Opendata Ademe

Previous value: -"Geographic bounding box filter (only for geolocalized datasets). Format: \"lonMin,latMin,lonMax,latMax\". Example: \"-2.5,43,3,47\"."New value: +"Bounding box \"lonMin,latMin,lonMax,latMax\" (lon before lat), e.g. \"-2.5,43,3,47\". Geolocalized datasets only."

Previous value: -"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."New value: +"The exact dataset ID from the \"id\" field in list_datasets results. Do not use the title or slug."

Previous value: -"Temporal filter (only for temporal datasets with date fields). Accepts a single date \"YYYY-MM-DD\" to match that day, or a date range \"YYYY-MM-DD,YYYY-MM-DD\" to match an overlapping period. ISO datetimes also accepted. Example: \"2023-11-21\" or \"2023-01-01,2023-12-31\"."New value: +"Date \"YYYY-MM-DD\" (single day) or \"YYYY-MM-DD,YYYY-MM-DD\" (range), e.g. \"2023-11-21\". Temporal datasets only."

Previous value: -"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). All values must be strings, even for numbers/dates. If a column key has underscores (e.g., code_postal), just append the suffix: code_postal_eq. Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"New value: +"Column filters as key-value pairs: column_key + suffix, all values strings. Example: { \"ville_eq\": \"Paris\", \"age_lte\": \"30\", \"nom_search\": \"Jean\" }. Suffixes include _eq, _in, _gt/_lt, _search and more; if one is rejected the 400 error lists what the column supports. Never _c_-prefix a column filter (use ville_eq, not _c_ville_eq)."

Previous value: -"Geographic proximity filter (only for geolocalized datasets). Restricts results to within a distance from a point. Format: \"lon,lat,distance\". Example: \"2.35,48.85,10km\". Use distance \"0\" for point-in-polygon containment."New value: +"Proximity filter \"lon,lat,distance\" (lon first), e.g. \"2.35,48.85,10km\"; distance \"0\" = point-in-polygon. Geolocalized datasets only."

Removed value: -{
-  "description": "Array of aggregation results for each specified column (limited to 20 rows)",
-  "items": {
-    "additionalProperties": false,
-    "properties": {
-      "aggregations": {
-        "description": "Nested aggregation results when multiple columns are specified (max 3 levels deep)",
-        "items": {
-          "$ref": "#/properties/aggregations/items"
-        },
-        "type": "array"
-      },
-      "columnValue": {
-        "description": "The value of the aggregated column (string or number)",
-        "type": [
-          "string",
-          "number"
-        ]
-      },
-      "metricValue": {
-        "description": "The value of the aggregation metric (e.g., sum, avg) on the selected column",
-        "type": [
-          "number",
-          "null"
-        ]
-      },
-      "nonRepresented": {
-        "description": "Number of rows NOT included in the returned aggregations for this column (only top groups are returned)",
-        "type": "number"
-      },
-      "total": {
-        "description": "Total number of rows aggregated for this column",
-        "type": "number"
-      },
-      "totalAggregated": {
-        "description": "Total number of different values aggregated for this column",
-        "type": "number"
-      }
-    },
-    "required": [
-      "total",
-      "columnValue"
-    ],
-    "type": "object"
-  },
-  "type": "array"
-}

Added value: +{
+  "description": "Array of aggregation results for each group (limited to 20 rows)",
+  "type": "array"
+}

Removed value: -{
-  "description": "Number of rows NOT included in the returned aggregations (only the top 20 groups are returned). Add this to the sum of all group totals to reconstruct the dataset total.",
-  "type": "number"
-}

Removed value: -{
-  "description": "The total number of different values aggregated across all specified columns",
-  "type": "number"
-}

Added value: +{
+  "description": "Number of rows NOT included in the returned aggregations (only the top groups are returned). Add this to the sum of all group totals to reconstruct the dataset total.",
+  "type": "number"
+}

