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

With no annotations, the description carries the full behavioral burden. It discloses that the operation is an analysis producing multi-mode comparisons and is sensitive to departure time, which implies a read-only, side-effect-free operation. It says nothing about permissions, rate limits, mode-availability fallbacks, or error behavior, so the disclosure is useful but not complete.

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?

Purpose is front-loaded and the Args/Returns structure is easy to scan. There is mild padding ('advanced tool,' 'Essential for...'), and the Returns block duplicates what the output schema already provides, but nothing is confusing or badly ordered.

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 6-parameter tool with a rich output schema, the definition covers purpose, parameter formats, and output shape adequately, so an agent can invoke it correctly. The remaining gap is routing guidance among the many nearby siblings, which the description does not address.

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 must compensate, and it does: it documents all six parameters with units ('decimal degrees'), the accepted mode values ('car', 'foot', 'bike'), and the time format ('HH:MM'). This adds semantics the bare schema (titles only, no enum constraint, no format) entirely 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 gives a specific verb and resource: 'Perform a detailed commute analysis between home and work locations,' and clarifies it compares multiple transportation modes with metrics. This distinguishes it conceptually from a plain point-to-point router. However, it never names or contrasts with siblings like get_route_directions or suggest_meeting_point, so the agent must infer the boundary itself.

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 offers use contexts ('real estate decisions, lifestyle planning, and workplace relocation analysis'), which implies when the tool is valuable. But it gives no when-not-to-use guidance and does not point to an alternative for simpler single-mode routing, leaving the choice among siblings to inference.

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 full behavioral burden. It never states whether the operation is read-only, whether it hits a paid/rate-limited API, latency expectations, or auth requirements; it only describes the output contents, leaving the operational profile undisclosed.

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?

Front-loaded purpose is good, but the 'Invaluable for real estate decisions...' sentence is marketing padding and the entire Returns block is redundant given an output schema exists. Coverage is present but several sentences do not earn their 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?

Parameters are fully documented and the output schema covers return shape, so the core is adequate. It still omits sibling routing and any behavioral/safety context, leaving meaningful gaps for an analysis tool with a dozen siblings and no annotations.

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 must compensate, and it does: it documents all three parameters with units ('latitude: Center point latitude (decimal degrees)', 'radius: Analysis radius in meters') and the 1000m default. This fully covers the 3 params, though it adds no constraints or ranges.

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?

States a clear verb+resource ('Generate a comprehensive neighborhood analysis') and specifies the domains covered (amenities, transportation, green spaces, services). It is understandable apart from generic siblings like explore_area, but it never explicitly names which sibling it supersedes or how it differs from find_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?

Use cases are implied via 'Invaluable for real estate decisions, relocation planning, and neighborhood comparisons,' which hints at context. However, there is no explicit when-to-use vs when-to-use-an-alternative guidance and no exclusions against the many nearby-place 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?

No annotations are provided, so the description carries the full behavioral burden. It never states that the operation is read-only, whether it incurs cost or rate limits, how large a radius is safe, or how long the analysis takes; instead it relies on marketing language ('This powerful analysis tool') rather than disclosing 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?

Front-loaded with the purpose, then a clean Args/Returns structure, but the middle paragraph is padded with promotional filler ('powerful analysis tool', 'Excellent for...') that repeats the opening instead of earning 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?

An output schema exists, yet the description restates the return contents at length (categories, counts, per-feature metadata), which is redundant. It is adequate for invocation but omits sibling differentiation and any behavioral context an agent would want before calling.

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 must compensate, and it largely does: it documents latitude/longitude as decimal-degree center points and radius as a meters value defaulting to 500. Only minor gaps remain, such as valid ranges or a radius cap.

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?

States a clear verb+resource: generates a comprehensive profile of an area, covering amenities and features organized by category. It is specific about the output shape but never distinguishes itself from close siblings like find_nearby_places, analyze_neighborhood, or search_category.

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?

