Suburb · All schools — bundle
suburbs_schools_allAll schools — bundle
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| suburb_name | Yes |
suburbs_schools_allAll schools — bundle
| Name | Required | Description | Default |
|---|---|---|---|
| suburb_name | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -{
- "properties": {
- "available": {
- "anyOf": [
- {
- "type": "boolean"
- },
- {
- "type": "null"
- }
- ],
- "description": "`false` on no-data responses. Omitted on success — branch on `data !== null` if you want a single discriminator.",
- "title": "Available"
- },
- "data": {
- "anyOf": [
- {
- "properties": {
- "catchment": {
- "anyOf": [
- {
- "items": {
- "additionalProperties": true,
- "description": "A SchoolNearbyRow plus the catchment polygon and school point.\nSame shape as SchoolNearbyRow with two extra geo fields.",
- "example": {
- "area_level": "suburb",
- "area_name": "Belmont North",
- "attendance_rate": 0.91,
- "boys": 243,
- "catchment_geometry": {
- "coordinates": [
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- ],
- "type": "Polygon"
- },
- "catchment_name": "Floraville PS",
- "gender": "coed",
- "girls": 244,
- "id": 42041,
- "naplan_rank": 0.5496460540954865,
- "school_geometry": {
- "coordinates": [
- 151.663835,
- -33.014211
- ],
- "type": "Point"
- },
- "school_level_type": "Primary",
- "school_name": "Floraville Public School",
- "school_sector_type": "Public",
- "socioeconomic_rank": 0.6239973262032086
- },
- "properties": {
- "area_level": {
- "description": "Always 'suburb'.",
- "title": "Area Level",
- "type": "string"
- },
- "area_name": {
- "description": "Suburb (SAL) name.",
- "title": "Area Name",
- "type": "string"
- },
- "attendance_rate": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Share of school days actually attended by the average enrolled student, as a fraction between 0 and 1 — 0.89 means 89%. Multiply by 100 to display. Most schools cluster in the high 0.8s to low 0.9s, so small differences matter more than the range suggests.",
- "title": "Attendance Rate"
- },
- "boys": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Number of male students enrolled — a headcount, despite the numeric type. Add to `girls` for total enrolment, which is the best available proxy for school size.",
- "title": "Boys"
- },
- "catchment_geometry": {
- "anyOf": [
- {
- "description": "RFC 7946 GeoJSON Polygon — list of linear rings, each ring a list\nof `[lon, lat]` pairs. First ring is the outer boundary; any\nadditional rings are inner holes.",
- "example": {
- "coordinates": [
- [
- [
- 151.67,
- -32.98
- ],
- [
- 151.68,
- -32.98
- ],
- [
- 151.68,
- -32.99
- ],
- [
- 151.67,
- -32.99
- ],
- [
- 151.67,
- -32.98
- ]
- ]
- ],
- "type": "Polygon"
- },
- "properties": {
- "coordinates": {
- "description": "`[ring][point][lon|lat]`. First ring is outer boundary; subsequent rings are holes (none today). Each ring is a list of `[lon, lat]` pairs; rings are explicitly closed (first pair == last pair).",
- "items": {
- "items": {
- "items": {
- "type": "number"
- },
- "type": "array"
- },
- "type": "array"
- },
- "title": "Coordinates",
- "type": "array"
- },
- "type": {
- "const": "Polygon",
- "description": "Always 'Polygon'.",
- "title": "Type",
- "type": "string"
- }
- },
- "required": [
- "type",
- "coordinates"
- ],
- "title": "GeoJsonPolygon",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "GeoJSON polygon of the catchment boundary."
- },
- "catchment_name": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Catchment name as listed by myschool.",
- "title": "Catchment Name"
- },
- "gender": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Who the school enrols — 'coed', 'girls' (girls only) or 'boys' (boys only).",
- "title": "Gender"
- },
- "girls": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Number of female students enrolled — a headcount. See `boys`.",
- "title": "Girls"
- },
- "id": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Stable numeric identifier for the school, for joining these rows across calls. Delivered as a number but it is an identifier — do not do arithmetic on it or compare its magnitude.",
- "title": "Id"
- },
- "name": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "The school's full name, as officially registered.",
- "title": "Name"
- },
- "naplan_rank": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "The school's academic standing on national NAPLAN testing, as a percentile between 0 and 1 where higher is better — 0.63 puts the school ahead of about 63% of schools, i.e. in roughly the top 40%. A fraction, not a percentage and not a raw test score. Null when the school has no published NAPLAN standing.",
- "title": "Naplan Rank"
- },
- "school_geometry": {
- "anyOf": [
- {
- "description": "RFC 7946 GeoJSON Point — `[longitude, latitude]` coordinates.",
- "example": {
- "coordinates": [
- 151.67,
- -33.01
- ],
- "type": "Point"
- },
- "properties": {
- "coordinates": {
- "description": "`[longitude, latitude]` — 2 numbers, lon first per GeoJSON.",
- "items": {
- "type": "number"
- },
- "title": "Coordinates",
- "type": "array"
- },
- "type": {
- "const": "Point",
- "description": "Always 'Point'.",
- "title": "Type",
- "type": "string"
- }
- },
- "required": [
- "type",
- "coordinates"
- ],
- "title": "GeoJsonPoint",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "GeoJSON point of the school location."