Added value: +{
+  "description": "The total number of different values aggregated across all specified columns",
+  "type": "number"
+}

Previous value: -[
-  "total",
-  "totalAggregated",
-  "nonRepresented",
-  "datasetId",
-  "requestUrl",
-  "aggregations"
-]New value: +[
+  "datasetId",
+  "total",
+  "total_values",
+  "total_other",
+  "requestUrl",
+  "aggs"
+]

Previous value: -"Geographic bounding box filter (only for geolocalized datasets). Format: \"lonMin,latMin,lonMax,latMax\". Example: \"-2.5,43,3,47\"."New value: +"Bounding box \"lonMin,latMin,lonMax,latMax\" (lon before lat), e.g. \"-2.5,43,3,47\". Geolocalized datasets only."

Previous value: -"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."New value: +"The exact dataset ID from the \"id\" field in list_datasets results. Do not use the title or slug."

Previous value: -"Temporal filter (only for temporal datasets with date fields). Accepts a single date \"YYYY-MM-DD\" to match that day, or a date range \"YYYY-MM-DD,YYYY-MM-DD\" to match an overlapping period. ISO datetimes also accepted. Example: \"2023-11-21\" or \"2023-01-01,2023-12-31\"."New value: +"Date \"YYYY-MM-DD\" (single day) or \"YYYY-MM-DD,YYYY-MM-DD\" (range), e.g. \"2023-11-21\". Temporal datasets only."

Previous value: -"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). All values must be strings, even for numbers/dates. If a column key has underscores (e.g., code_postal), just append the suffix: code_postal_eq. Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"New value: +"Column filters as key-value pairs: column_key + suffix, all values strings. Example: { \"ville_eq\": \"Paris\", \"age_lte\": \"30\", \"nom_search\": \"Jean\" }. Suffixes include _eq, _in, _gt/_lt, _search and more; if one is rejected the 400 error lists what the column supports. Never _c_-prefix a column filter (use ville_eq, not _c_ville_eq)."

Previous value: -"Geographic proximity filter (only for geolocalized datasets). Restricts results to within a distance from a point. Format: \"lon,lat,distance\". Example: \"2.35,48.85,10km\". Use distance \"0\" for point-in-polygon containment."New value: +"Proximity filter \"lon,lat,distance\" (lon first), e.g. \"2.35,48.85,10km\"; distance \"0\" = point-in-polygon. Geolocalized datasets only."

Removed value: -{
-  "description": "The metric that was calculated",
-  "type": "string"
-}

Previous value: -[
-  "datasetId",
-  "fieldKey",
-  "metric",
-  "total"
-]New value: +[
+  "datasetId",
+  "fieldKey",
+  "total"
+]

Previous value: -"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."New value: +"The exact dataset ID from the \"id\" field in list_datasets results. Do not use the title or slug."

Previous value: -"Spatial bounding box of the dataset: [lonMin, latMin, lonMax, latMax]. Present only for geolocalized datasets."New value: +"Geographic bounding box [lonMin, latMin, lonMax, latMax]"

Previous value: -"Whether this dataset has geographic data. When true, geo filters (bbox, geoDistance) are available in search_data, aggregate_data, and calculate_metric."New value: +"Whether the dataset has geographic data"

Removed value: -{
-  "description": "Link to the dataset page (must be included in responses as citation source)",
-  "type": "string"
-}

Added value: +{
+  "description": "Link to the dataset page (must be included in responses as citation source)",
+  "type": "string"
+}

Previous value: -"Whether this dataset has temporal data (date fields). When true, the dateMatch filter is available in search_data, aggregate_data, and calculate_metric."New value: +"Whether the dataset has temporal data"

Previous value: -"Temporal coverage of the dataset data. Present only for temporal datasets."New value: +"Time period covered by the dataset"

Previous value: -"End of the temporal coverage (ISO datetime)"New value: +"End date of the time period"

Previous value: -"Start of the temporal coverage (ISO datetime)"New value: +"Start date of the time period"