Offers implied usage contexts ('neighborhood research, area comparisons, and location-based decision making') but gives no explicit when-to-use conditions, no prerequisites, and no routing to or away from any of the eleven 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, so the description carries the full burden. It discloses the nature of the search and enumerates returned fields (operator, connectors, speeds, points, access restrictions), but says nothing about read-only safety, pagination/limits, or error behavior beyond what the output schema already conveys.

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?

Front-loaded with the purpose and structured into Args/Returns, so it is easy to scan. The sentence 'Essential for EV owners planning trips...' is mild marketing filler that doesn't add actionable information.

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 annotations, an output schema present, and five parameters at 0% schema coverage, the description compensates well by documenting every parameter and the purpose. It is slightly incomplete on read-only expectations and routing versus generic nearby-search siblings.

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 must carry param meaning, and it documents all five: lat/long as center point in decimal degrees, radius default of 5000m, connector_types with concrete examples, and min_power in kW. Connector examples are illustrative ('etc.') rather than exhaustive, leaving some ambiguity.

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?

States a specific verb (Locate) and resource (EV charging stations) with scope ('near a specific location'), and marks itself as a 'specialized search tool' that distinguishes it from the generic find_nearby_places/search_category siblings without opening their schemas.

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?

Gives clear usage context ('planning trips or evaluating potential charging stops') and the filtering intent, but names no alternatives and provides no exclusions or conditions for choosing this over find_nearby_places or search_category.

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, and it partially meets it: it discloses the default radius and that results are grouped by category, and the 'discover/search' framing implies a read-only operation. However, it says nothing about permissions, rate limits, error behavior, or pagination, so key behavioral traits remain undisclosed.

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?

Purpose is front-loaded and the Args section is justified given 0% schema coverage. The Returns block duplicates the existing output schema and the multi-sentence framing paragraph is somewhat padded, but nothing is seriously wasteful.

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 5-parameter read tool, the definition covers purpose, every parameter, and the result shape, which is enough to invoke it correctly. It is slightly incomplete on routing between this and the specialized sibling find_* tools, which an agent would still have to infer.

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 and it does: it defines all five parameters, gives the radius default (1000m/1km), explains that categories accepts OSM-style values with concrete examples (['amenity','shop','tourism']) and that omitting it searches common categories, and clarifies limit is a *total* result cap. This adds meaning far 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 opens with a specific verb+resource ('Discover points of interest and amenities near a specific location') and elaborates that results are grouped by category and subcategory. It clearly conveys the operation, but it never contrasts itself with generic siblings like explore_area or search_category, so an agent gets no explicit differentiation.

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 names use contexts ('location-based recommendations, neighborhood analysis, and proximity-based decision making'), which implies when the tool is appropriate, but offers no when-not guidance or alternatives. Notably, it gives no hint about when to prefer this general search over narrow siblings such as find_schools_nearby, find_ev_charging_stations, or find_parking_facilities.

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 behavioral burden. It discloses that results can be filtered by parking type and include capacity information where available, but it does not explicitly state that the operation is read-only, nor does it mention permissions, rate limits, or 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?

The description is front-loaded with a clear first sentence and structured with Args/Returns sections. It is slightly verbose: the second sentence largely restates the first, and the 'Useful for...' sentence is filler rather than actionable 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?

Given four parameters, two required, and the presence of an output schema, the description provides adequate coverage of inputs and even describes return fields. The main gap is the absence of usage guidance relative to sibling tools, but the core information needed to invoke the tool correctly is present.

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 must fully document parameters. It does so clearly: latitude and longitude with decimal-degree units, radius with meter units and a 1000m default, and parking_type as an optional filter with concrete examples like 'surface' and 'underground'.

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: 'Locate parking facilities near a specific location.' This clearly distinguishes it from generic siblings like find_nearby_places or find_ev_charging_stations by resource, but it does not explicitly name or contrast against any sibling 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 description gives implied usage through 'Useful for trip planning, city navigation, and evaluating parking availability in urban areas,' but offers no explicit when-to-use guidance, no exclusions, and no mention of alternative tools like find_nearby_places or explore_area.