- },
- "school_level_type": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Which years the school covers — 'Primary', 'Secondary', or 'Combined' for a school spanning both.",
- "title": "School Level Type"
- },
- "school_sector_type": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Who runs the school — 'Public' (government), 'Private', or 'Non-Government' (the wider category including Catholic and independent schools). Fee-paying status is implied, not stated.",
- "title": "School Sector Type"
- },
- "socioeconomic_rank": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "How advantaged the school's community is, as a percentile between 0 and 1 where higher means more advantaged — 0.17 sits near the bottom of the national distribution. Measures the intake's socio-economic background, not teaching quality, and it is separate from `naplan_rank`: schools rank high on one and low on the other.",
- "title": "Socioeconomic Rank"
- }
- },
- "required": [
- "area_name",
- "area_level"
- ],
- "title": "CatchmentRow",
- "type": "object"
- },
- "type": "array"
- },
- {
- "type": "null"
- }
- ],
- "title": "Catchment"
- },
- "nearby": {
- "anyOf": [
- {
- "items": {
- "additionalProperties": true,
- "description": "One school within the suburb's catchment radius.",
- "example": {
- "area_level": "suburb",
- "area_name": "Belmont North",
- "attendance_rate": 0.89,
- "boys": 90,
- "gender": "coed",
- "girls": 82,
- "id": 42002,
- "name": "Belmont North Public School",
- "naplan_rank": 0.6282832390938133,
- "school_level_type": "Primary",
- "school_sector_type": "Public",
- "socioeconomic_rank": 0.17342543077837194
- },
- "properties": {
- "area_level": {
- "description": "Always 'suburb'.",
- "title": "Area Level",
- "type": "string"
- },
- "area_name": {
- "description": "Suburb (SAL) name.",
- "title": "Area Name",
- "type": "string"
- },
- "attendance_rate": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Share of school days actually attended by the average enrolled student, as a fraction between 0 and 1 — 0.89 means 89%. Multiply by 100 to display. Most schools cluster in the high 0.8s to low 0.9s, so small differences matter more than the range suggests.",
- "title": "Attendance Rate"
- },
- "boys": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Number of male students enrolled — a headcount, despite the numeric type. Add to `girls` for total enrolment, which is the best available proxy for school size.",
- "title": "Boys"
- },
- "gender": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Who the school enrols — 'coed', 'girls' (girls only) or 'boys' (boys only).",
- "title": "Gender"
- },
- "girls": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Number of female students enrolled — a headcount. See `boys`.",
- "title": "Girls"
- },
- "id": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "Stable numeric identifier for the school, for joining these rows across calls. Delivered as a number but it is an identifier — do not do arithmetic on it or compare its magnitude.",
- "title": "Id"
- },
- "name": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "The school's full name, as officially registered.",
- "title": "Name"
- },
- "naplan_rank": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "The school's academic standing on national NAPLAN testing, as a percentile between 0 and 1 where higher is better — 0.63 puts the school ahead of about 63% of schools, i.e. in roughly the top 40%. A fraction, not a percentage and not a raw test score. Null when the school has no published NAPLAN standing.",
- "title": "Naplan Rank"
- },
- "school_level_type": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Which years the school covers — 'Primary', 'Secondary', or 'Combined' for a school spanning both.",
- "title": "School Level Type"
- },
- "school_sector_type": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Who runs the school — 'Public' (government), 'Private', or 'Non-Government' (the wider category including Catholic and independent schools). Fee-paying status is implied, not stated.",
- "title": "School Sector Type"
- },
- "socioeconomic_rank": {
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "description": "How advantaged the school's community is, as a percentile between 0 and 1 where higher means more advantaged — 0.17 sits near the bottom of the national distribution. Measures the intake's socio-economic background, not teaching quality, and it is separate from `naplan_rank`: schools rank high on one and low on the other.",
- "title": "Socioeconomic Rank"
- }
- },
- "required": [
- "area_name",
- "area_level"
- ],
- "title": "SchoolNearbyRow",
- "type": "object"
- },
- "type": "array"
- },
- {
- "type": "null"
- }
- ],
- "title": "Nearby"
- }
- },
- "title": "SuburbSchoolsAll",
- "type": "object"
- },
- {
- "type": "null"
- }
- ],
- "description": "The endpoint's payload, or `null` when Microburbs has no value."
- },
- "message": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Human-readable explanation. Omitted on success.",
- "title": "Message"
- },
- "reason": {
- "anyOf": [
- {
- "type": "string"
- },
- {
- "type": "null"
- }
- ],
- "description": "Machine-readable slug naming the no-data condition (e.g. `no_avm_for_GANSW704074813`). Stable per endpoint. Omitted on success.",
- "title": "Reason"
- }
- },
- "title": "ApiResponse[SuburbSchoolsAll]",
- "type": "object",
- "x-fastmcp-top-level-schema": "ApiResponse_SuburbSchoolsAll_"
-}New value: +nullDoes the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. However, the description adds no behavioral context beyond that—no indication of what the 'bundle' contains, whether it returns aggregated stats or raw lists, or any response characteristics.
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?
Three words is concise, but the text is underspecified rather than efficiently informative. It is essentially a title fragment, not a structured description that earns its place by adding 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?
With no output schema and no description of what the 'bundle' includes, the tool is not fully callable by an agent without external knowledge. A one-parameter tool is simple, but the absence of any return-value or scope description leaves important gaps.
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 only parameter, suburb_name, is self-explanatory by name, but the schema provides no description and the tool description adds nothing about expected format, examples, or constraints. With 0% schema description coverage, the description should compensate but does not.
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 is simply 'All schools — bundle', which restates the tool name and title without a verb or any indication of what is actually returned. It does not distinguish this from similarly named siblings like suburbs_schools_nearby, properties_schools_all, or properties_schools_ranking.
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?
There is no guidance whatsoever about when to call this tool versus the many sibling school-related tools. No conditions, alternatives, or exclusions are mentioned, leaving the agent to guess based on the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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