Previous value: -[
-  "id",
-  "title",
-  "link",
-  "count",
-  "schema",
-  "sampleLines"
-]New value: +[
+  "id",
+  "title",
+  "page",
+  "count",
+  "schema",
+  "sampleLines"
+]

Previous value: -"Number of results returned"New value: +"Number of results found"

Previous value: -"Geocoding results ordered by relevance"New value: +"Array of geocoding results with coordinates"

Previous value: -"Administrative hierarchy (department, region)"New value: +"Geographic context (department, region)"

Previous value: -"Latitude (WGS84)"New value: +"Latitude coordinate"

Previous value: -"Longitude (WGS84)"New value: +"Longitude coordinate"

Previous value: -"Street name or place name"New value: +"Name of the location"

Previous value: -"Relevance score between 0 and 1"New value: +"Relevance score (0-1)"

Previous value: -"Result type: housenumber, street, locality, municipality"New value: +"Result type (e.g., housenumber, street, municipality)"

Previous value: -"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."New value: +"The exact dataset ID from the \"id\" field in list_datasets results. Do not use the title or slug."

Previous value: -"Geographic bounding box filter (only for geolocalized datasets). Format: \"lonMin,latMin,lonMax,latMax\". Example: \"-2.5,43,3,47\"."New value: +"Bounding box \"lonMin,latMin,lonMax,latMax\" (lon before lat), e.g. \"-2.5,43,3,47\". Geolocalized datasets only."

Previous value: -"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."New value: +"The exact dataset ID from the \"id\" field in list_datasets results. Do not use the title or slug."

Previous value: -"Temporal filter (only for temporal datasets with date fields). Accepts a single date \"YYYY-MM-DD\" to match that day, or a date range \"YYYY-MM-DD,YYYY-MM-DD\" to match an overlapping period. ISO datetimes also accepted. Example: \"2023-11-21\" or \"2023-01-01,2023-12-31\"."New value: +"Date \"YYYY-MM-DD\" (single day) or \"YYYY-MM-DD,YYYY-MM-DD\" (range), e.g. \"2023-11-21\". Temporal datasets only."

Previous value: -"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). All values must be strings, even for numbers/dates. If a column key has underscores (e.g., code_postal), just append the suffix: code_postal_eq. Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"New value: +"Column filters as key-value pairs: column_key + suffix, all values strings. Example: { \"ville_eq\": \"Paris\", \"age_lte\": \"30\", \"nom_search\": \"Jean\" }. Suffixes include _eq, _in, _gt/_lt, _search and more; if one is rejected the 400 error lists what the column supports. Never _c_-prefix a column filter (use ville_eq, not _c_ville_eq)."

Previous value: -"Geographic proximity filter (only for geolocalized datasets). Restricts results to within a distance from a point. Format: \"lon,lat,distance\". Example: \"2.35,48.85,10km\". Use distance \"0\" for point-in-polygon containment."New value: +"Proximity filter \"lon,lat,distance\" (lon first), e.g. \"2.35,48.85,10km\"; distance \"0\" = point-in-polygon. Geolocalized datasets only."

Previous value: -"Sort order for results. Comma-separated list of column keys. Prefix with - for descending order. Special keys: _score (relevance), _i (index order), _updatedAt, _rand (random), _geo_distance:lon:lat (distance from point, for geolocalized datasets). Examples: \"population\" (ascending), \"-population\" (descending), \"_geo_distance:2.35:48.85\" (closest first)"New value: +"Sort order for results. Comma-separated list of column keys. Prefix with - for descending order. Special keys: _score (relevance), _i (index order), _updatedAt, _rand (random), _geo_distance:lon:lat (distance from point, for geolocalized datasets — longitude first, then latitude). Examples: \"population\" (ascending), \"-population\" (descending), \"_geo_distance:2.35:48.85\" (closest to lon=2.35, lat=48.85)"