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 at all, the description carries the full behavioral burden, yet it discloses no limits: no auth/permission requirements, no maximum radius or result count, no pagination or sorting behavior, no note on whether results are cached or how distance is computed. The only behavioral detail (radius default of 2000m) is really parameter information.

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?

Purpose and scope are front-loaded in the first two sentences, and the Args block is compact. The Returns section is somewhat redundant given an output schema exists, which costs a little conciseness but not much.

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 4-parameter geo-search with an output schema, the definition covers the required inputs, units, defaults and filter semantics, so an agent can call it correctly. The main gap is routing guidance versus the many nearby siblings and any result-limit expectations.

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 must compensate and largely does: it explains latitude/longitude as the search center in decimal degrees, radius as meters with a 2000m default, and education_levels as an optional filter with concrete example values. It stops short of enumerating the valid education-level strings, which the schema does not constrain with an enum either.

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 gives a specific verb (locate/find) and resource (educational institutions: schools, colleges) and frames itself as a 'specialized search tool', which implies it is narrower than generic place search. It does not, however, explicitly name or distinguish itself from siblings like find_nearby_places or analyze_neighborhood, so an agent must infer the boundary.

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 offers a motivating context ('essential for families evaluating neighborhoods or real estate') which implies when to reach for it, but gives no explicit when-not guidance and never names an alternative such as find_nearby_places or search_category. Usage 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.

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that multiple matches may be returned ('List of matching locations') and what each result contains, but says nothing about no-match behavior, ambiguity/disambiguation, rate limits, or any auth requirements.

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 first sentence is a strong front-loaded summary, but the second paragraph largely restates it and the Returns block duplicates a field-by-field list that the output schema already provides.

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 lookup tool with an output schema covering the return shape, the description supplies adequate input semantics and result content. Missing only edge-case behavior (no results, ambiguous queries) and any operational constraints.

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 with only one parameter the description compensates well by enumerating accepted input forms with concrete examples (landmark names, street addresses, parks), which is meaning the bare 'address: string' schema does not convey.

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?

States a specific verb+resource (convert an address to geographic coordinates) and the input domain is unambiguous. The address-to-coordinates direction implicitly distinguishes it from reverse_geocode, but no sibling is named explicitly.

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?

Usage is implied by the input/output direction and the closing note that results feed 'other geospatial tools,' but there is no explicit when-to-use vs. when-not guidance and no named alternative such as reverse_geocode for the opposite direction.

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 underlying engine (OSRM) and, usefully, that response size is controllable via steps/overview/annotations, plus the return shape. However it does not state that this is a read-only operation, nor mention rate limits, coordinate validation failures, or error 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 Args/Returns/Example blocks, and the example is genuinely useful given the undocumented schema. The opening two sentences ('Calculate detailed route directions...' and 'provides comprehensive routing information...') restate the same idea, a minor redundancy that keeps it from a 5.

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 an 8-parameter tool with an output schema, the description covers purpose, every parameter, and the controlling knobs for output size. No annotations exist, so it should ideally add auth/error/read-only context, but the essential information needed to invoke the tool correctly is present.

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, and it largely does: it documents all eight parameters with meanings, defaults (steps=false, overview='simplified', annotations=false), and value options for mode ('car','bike','foot') and overview ('full','simplified','false') that the schema does not enumerate. This adds substantial 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?

States a specific verb and resource: 'Calculate detailed route directions between two geographic points,' naming the provider (OSRM) and the parameterized controls. It is immediately clear what the tool does, but it never names or distinguishes itself from siblings like analyze_commute or suggest_meeting_point, so an agent cannot differentiate on description alone.

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?

Usage is implied by the two-point input model (routing from A to B), but there is no explicit when-to-use, no when-not-to-use, and no alternative sibling named. The agent must infer that this is the point-to-point router rather than derive it from stated guidance.

