AllTrails

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

Annotations declare readOnlyHint=true, so safety is established. The description adds critical behavioral constraints not in annotations: that numeric filters MUST be in meters, and that responses contain both metric/imperial units which MUST be converted to locale-appropriate units for display. It also notes the intersection vs union filter behaviors for different filter types.

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?

Well-structured with clear sections: purpose, usage triggers, fallback logic, filter capabilities, and response formatting. Every sentence provides distinct value. Slightly verbose in the response formatting section, but the structure allows the agent to quickly identify relevant sections.

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 complex search tool with rich filtering (10+ filter types), the description comprehensively covers: when to use vs siblings, mandatory unit constraints, filter categories (activities, suitability, attractions), and response handling requirements. With an output schema present, it appropriately focuses on input constraints and selection logic rather than return values.

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?

While the schema has extensive nested descriptions (making baseline understanding high), the description adds crucial context about unit requirements ('MUST be specified in meters') and lists activity examples in the opening sentence. It compensates for the single 'input' parameter wrapper by explaining the conceptual model (coordinates + filters) at the top level.

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 opens with a specific verb ('Find') and clearly identifies the resource (hiking, running, biking trails) and method (near coordinates with optional radius). It distinguishes from siblings by emphasizing the coordinate-based approach vs. the bounding box approach of find_trails_within_bounds.

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?

Provides explicit 'Use this tool when' bullet points covering specific coordinates, points of interest, and time constraints. Critically, it explicitly names the alternative ('search within bounding box' tool referring to find_trails_within_bounds) and states this is a fallback when bounding boxes are unknown, creating clear decision boundaries.

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 indicate readOnlyHint=true (safe operation). The description adds critical behavioral constraints not in annotations: that filter values MUST be specified in meters, and that the response returns values in both meters and imperial units which MUST be displayed according to user locale. Deducting one point for not mentioning potential rate limits or result pagination behavior.

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?

Well-structured with clear visual hierarchy: single-sentence purpose statement, bulleted usage conditions, paragraph for alternative tools, and dedicated sections for filter constraints and output handling. No redundant sentences; every paragraph addresses distinct concerns (selection, invocation, constraints, presentation).

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 complex tool with 10+ filter options and nested objects, the description provides complete guidance. It acknowledges the existence of an output schema (per context signals) by focusing on presentation logic rather than enumerating return fields, and correctly references sibling tools for alternative workflows.

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?

While the schema has comprehensive internal descriptions (despite the 0% top-level coverage signal), the description adds crucial semantic information about unit requirements (meters for input) and locale-appropriate display conversion for outputs. It could explicitly confirm the latitude/longitude structure of the bounds parameters, but the schema handles this adequately.

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 opens with a specific verb ('Find') and resource ('trails'), clearly defining the scope as 'within a specified bounding box defined by southwest and northeast coordinates.' It distinguishes from the sibling tool 'find_trails_near_location' by emphasizing the bounding box requirement versus proximity search.

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?

Contains explicit 'Use this tool when' bullet points covering geographic boundaries, named places with known bounding boxes, and protected areas. Critically, it states the negative condition: 'If the bounding box for the named place is not known, use the 'find trails near a location' tool instead,' providing clear selection 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?

Annotations establish the read-only, non-destructive safety profile. The description adds valuable behavioral context beyond this: it mandates specific unit conversion requirements for display ('MUST be displayed... in the units most appropriate for the user's locale'), explains the review summarization logic, and details the categories of data returned (accessibility, activities, user-generated content stats).

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 well-structured and front-loaded with the core purpose. Every sentence earns its place: content scoping, unit handling mandates, and review guidance are all necessary precision. It avoids tautology while remaining appropriately detailed for a data-retrieval tool with complex output formatting requirements.

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 output schema exists, the description appropriately avoids documenting all return fields, focusing instead on critical output handling logic (units, review summaries). However, the complete absence of input parameter documentation creates a significant gap, preventing this from scoring higher despite strong coverage of behavioral traits.

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?

With 0% schema description coverage, the description bears full responsibility for documenting the 'trail_id' parameter. It completely fails to mention the required parameter, its format (integer), or where to obtain it (e.g., from sibling search tools). The nested 'input' object structure in the schema is also 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 opens with a specific verb ('Find') and resource ('detailed information about a trail'), including the external data source ('AllTrails'). It clearly targets a single trail entity, distinguishing it from the sibling search/discovery tools (find_trails_near_location, search_trails_by_name) which return collections.

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 provides explicit guidance on limitations and alternatives: it states when NOT to rely on the tool for specific review content and directs users to the AllTrails web URL instead. However, it lacks explicit workflow guidance stating that this tool requires a trail_id obtained from sibling search tools first.

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 readOnly/destructive status. The description adds valuable behavioral context: geographic specificity (trailhead only), temporal scope (7-day), and data limitations (high/low only). However, it omits details about data sources, caching, or rate limiting that would further aid agent decision-making.

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 tightly written paragraphs with zero redundancy. The first sentence front-loads the core functionality; the second immediately addresses scope limitations and alternatives. Every word serves a distinct purpose.

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's simplicity (single input object) and presence of an output schema, the description adequately covers the return value semantics (7-day, high/low) and sibling relationships. Minor gap in not mentioning the output format structure, though this is presumably handled by the 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?

Context signals indicate 0% schema description coverage for the input parameter, and the description fails to compensate—it mentions 'for a trail' but never explains trail_id or the units parameter. While the schema internally documents these, the description provides no semantic guidance on parameter usage or valid values.

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 specific action (Get 7-day forecast), resource (trail weather), location context (trailhead), and data scope (high/low temperatures). It effectively differentiates from sibling tools by focusing specifically on forecast overview versus detailed trail information.

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 defines when NOT to use the tool (for current conditions, sunrise/sunset, alerts) and provides a specific alternative pathway (direct user to AllTrails URL from get_trail_details response). This clear exclusion criteria and alternative routing prevents misuse.

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 confirm read-only, non-destructive behavior. The description adds valuable behavioral context not in annotations: the search ranking can be biased by coordinates from request metadata, and it mandates specific unit localization rules for the response (imperial vs metric). It does not disclose rate limits or auth requirements, preventing a perfect score.

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?

Well-structured with logical flow from purpose to usage conditions to behavioral notes. The unit localization paragraph, while technically response formatting, earns its place as a behavioral mandate. Minor deduction for slight verbosity in the coordinate bias explanation which could be more compact.

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 presence of an output schema, the description appropriately focuses on triggering logic and presentation requirements rather than return value structures. It adequately covers the tool's role in the broader workflow (search then detail fetch). However, the lack of parameter documentation given the 0% schema coverage leaves a significant gap for a tool with nested arguments.

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?

With 0% schema description coverage and a nested input structure, the description fails to adequately compensate. While it implicitly references the 'search query' and 'coordinates' in the usage section, it never explains the 'limit' parameter or clarifies that these fields reside inside an 'input' wrapper object. The agent must infer parameter semantics from examples and context.

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 opens with a specific verb ('Search') and clearly defines the resource ('hiking, running, biking, backpacking or other trails') and matching method ('full or partial name match'). It effectively distinguishes from sibling tools by explicitly referencing `get_trail_details` as the subsequent step for presenting complete details, implying this tool is for discovery rather than full 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?

Provides explicit 'Use this tool when the user:' criteria with concrete examples ('Avalanche Lake Trail', 'Half Dome'). It also prescribes a specific workflow—automatically calling `get_trail_details` if there's a clear match—and clarifies the coordinate biasing behavior, giving the agent clear decision boundaries.

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