Removed value: -{
-  "description": "Number of data rows matching the search criteria and filters",
-  "type": "number"
-}

Removed value: -{
-  "description": "An array of data rows matching the search criteria (up to the requested size).",
-  "items": {
-    "additionalProperties": {},
-    "description": "Data row object containing column keys as object keys with their values, plus _score field indicating search relevance (higher score = more relevant)",
-    "type": "object"
-  },
-  "type": "array"
-}

Added value: +{
+  "description": "An array of data rows matching the search criteria (up to the requested size).",
+  "items": {
+    "additionalProperties": {},
+    "type": "object"
+  },
+  "type": "array"
+}

Added value: +{
+  "description": "Number of data rows matching the search criteria and filters",
+  "type": "number"
+}

Previous value: -[
-  "datasetId",
-  "count",
-  "filteredViewUrl",
-  "lines"
-]New value: +[
+  "datasetId",
+  "total",
+  "filteredViewUrl",
+  "results"
+]

Added value: +{
+  "description": "Geographic bounding box filter (only for geolocalized datasets). Format: \"lonMin,latMin,lonMax,latMax\". Example: \"-2.5,43,3,47\".",
+  "type": "string"
+}

Added value: +{
+  "description": "Temporal filter (only for temporal datasets with date fields). Accepts a single date \"YYYY-MM-DD\" to match that day, or a date range \"YYYY-MM-DD,YYYY-MM-DD\" to match an overlapping period. ISO datetimes also accepted. Example: \"2023-11-21\" or \"2023-01-01,2023-12-31\".",
+  "type": "string"
+}

Added value: +{
+  "description": "Geographic proximity filter (only for geolocalized datasets). Restricts results to within a distance from a point. Format: \"lon,lat,distance\". Example: \"2.35,48.85,10km\". Use distance \"0\" for point-in-polygon containment.",
+  "type": "string"
+}

Added value: +{
+  "description": "Geographic bounding box filter (only for geolocalized datasets). Format: \"lonMin,latMin,lonMax,latMax\". Example: \"-2.5,43,3,47\".",
+  "type": "string"
+}

Added value: +{
+  "description": "Temporal filter (only for temporal datasets with date fields). Accepts a single date \"YYYY-MM-DD\" to match that day, or a date range \"YYYY-MM-DD,YYYY-MM-DD\" to match an overlapping period. ISO datetimes also accepted. Example: \"2023-11-21\" or \"2023-01-01,2023-12-31\".",
+  "type": "string"
+}

Added value: +{
+  "description": "Geographic proximity filter (only for geolocalized datasets). Restricts results to within a distance from a point. Format: \"lon,lat,distance\". Example: \"2.35,48.85,10km\". Use distance \"0\" for point-in-polygon containment.",
+  "type": "string"
+}

Added value: +{
+  "description": "Spatial bounding box of the dataset: [lonMin, latMin, lonMax, latMax]. Present only for geolocalized datasets.",
+  "items": {
+    "type": "number"
+  },
+  "type": "array"
+}

Added value: +{
+  "description": "Whether this dataset has geographic data. When true, geo filters (bbox, geoDistance) are available in search_data, aggregate_data, and calculate_metric.",
+  "type": "boolean"
+}

Added value: +{
+  "description": "Whether this dataset has temporal data (date fields). When true, the dateMatch filter is available in search_data, aggregate_data, and calculate_metric.",
+  "type": "boolean"
+}

Added value: +{
+  "additionalProperties": false,
+  "description": "Temporal coverage of the dataset data. Present only for temporal datasets.",
+  "properties": {
+    "endDate": {
+      "description": "End of the temporal coverage (ISO datetime)",
+      "type": "string"
+    },
+    "startDate": {
+      "description": "Start of the temporal coverage (ISO datetime)",
+      "type": "string"
+    }
+  },
+  "required": [
+    "startDate",
+    "endDate"
+  ],
+  "type": "object"
+}

