however, contrast this with siblings like search_products or get_product_price, so differentiation is left to inference.

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 when-to-use guidance is given relative to the sibling tools (get_product_price, list_categories, search_products). The criteria describe what is returned rather than when an agent should pick this tool over a general product search, so usage must be guessed.

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 usefully discloses the return fields (product, store, price, confirmation time) in place of a missing output schema, but says nothing about data freshness, caching, rate limits, or whether the confirmation time is a live check.

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 sentence front-loads the action and scope, then the return payload. It is dense but every clause carries information, with 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?

With no annotations and no output schema, the description does cover purpose, scope, currency, and return fields, which is adequate for a 2-parameter search tool. However, it omits how results are ranked/limited, pagination, and any freshness caveat around the confirmation time, leaving real gaps.

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 50%: query is documented in the schema and category is an enum without per-value descriptions. The description only loosely maps its parenthetical categories (3C, beauty, appliances) onto the enum values, so it adds marginal meaning rather than compensating for the coverage gap. Baseline 3 fits.

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?

Specific verb+resource (搜尋...商品) with clear scope: Taiwan shopping sites, three product categories, NTD pricing, and the returned fields. An agent can tell it searches rather than retrieves a single price, but the description never explicitly contrasts itself with siblings like get_product_price or list_price_drops.

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 at all. The sibling get_product_price is highly overlapping (both surface a price), yet the description gives no rule for choosing between them, leaving the agent to infer from the names alone.

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