surf-trip-planner

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false. The description adds context by listing the comparison dimensions (ability level, season, travel access, hazards, consistency, spot candidates), which informs the agent about what aspects the tool evaluates without repeating annotation data.

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, front-loaded with the usage context, and every word is meaningful. No redundancy or fluff. It efficiently packs purpose, usage, and behavioral traits into minimal 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?

Given the tool has 3 parameters, no output schema, and clear annotations, the description covers the key aspects: what it does, when to use, and comparison criteria. It lacks only a hint about the output format (e.g., a comparison summary), but that is minor given the absence of an output schema.

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?

All three parameters have schema descriptions (100% coverage), establishing a baseline of 3. The description adds value by linking parameters to comparison aspects: 'ability level' to surferLevel, 'season' to travelMonth, and 'destinations' explicitly. It also confirms the intended use of the destinations array.

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 compares specific surf destinations (countries, regions, spots) across multiple dimensions. It distinguishes from sibling tools like recommend_surf_trip_destinations by focusing on comparison of user-defined sets.

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 explicitly opens with 'Use this when a user is deciding between specific countries, regions, or surf spots', providing a clear, direct usage guideline. It implicitly tells the agent this is for comparison, not for general recommendations or forecasts.

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 indicate read-only and non-destructive behavior. The description adds that the tool matches user queries and intents against guide titles and keywords, providing transparency beyond annotations without contradiction.

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, well-structured sentence that lists concrete examples. Every part is useful, with 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 simple search tool with few parameters and no output schema, the description is complete enough. It covers usage context and behavioral intent, though a brief comparison to sibling tools would enhance completeness.

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?

Both parameters are fully described in the schema with 100% coverage. The description reiterates the examples from the intent enum but does not add new semantic meaning beyond what the schema 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 clearly states the tool is for surf trip planning guidance and lists specific use cases like landlocked surfer planning and cheap flights. However, it does not explicitly distinguish this tool from siblings like recommend_surf_trip_destinations, which may lead to confusion.

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 explicit contexts for use (e.g., landlocked surfer, where to surf next) and includes a list of intents. It lacks guidance on when not to use the tool or how it differs from similar sibling tools, but the intent enum helps specify usage.

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 indicate readOnlyHint=true and destructiveHint=false. The description adds that it fetches a live 10-day forecast and best days, which is consistent and provides behavioral context without contradiction.

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 use case, and no redundant words. Every sentence adds value.

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 tool with one parameter and no output schema, the description adequately covers what the tool does (fetches forecast) and when to use it. It does not detail output format but is sufficient for selection.

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 a clear description of the 'spot' parameter. The description adds no further semantic detail beyond 'one spot', so baseline score 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?

The description clearly states 'Fetches the live 10-day Strike Mission forecast and best days for one spot' with a specific verb and resource, and distinguishes from siblings by emphasizing 'one spot' and live forecast versus planning/comparing.

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 says 'Use this when the user asks whether a specific surf spot is worth surfing or traveling to soon.' It provides clear context but does not explicitly list when not to use or name alternatives, though siblings imply other cases.

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 declare readOnlyHint=true, so the description doesn't need to restate that. It adds value by listing the return fields, giving the agent a clear picture of what information to expect.

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 efficient sentence with no wasted words. Front-loaded with usage context, then lists return 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 single-parameter, read-only tool without an output schema, the description adequately covers what the tool does and what it returns. Could be slightly more detailed about output format, but sufficient.

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 baseline is 3. The description does not add extra meaning beyond what the schema provides for the 'spot' parameter.

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 purpose: returns planning context for a specific surf spot. It lists specific information categories (difficulty, hazards, etc.), distinguishing it from sibling tools like get_live_spot_forecast or compare_surf_destinations.

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 says 'Use this when the user asks about a specific surf spot.' While it doesn't state exclusions or alternatives, the context and sibling tool names imply when not to use (e.g., for live forecasts).

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?

The description discloses that the tool is read-only (consistent with annotations), returns specific destination details, and for near-term trips uses live Strike Scores for ranking. This adds behavioral context beyond annotations without contradiction.

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 three concise sentences, front-loading purpose, then output, then a special case (near-term ranking). No redundant information; every sentence 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?

With 10 parameters and no output schema, the description explains the output format (destination candidates with specific attributes) and ranking logic. It covers main use cases adequately, though could explicitly mention that results are a list of destinations. Annotations provide safety context.

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 baseline is 3. The description adds value by providing usage hints for parameters like surferLevel ('Use intermediate when the user can catch green waves') and avoidHeavyWaves ('Set true for beginners, intermediates, family trips'), enhancing understanding beyond schema descriptions.

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 purpose: recommend surf trip destinations based on user queries about where to surf, fly for surf, or plan trips. It distinguishes from siblings by specifying the output (Strike Mission destination candidates with ability fit, season, travel, hazards, and dashboard links) and the near-term ranking feature.

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 explicit usage scenarios (e.g., 'when a user asks where to surf'), but does not explicitly state when not to use it or contrast with sibling tools. However, the context is clear enough for appropriate selection.

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