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 full behavioral burden. It does convey that the operation is a non-mutating lookup and describes the shape of the returned location data, but it omits permission requirements, rate limits, and what happens for out-of-range or ocean coordinates.

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 front-loaded with the one-line purpose, then structured into Args and Returns sections. The Returns block partially duplicates the earlier 'including its address, nearby landmarks, administrative boundaries' sentence, and is redundant given an output schema exists, but the overall structure is clean.

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 two-parameter read-only tool with an output schema, the description is largely sufficient. Gaps remain: no error/edge-case behavior, no guidance on result precision or coverage limits, and no routing among the eleven sibling geo tools.

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 schema contributes only types. The description compensates by specifying the expected format ('decimal degrees') and the coordinate system ('WGS84'), which is meaningful semantics an agent could not infer. It stops short of stating valid ranges or hemisphere conventions.

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 sentence states a precise verb and resource ('Convert geographic coordinates to a detailed address'), and the direction of conversion implicitly separates it from the sibling geocode_address. However, it never names that inverse sibling, so the differentiation is left to inference.

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?

Usage is only implied via 'Useful for translating GPS coordinates into human-readable locations.' There is no explicit statement of when to prefer this over geocode_address or find_nearby_places, and no mention of prerequisites such as coordinate validity or coverage.

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 full behavioral burden. It discloses the response shape (query params, count, matching places with coordinates/metadata), which is useful, but says nothing about result caps, pagination, rate limits, or authentication for what is presumably a read-only search.

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 core purpose is front-loaded and the Args block is compact and scannable. The Returns section is somewhat redundant given an output schema already exists, which is the only minor padding.

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 6 parameters, 5 required, and an existing output schema, the description covers required inputs, optional filtering, and the general result contract, so an agent has enough to call it correctly. It stops short of clarifying how it differs from sibling search tools, which is the remaining gap.

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 must compensate and largely does: it defines category with OSM examples ('amenity', 'shop', 'tourism'), maps each boundary to a cardinal edge (min_latitude = southern, min_longitude = western), and gives subcategory examples. This adds real meaning beyond the bare 'Max Latitude' style titles, though format specifics like decimal-degree ranges are only lightly touched.

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+resource: targeted search for places of a given category inside a rectangular region. It is clear what the tool does and what it returns. However, it never distinguishes itself from close siblings like find_nearby_places or explore_area, leaving the agent to infer which search tool applies.

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 gives implied usage context ('useful for filtering places by type within a neighborhood or city district'), which hints at when to reach for it. But there is no explicit when-not guidance and no naming of alternatives, so the overlap with geocode_address, explore_area, and find_nearby_places is unresolved.

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 behavioral burden. It usefully discloses the two-phase computation (centroid calculation then venue lookup) and sketches the return payload, but says nothing about permission requirements, behavior when no venues match, location-count limits, or how venue_type matching is performed.

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 purpose is front-loaded in the first sentence, followed by mechanism, then usage context, then parameter and return details. Each block adds distinct information with no filler, and the Args example earns its space by showing the nested structure the 0%-coverage schema omits.

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 two-parameter tool with a rich output schema and no annotations, the description covers purpose, mechanism, usage, and parameter formats adequately. The Returns block partially duplicates the output schema, which is redundant but harmless; the real gap is the absence of any edge-case or failure behavior.

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 must compensate, and it does: it defines 'locations' as a list of lat/lon dictionaries and provides a concrete two-entry example, and it explains 'venue_type' with sample values. It stops short of stating the default ('cafe', visible only in the schema) or any constraints on list size.

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 sentence gives a specific verb ('Find') and resource ('optimal meeting place'), and the second sentence clarifies the two-step mechanism (compute a central point, then recommend venues). It implicitly separates itself from single-origin siblings like find_nearby_places or geocode_address by emphasizing multi-person convergence, though no sibling is named explicitly.

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 clear usage contexts ('planning social gatherings, business meetings, or any situation where multiple people need to converge'), which tells the agent when this tool is appropriate. It does not, however, name an alternative tool or state when not to use this one.

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