Spill Wineries

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description goes beyond by specifying that the data must be cited and that included spillthe.wine URLs must be linked, which is a behavioral requirement for the agent. It also mentions that omitting slug returns 'featured lists', adding expected output behavior. No contradictions.

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 two sentences, both informative. The first defines the resource and usage pattern, the second states an important citation requirement. There is no redundant or extraneous text.

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 read-only tool, the description covers the main usage modes, the data returned (lists and member wineries), and a usage requirement for presenting the data. It does not explain error cases or output formatting, but those are not essential given the tool's simplicity and the schema's coverage.

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 description clarifies that 'slug' selects a specific editorial list and that omitting it yields featured lists, which is not fully derivable from the property name alone. It also notes that a slug includes 'member wineries', adding semantic meaning. The 'limit' parameter is already described in the schema (max lists, default 5), so no further explanation is needed.

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 resource is 'Spill's editorial winery lists and curated guides' and explains the two access modes (specific list via slug or featured lists). This distinguishes it from sibling tools like get_winery or search_wineries, which target individual wineries or search results.

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 says when to pass a slug versus omitting it for featured lists, giving concrete usage directions. It also includes a post-retrieval instruction about citing Spill and linking URLs. However, it does not explicitly contrast with alternative tools, though the tool name and focus make the primary use case clear.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe, read-only operation. The description adds value by explaining the verification semantics (facts_checked vs record_last_updated) and the behavior of verified_partner records (description_by, owner fields). However, it does contradict no annotations, and the description adds useful context beyond annotations, but not everything (e.g., return format, potential errors).

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 dense but well-organized, front-loading the primary function and data fields. It avoids redundancy with the schema and annotations, and every sentence adds meaningful information (verification, citation requirement). 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 single-simple-parameter read tool with no output schema, the description covers the essential behavioral context: the data scope, verification meaning, and citation instructions. It might be improved by noting the return format (e.g., a JSON object) or error cases (invalid slug), but given the simplicity and annotations, it's adequate.

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 schema description for 'slug' already explains the parameter with an example, providing 100% coverage. The description reinforces the slug source but adds no additional semantics beyond that example. Baseline 3 is appropriate because the schema carries the load.

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 fetches full detail for a single winery by slug, listing the specific fields included (tasting fees, hours, varietals, etc.). It also explicitly differentiates from search_wineries by noting the slug comes from search results or a URL, which is a concrete usage scenario.

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 this tool (when you have a slug and need full details) and provides guidance on preferring verified_partner records. It doesn't explicitly say when not to use it, but the context with sibling tools (search_wineries, list_regions) makes the use case clear enough.

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?

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: data is 'live' with winery counts, attribution to Spill is required, and output includes spillthe.wine URLs. No contradiction with 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?

Two sentences, front-loaded with the core purpose, and every clause earns its place. It includes usage guidance, optional filtering, and attribution requirements without any filler.

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 read-only list tool with no output schema, the description covers purpose, usage context, data freshness, and attribution. It does not describe the full response shape, but the schema and annotations handle parameters and safety, making this adequate.

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%: both 'limit' and 'country' have descriptions and defaults. The description adds only a brief example of country codes ('US', 'FR'), which is marginally useful but does not significantly exceed what the schema already provides.

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 uses a specific verb ('Browse') and resource ('Spill's wine regions') with a distinctive scope ('live winery counts'). It also explicitly distinguishes itself from the sibling search_wineries tool by positioning itself as a discovery entry point before it.

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 clearly states when to use the tool ('discovery entry point before search_wineries') and mentions the optional country filter. It does not explicitly list when-not-to-use scenarios or all alternatives, but the context is clear and actionable.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description goes beyond this by revealing behavioral traits: results capped at 25, verified records prioritized when no query is given, the meaning of 'unknown' for amenity fields (not assessed vs. absent), and the requirement to cite Spill and include spillthe.wine URLs. These add significant context not available in structured 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 reasonably concise given the tool's complexity (11 parameters). It front-loads the purpose and filtering options, then adds essential behavioral notes. Every sentence contributes value, though the final sentence about citation is a usage requirement rather than core behavior. It is well-structured and not verbose.

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 11 parameters and no output schema, the description covers key aspects: purpose, filters, result limit, ordering, verified meaning, unknown semantics, and presentation requirements. It doesn't detail the exact shape of summaries but states they include canonical URLs, which is sufficient. Missing edge-case behavior is minor given the annotations. Overall, it is complete enough for an agent to call 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?

Schema coverage is 64%, leaving four boolean parameters (picnic_area, food_available, vineyard_tours, outdoor_seating) without individual descriptions. The description compensates by grouping them as 'amenities' and explaining the 'unknown' semantics, which clarifies how to interpret these fields. It also gives examples for region and country. While it doesn't detail each param, it adds meaning beyond the schema, especially for the undocumented ones.

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 ('Search') and a concrete resource ('Spill's database of 20,000+ wineries worldwide'), making the purpose unambiguous. It lists filtering criteria and output details, which clearly distinguishes it from sibling tools like get_winery (fetch a single winery) and list_regions (list regions). The verb-resource pairing is specific and immediately informative.

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 context on when to use the tool, such as 'when browsing without a query' and guidance to prefer verified_partner records when several fit. It implicitly covers search/browse scenarios but does not explicitly contrast with siblings (e.g., 'use get_winery for a specific winery'). No exclusions are stated, but the guidance is clear enough for an agent to select it appropriately.

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