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 clearly states the tool returns administrative boundaries, implying a read-only operation, without contradicting annotations. It does not explicitly state it is non-destructive, but the context is 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, front-loads the purpose, and uses a clear structure with Args and Returns sections, earning its place without redundancy.

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 description adequately covers the three parameters and the general return value ('Administrative boundaries from largest to smallest'), though it could provide more detail on the exact structure of the returned boundaries.

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 coverage, the description fully compensates by explaining each parameter, including the output_mode choices, providing meaning beyond the schema's type constraints.

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 'Get administrative boundary hierarchy for a location' and specifies the hierarchy from country to neighbourhood, distinguishing it from sibling tools like geocode or nearby_places.

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 use for coordinates, but does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it.

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 key behaviors: sequential processing (rate limit respect) and that individual failures do not abort the batch. It also provides retry advice. No annotations exist, so the description carries the full burden. A minor point is that it does not mention any potential performance or timeout implications, but overall it 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 well-structured with sections (Args, Returns, CRITICAL guidance) and is front-loaded with the main purpose. It effectively communicates essential information, though the retry guidance could be integrated more concisely. Still, every sentence serves a 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 no annotations and no output schema, the description sufficiently covers the tool's behavior, parameters, and error handling. It also provides clear retry logic. It is complete enough for an agent to use correctly, though it could mention expected return format in more detail.

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?

Although the schema has 0% description coverage, the description adds meaning for all three parameters: 'queries' explained as a JSON array of place names (with example), 'limit' as max results per query, and 'output_mode' as 'json' or 'text'. This significantly clarifies usage, though there is a slight inconsistency: schema type for queries is 'string' but description says 'JSON array', which could cause confusion.

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: 'Geocode multiple place names in one call.' It distinguishes from siblings by emphasizing batch processing and mentions sequential execution and rate limits, making the purpose specific and unambiguous.

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 guidance on when to use this tool, including sequential processing to respect rate limits. It includes critical retry guidance: if a query fails, use the single geocode tool with simplified names, directly addressing failure scenarios and alternatives.

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, so description carries full burden. Discloses return format (bbox, center, area) and EPSG:4326. Includes retry behavior. Does not cover rate limits or error handling beyond retry, but adequate for a read-only geocoding tool.

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?

First line front-loads core purpose. Retry workflow is detailed but necessary. Could be slightly more concise, but structure is logical and efficient for LLM guidance.

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?

No output schema, but description explains return value. Covers all 3 parameters and includes retry logic. For a tool with 3 params and no nested objects, it is fairly 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 coverage 0%, but description provides detailed semantics: 'query' with example, 'padding' as fractional expansion with default, 'output_mode' options. Adds meaning beyond bare schema.

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?

Clear verb 'Get' and resource 'bounding box for a place'. Specifies bbox format as [west, south, east, north] in EPSG:4326 and lists compatible tools (dem_fetch, stac_search, etc.), distinguishing it from sibling geocoding tools.

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 states it is suitable for DEM/STAC tools and provides a detailed retry workflow on no results, guiding the LLM to simplify queries. Lacks explicit when-not-to-use, but the context is 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?

With no annotations provided, the description fully bears the burden of behavioral disclosure. It clearly states that no API calls are made, explains input formats, output mode, and the return value (NxN distance matrix in metres). This is comprehensive for a computation-only tool.

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, using a docstring format with Args/Returns sections. It could be slightly more front-loaded (the first sentence is clear), but overall every sentence adds value with no redundancy.

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 only 2 parameters, no output schema, and no annotations, the description is fully complete: it explains both input formats, the output mode, and the return type (distance matrix in metres). No gaps remain.

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 0%, so the description must compensate. It does so thoroughly: details both point formats (array or object), auto-naming behavior, and output_mode options (json/text default). This adds significant meaning beyond the raw schema.

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 it computes a haversine distance matrix between multiple points. It specifies that it is pure computation without API calls, and provides input format examples. The purpose is distinct from sibling tools (geocoding, routing).

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 says 'Pure computation — no API calls needed,' which helps an agent choose this offline tool over potentially slower or costlier alternatives. It implies appropriate usage but does not list exclusions or when-not-to-use.

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 full burden. It discloses use of Nominatim, retry behavior, and notes that simple names work best. Does not explicitly mention read-only nature or authentication, but provides adequate behavioral context.

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 sections for description, args, returns, and a detailed 'CRITICAL' section. The retry workflow is verbose but valuable. Could be more concise, but front-loads 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 5 parameters, no output schema, and no annotations, the description is comprehensive. Covers all parameters, return format, and provides a critical retry strategy for edge cases.

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%, but the description explains all 5 parameters: query (with example), limit (range/default), countrycodes (ISO codes), language (example), output_mode (options). Adds significant meaning beyond schema.

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 'Forward geocode a place name to coordinates' and specifies the database (OpenStreetMap/Nominatim). It distinguishes from siblings like reverse_geocode by focusing on forward geocoding.

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?

Includes a detailed retry workflow for when no results are found, guiding the LLM on how to handle failures. Does not explicitly state when not to use or compare with alternatives, but provides clear context.

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, and the description only mentions the return value. It lacks disclosure of behavioral traits such as idempotency, side effects, rate limits, or authentication requirements, which is insufficient for a tool with no 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 concise with two short lines plus structured Args/Returns. It is front-loaded with the core purpose, though could be slightly more informative without sacrificing brevity.

