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

With no annotations provided, the description carries the behavioral burden. It discloses coordinate units, the SW/NE convention, the required ordering constraints (min_lat <= max_lat, min_lon <= max_lon), and the default behavior of 'categories'. Return shape is not described, but an output schema exists.

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 compact and well-structured: purpose first, then units, coordinate conventions, constraints, default behavior, and a concrete example. Every sentence contributes useful information with no 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 tool with no annotations and an output schema present, the description is nearly complete. It covers units, parameter semantics, defaults, and a calling example. The only notable gap is not explicitly distinguishing this from the related 'pois' sibling.

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 80%, so baseline is 3. The description adds genuinely useful semantics beyond the schema: all coordinates are decimal degrees, min is south-west, max is north-east, the inequality constraints are required, and categories has a sensible default. The example further clarifies parameter usage.

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 clear specific action ('Counts of key amenities inside a bounding box') and identifies itself as a 'light density helper'. This clearly separates it from geocoding and routing siblings, though it does not explicitly contrast with the sibling 'pois' tool.

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 context is reasonably clear: this is for quick amenity counts within a bounding box, and the example reinforces usage. However, there is no explicit guidance on when to choose this over alternatives such as 'pois', and no when-not-to-use conditions are 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?

With no annotations provided, the description carries the behavioral burden. It discloses the coordinate units, the output format via example, and the input/output mapping. It does not mention error handling for ambiguous or non-existent place names, but for a simple stateless lookup the core behavior is transparent.

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 appropriately brief: purpose, units, and a concrete example. Every sentence adds value, and the most important scoping information is 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?

For a tool with one simple parameter and an output schema, the description is complete enough. It explains the input, output coordinate system, and provides an example, which is everything an agent needs to invoke it 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?

The schema provides only a plain string 'query' with no description, and schema description coverage is 0%. The description compensates by specifying that the query is a place name and gives a concrete example showing expected usage, adding meaning that the schema alone lacks.

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 and resource: 'Forward geocode a place name to a WGS84 coordinate'. It clearly distinguishes itself from the sibling reverse_geocode by specifying 'forward' and stating the direction from place name to coordinate.

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 makes clear this is for converting a place name to coordinates, which tells the agent when to use it versus reverse_geocode. It does not explicitly list exclusions or alternative conditions, but the context is strong enough for correct selection.

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. It does this well by specifying the polygon ring as [lon, lat] pairs, area_m2 units, decimal-degree coordinates, and the 1–120 minute budget range. It does not discuss side effects, but this is a spatial query tool and the core behavior is clearly 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 compact and well structured: a one-sentence purpose, a unit/format legend, and a fully worked example. Every sentence earns its place and the most important information appears first.

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 an output schema present and a fully documented input schema, the description provides the essential operational facts: coordinate order, units, time-budget bounds, and an example call. It is sufficient for invoking the tool correctly, though it leaves usage-vs-alternative routing to inference.

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 documents all four parameters with 100% coverage, so the baseline is 3. The description adds a meaningful example and confirms units, but it largely restates schema-level details (decimal degrees, minutes 1–120) without adding deeper parameter-specific trade-offs or nuances.

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 opening phrase 'Reachable-area polygon within a travel-time budget' is a specific, concrete summary that clearly states the tool's output and resource type. It is conceptually distinct from the geo sister tools, though it does not explicitly name siblings or describe exclusions.

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: use this tool when you need a reachable-area polygon for a given travel-time budget. The example reinforces the intended call shape, but there is no explicit guidance about when to prefer this over geocode, pois, bbox_summary, or reverse_geocode.

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 burden. It discloses the exact output format and the health-check nature of the operation. It does not explicitly state 'no side effects,' but the minimal ping semantics make that reasonably clear.

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 and well-structured: a one-line label, a return contract, and an example. There is no filler, and the most important information appears first.

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 zero-argument reachability check with an output schema, this description is fully sufficient. It states what the tool does, what it returns, and how to call it.

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 has zero parameters and the schema already confirms an empty parameter object, so the schema description coverage is effectively 100%. Per the baseline for zero-parameter tools, a 4 is appropriate; no additional parameter 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 explicitly identifies it as a health-check tool and gives the exact return payload, so an agent immediately knows its purpose. It is clearly distinguishable from the geospatial sibling tools by being a reachability probe rather than a geocoding/isochrone/POI operation.

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 states that it is for 'any MCP client to confirm reachability,' which gives a clear usage context. It does not enumerate exclusions, but none are really needed because the tool takes no arguments and the sibling tools serve obviously different purposes.

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?

There are no annotations, so the description carries the burden of behavioral disclosure. It provides useful behavioral details: results are grouped by category, units are decimal degrees and metres, radius is capped at 5000, categories are enum-constrained, and schema documentation states that category values map to fixed OSM tags server-side rather than raw tag expressions. It does not explicitly state read-only behavior or auth needs, but the query nature and constraint details cover the most important operational traits.

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 compact and front-loaded, with the core function stated first, then units and constraints, then a concrete example. Every sentence contributes necessary information, and there is no padding or repetition of schema details.

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 four-parameter schema and the presence of an output schema, the description is complete enough for correct invocation. It covers the coordinate inputs, radius limit, category constraint, units, and provides an example. There is no missing information required for an agent to construct a valid call.

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 baseline is 3. The description adds semantic value beyond the schema by defining the relationship between parameters: lat/lon define the center point, radius_m defines the search distance, and categories constrain what is returned. The concrete example (lat=3.15, lon=101.71, radius_m=500, categories=["cafe","transit"]) makes parameter usage unambiguous.

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 function: returning points of interest within a radius of a coordinate, grouped by category. It is specific about the resource (POIs near a point) and includes an example call that removes any ambiguity. The resource and behavior distinguish it from sibling tools like geocode, reverse_geocode, isochrone, and bbox_summary.

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 the tool: when you need POIs near a lat/lon point within a limited radius, with category filtering. It also states constraints (radius max 5000, categories are enum-constrained, no free-text queries). However, it does not explicitly compare against sibling tools or state when not to use this tool, so an agent must infer the alternatives from the sibling 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?

With no annotations, the description must carry the burden. It discloses units, the return type (display-name string), and demonstrates output with an example. However, it does not mention potential failure modes, coverage limitations, or any caveats about accuracy, which are relevant for a reverse geocoding operation.

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 compact and well-structured: a clear one-sentence purpose, a units note, and an illustrative example. Every sentence earns its place, with the example positioned at the end for clarity.

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?

The tool is simple with two fully documented parameters and an output schema available. The description adds units and an example, which is sufficient for an agent to call it correctly. It could be more complete by noting when to prefer it over forward geocoding, but for the tool's complexity it is nearly 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%, so the baseline is 3. The description adds value by reiterating units and providing a worked example that shows exact parameter values and the resulting output pattern. This goes beyond the schema's range descriptions and helps an agent verify correct invocation.

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 and resource: 'Reverse geocode a coordinate to a human-readable address.' This clearly distinguishes it from siblings like geocode (forward geocoding), isochrone, and pois, and the example reinforces the behavior with actual coordinate-to-address mapping.

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 the use case (given lat/lon, get an address) and provides an example, but it does not explicitly mention alternatives or conditions for when to choose this tool over geocode or other siblings. The guidance is implied rather than stated.

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