Added value: +{
+  "description": "Geographic bounding box filter (only for geolocalized datasets). Format: \"lonMin,latMin,lonMax,latMax\". Example: \"-2.5,43,3,47\".",
+  "type": "string"
+}

Added value: +{
+  "description": "Temporal filter (only for temporal datasets with date fields). Accepts a single date \"YYYY-MM-DD\" to match that day, or a date range \"YYYY-MM-DD,YYYY-MM-DD\" to match an overlapping period. ISO datetimes also accepted. Example: \"2023-11-21\" or \"2023-01-01,2023-12-31\".",
+  "type": "string"
+}

Added value: +{
+  "description": "Geographic proximity filter (only for geolocalized datasets). Restricts results to within a distance from a point. Format: \"lon,lat,distance\". Example: \"2.35,48.85,10km\". Use distance \"0\" for point-in-polygon containment.",
+  "type": "string"
+}

Previous value: -"Sort order for results. Comma-separated list of column keys. Prefix with - for descending order. Special keys: _score (relevance), _i (index order), _updatedAt, _rand (random). Examples: \"population\" (ascending), \"-population\" (descending), \"city,-population\" (city asc then population desc)"New value: +"Sort order for results. Comma-separated list of column keys. Prefix with - for descending order. Special keys: _score (relevance), _i (index order), _updatedAt, _rand (random), _geo_distance:lon:lat (distance from point, for geolocalized datasets). Examples: \"population\" (ascending), \"-population\" (descending), \"_geo_distance:2.35:48.85\" (closest first)"

Added value: +{
+  "description": "Total number of enum values before truncation",
+  "type": "number"
+}

Added value: +{
+  "description": "Whether the enum list was truncated because it exceeded 20 values",
+  "type": "boolean"
+}

Removed value: -{
-  "additionalProperties": false,
-  "description": "The aggregation specification to perform on the specified column. Use keys from describe_dataset. If not provided, defaults to counting unique values in the aggregation column.",
-  "properties": {
-    "column": {
-      "description": "The column key to aggregate (use keys from describe_dataset)",
-      "type": "string"
-    },
-    "metric": {
-      "description": "Aggregation metric to perform on the column. Available operations are: sum, avg, min, max, count.",
-      "enum": [
-        "sum",
-        "avg",
-        "min",
-        "max",
-        "count"
-      ],
-      "type": "string"
-    }
-  },
-  "required": [
-    "column",
-    "metric"
-  ],
-  "type": "object"
-}

Removed value: -{
-  "description": "List of column keys to aggregate (use keys from describe_dataset, min 1 column, max 3 columns)",
-  "items": {
-    "type": "string"
-  },
-  "maxItems": 3,
-  "minItems": 1,
-  "type": "array"
-}

Previous value: -"The unique dataset ID obtained from search_datasets tool"New value: +"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."

Previous value: -"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"New value: +"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). All values must be strings, even for numbers/dates. If a column key has underscores (e.g., code_postal), just append the suffix: code_postal_eq. Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"

Added value: +{
+  "description": "Columns to GROUP BY (like SQL GROUP BY). These define the categories/buckets, NOT the column to compute metrics on. Use column keys from describe_dataset (min 1, max 3).",
+  "items": {
+    "type": "string"
+  },
+  "maxItems": 3,
+  "minItems": 1,
+  "type": "array"
+}

Added value: +{
+  "additionalProperties": false,
+  "description": "Optional metric to compute ON EACH GROUP. If not provided, defaults to counting rows per group.",
+  "properties": {
+    "column": {
+      "description": "The column to compute the metric ON (e.g., \"salary\" for average salary). This is NOT the grouping column. Use column keys from describe_dataset.",
+      "type": "string"
+    },
+    "type": {
+      "description": "Metric to compute on each group. \"count\" counts rows per group (identical to omitting the metric parameter — does NOT count non-null values of the specified column).",
+      "enum": [
+        "sum",
+        "avg",
+        "min",
+        "max",
+        "count"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "column",
+    "type"
+  ],
+  "type": "object"
+}