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 output schema and minimal parameter details, the description is incomplete. It mentions 'LLM-friendly usage guidance' without explaining what that entails, leaving the agent without enough context for effective use.

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 adds meaning for the output_mode parameter by listing default and options, but does not clarify what each output mode returns. With 0% schema coverage, more detail would be expected.

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 returns 'full server capabilities' including tool lists, API details, and usage guidance. It is distinct from sibling tools which focus on geocoding, status, or other operations.

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 tool is for discovering capabilities, but it does not explicitly state when to use it versus alternatives like geocoder_status or other sibling tools.

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, and the description does not disclose behavioral traits such as side effects, rate limits, or authentication requirements. It only describes the return value, leaving the agent without information on potential impacts.

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 with clear sections for description, args, and returns. Every sentence adds value without redundancy.

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 (one optional parameter) and the description's coverage of purpose, return values, and parameter options, it is complete enough for an agent to use correctly. No output schema exists, but return fields are explicitly listed.

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 has 0% description coverage, but the description adds meaning by specifying valid values for 'output_mode' ('json' default, 'text'). This compensates for the lack of schema documentation.

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 'Get geocoder server status' and lists specific return values (server version, Nominatim URL, cache stats, tool count), clearly distinguishing it from sibling tools like geocode or reverse_geocode.

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 explicit guidance is given on when to use this tool versus alternatives. The description implies it is for checking server status but does not provide exclusions or context for when it is appropriate.

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 full burden. It reveals behavior like using reverse geocoding at multiple zoom levels and returning sorted results. However, it lacks details on error handling (invalid coordinates), rate limits, or authentication needs. The read-only nature is implied but not explicit.

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 with a brief summary followed by parameter documentation in a clean format. It is concise yet informative, with no wasted words. The parameter doc is slightly verbose but still efficient.

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 absence of an output schema, the description adequately explains the return value (list of places with distances sorted by proximity). It covers the tool's purpose, parameters, and output. However, it does not mention pagination, result limits beyond 'limit' parameter, or edge cases like no results found.

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%, so the description compensates. Each parameter (lat, lon, limit, categories, output_mode) is explained with context (e.g., comma-separated OSM categories, default values). It adds meaning beyond the schema, though output_mode could benefit from listing allowed 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 'Find places near a coordinate' and explains the scaling concept (buildings, streets, etc.), which distinguishes it from siblings like 'geocode' (text to coordinates) and 'reverse_geocode' (coordinates to address). However, it does not explicitly contrast with siblings, so a perfect score is not warranted.

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 describes what the tool does and implies usage for discovering nearby places, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., when to use 'reverse_geocode' versus this). No when-not or exclusion criteria are mentioned.

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 full burden. It implies a read-only lookup but does not explicitly state that the tool is non-destructive or detail any side effects, permissions, or rate limits. The behavioral traits are partially covered (e.g., zoom level impact), but more transparency would be beneficial.

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 efficiently structured with a brief intro, an Args section, and a Returns section. Every sentence adds value: it defines the operation, lists parameters with context, and summarizes output. There is no redundancy, and it is appropriately sized for a 5-parameter tool.

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 lack of an output schema, the description should detail the return structure. It mentions 'display name, structured address, and bounding box' but does not specify the format (e.g., JSON keys or text). For a tool with 5 parameters and no output schema, more detail on the return would improve 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?

Schema description coverage is 0%, so the description compensates by explaining each parameter: lat/lon ranges, zoom levels with examples, language format, and output_mode options. This adds meaningful context beyond the schema's type/default information. However, it lacks detailed examples for the language 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: 'Reverse geocode coordinates to a place name and address.' It specifies the input (coordinates) and output (display name, structured address, bounding box), making it unambiguous. The verb 'reverse geocode' is specific to the 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 does not provide explicit guidance on when to use this tool versus alternatives like 'geocode' or 'nearby_places.' While the purpose implies it's for coordinate-to-place conversion, no when-to-use or when-not-to-use context is given, which would help the agent choose among siblings.

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 fully bears the burden of disclosure. It states the algorithm (haversine distances), return structure (resolved waypoints, leg distances, total distance, bounding box), and retry 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 well-structured with clear sections (Args, Returns, CRITICAL). It is concise—no unnecessary words—and front-loads the core purpose. 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?

Despite no output schema, the description fully documents return values (resolved waypoints, leg distances, total distance, bounding box). It also provides critical retry guidance, making it complete for a tool with only 2 parameters and no nested objects.

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%, but the description fully explains both parameters: 'waypoints' is a JSON array of place names with an example, and 'output_mode' defaults to 'json' with 'text' as alternative. This adds essential meaning beyond the bare schema.

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 it geocodes waypoints and computes route distances, with a specific verb ('Geocode') and resource ('waypoints in order'). It distinguishes itself from sibling tools like 'geocode' (single place) and 'distance_matrix' (likely driving distances) by focusing on sequential waypoint resolution and haversine distances.

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 includes explicit CRITICAL retry guidance for when waypoints fail, instructing to simplify names and test with geocode. However, it does not explicitly compare with sibling tools like 'distance_matrix' for when to use straight-line vs driving distances.

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