Added value: +{
+  "description": "Sort order for aggregation results. Use special keys: \"count\" or \"-count\" (by row count asc/desc), \"key\" or \"-key\" (by column value asc/desc), \"metric\" or \"-metric\" (by metric value asc/desc). Default: sorts by metric desc (if metric specified), then count desc. Example: \"-count\" to sort by most frequent values first",
+  "type": "string"
+}

Previous value: -[
-  "datasetId",
-  "aggregationColumns"
-]New value: +[
+  "datasetId",
+  "groupByColumns"
+]

Previous value: -"The number of non-represented rows for this column"New value: +"Number of rows NOT included in the returned aggregations for this column (only top groups are returned)"

Previous value: -"The number of non-represented rows in the dataset, 0 if totalAggregated is less than 20, otherwise the number of non-represented rows"New value: +"Number of rows NOT included in the returned aggregations (only the top 20 groups are returned). Add this to the sum of all group totals to reconstruct the dataset total."

Previous value: -"The unique dataset ID obtained from search_datasets or provided by the user"New value: +"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."

Previous value: -"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"New value: +"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). All values must be strings, even for numbers/dates. If a column key has underscores (e.g., code_postal), just append the suffix: code_postal_eq. Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"

Previous value: -"The calculated metric value (number for most metrics, object for stats/percentiles)"New value: +"The calculated metric value. For avg/sum/min/max/value_count/cardinality: a single number. For stats: an object {count, min, max, avg, sum}. For percentiles: an object mapping percentage strings to values, e.g. {\"25\": 30000, \"50\": 42000, \"75\": 55000}."

Previous value: -"The unique dataset ID obtained from search_datasets or provided by the user"New value: +"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."

Previous value: -"The unique dataset ID obtained from search_datasets or provided by the user"New value: +"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."

Previous value: -"The unique dataset ID obtained from search_datasets or provided by the user"New value: +"The exact dataset ID from the \"id\" field in search_datasets results. Do not use the title or slug."

Previous value: -"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"New value: +"Column filters as key-value pairs. Key format: column_key + suffix (see server instructions for available suffixes). All values must be strings, even for numbers/dates. If a column key has underscores (e.g., code_postal), just append the suffix: code_postal_eq. Example: { \"nom_search\": \"Jean\", \"age_lte\": \"30\", \"ville_eq\": \"Paris\" }"

Previous value: -"URL from a previous search_data response to fetch the next page of results. When provided, all other parameters (query, filters, select, size) are ignored since the URL already contains them."New value: +"URL from a previous search_data response to fetch the next page of results. When provided, all other parameters (query, filters, select, sort, size) are ignored since the URL already contains them."

Previous value: -"French keywords for full-text search across all dataset columns (simple keywords, not sentences). Do not use with filters parameter. Examples: \"Jean Dupont\", \"Paris\", \"2025\""New value: +"French keywords for full-text search across all dataset columns (simple keywords, not sentences). Can be combined with filters, but prefer filters alone when criteria target specific columns. Use query for broad keyword matching across all columns. Examples: \"Jean Dupont\", \"Paris\", \"2025\""

Added value: +{
+  "description": "Sort order for results. Comma-separated list of column keys. Prefix with - for descending order. Special keys: _score (relevance), _i (index order), _updatedAt, _rand (random). Examples: \"population\" (ascending), \"-population\" (descending), \"city,-population\" (city asc then population desc)",
+  "type": "string"
+}

Previous value: -"French keywords for full-text search (simple keywords, not sentences). Examples: \"élus\", \"DPE\", \"entreprises\", \"logement social\""New value: +"French keywords for full-text search (simple terms, not sentences). If 0 results, try synonyms or broader terms. Examples: \"élus\", \"DPE\", \"entreprises\", \"logement social\""