# Send Json Parser to your agent Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually. ## Fast path - Download the package from Yavira. - Extract it into a folder your agent can access. - Paste one of the prompts below and point your agent at the extracted folder. ## Suggested prompts ### New install ```text I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete. ``` ### Upgrade existing ```text I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run. ``` ## Machine-readable fields ```json { "schemaVersion": "1.0", "item": { "slug": "json-parser", "name": "Json Parser", "source": "tencent", "type": "skill", "category": "开发工具", "sourceUrl": "https://clawhub.ai/datadrivenconstruction/json-parser", "canonicalUrl": "https://clawhub.ai/datadrivenconstruction/json-parser", "targetPlatform": "OpenClaw" }, "install": { "downloadUrl": "/downloads/json-parser", "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=json-parser", "sourcePlatform": "tencent", "targetPlatform": "OpenClaw", "packageFormat": "ZIP package", "primaryDoc": "SKILL.md", "includedAssets": [ "claw.json", "instructions.md", "SKILL.md" ], "downloadMode": "redirect", "sourceHealth": { "source": "tencent", "slug": "json-parser", "status": "healthy", "reason": "direct_download_ok", "recommendedAction": "download", "checkedAt": "2026-05-04T14:53:49.802Z", "expiresAt": "2026-05-11T14:53:49.802Z", "httpStatus": 200, "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=json-parser", "contentType": "application/zip", "probeMethod": "head", "details": { "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=json-parser", "contentDisposition": "attachment; filename=\"json-parser-2.1.0.zip\"", "redirectLocation": null, "bodySnippet": null, "slug": "json-parser" }, "scope": "item", "summary": "Item download looks usable.", "detail": "Yavira can redirect you to the upstream package for this item.", "primaryActionLabel": "Download for OpenClaw", "primaryActionHref": "/downloads/json-parser" }, "validation": { "installChecklist": [ "Use the Yavira download entry.", "Review SKILL.md after the package is downloaded.", "Confirm the extracted package contains the expected setup assets." ], "postInstallChecks": [ "Confirm the extracted package includes the expected docs or setup files.", "Validate the skill or prompts are available in your target agent workspace.", "Capture any manual follow-up steps the agent could not complete." ] } }, "links": { "detailUrl": "https://openagent3.xyz/skills/json-parser", "downloadUrl": "https://openagent3.xyz/downloads/json-parser", "agentUrl": "https://openagent3.xyz/skills/json-parser/agent", "manifestUrl": "https://openagent3.xyz/skills/json-parser/agent.json", "briefUrl": "https://openagent3.xyz/skills/json-parser/agent.md" } } ``` ## Documentation ### Overview Construction systems increasingly use JSON for data exchange - from IoT sensors to BIM metadata exports. This skill handles parsing, validation, and flattening of JSON structures. ### Python Implementation import json import pandas as pd from typing import Dict, Any, List, Optional, Union from dataclasses import dataclass from pathlib import Path @dataclass class JSONParseResult: """Result of JSON parsing operation.""" success: bool data: Any errors: List[str] record_count: int class ConstructionJSONParser: """Parse JSON data from construction sources.""" def __init__(self): self.errors: List[str] = [] def parse_file(self, file_path: str) -> JSONParseResult: """Parse JSON from file.""" try: with open(file_path, 'r', encoding='utf-8') as f: data = json.load(f) return JSONParseResult(True, data, [], self._count_records(data)) except json.JSONDecodeError as e: return JSONParseResult(False, None, [f"JSON Error: {e}"], 0) except Exception as e: return JSONParseResult(False, None, [str(e)], 0) def parse_string(self, json_string: str) -> JSONParseResult: """Parse JSON from string.""" try: data = json.loads(json_string) return JSONParseResult(True, data, [], self._count_records(data)) except json.JSONDecodeError as e: return JSONParseResult(False, None, [f"JSON Error: {e}"], 0) def _count_records(self, data: Any) -> int: """Count records in data.""" if isinstance(data, list): return len(data) elif isinstance(data, dict): return 1 return 0 def flatten_json(self, data: Dict, prefix: str = '') -> Dict[str, Any]: """Flatten nested JSON to single-level dict.""" flat = {} for key, value in data.items(): new_key = f"{prefix}_{key}" if prefix else key if isinstance(value, dict): flat.update(self.flatten_json(value, new_key)) elif isinstance(value, list): if all(isinstance(i, (str, int, float, bool, type(None))) for i in value): flat[new_key] = value else: for i, item in enumerate(value): if isinstance(item, dict): flat.update(self.flatten_json(item, f"{new_key}_{i}")) else: flat[f"{new_key}_{i}"] = item else: flat[new_key] = value return flat def to_dataframe(self, data: Union[List[Dict], Dict]) -> pd.DataFrame: """Convert JSON data to DataFrame.""" if isinstance(data, list): flat_records = [self.flatten_json(r) if isinstance(r, dict) else {'value': r} for r in data] return pd.DataFrame(flat_records) elif isinstance(data, dict): if all(isinstance(v, list) for v in data.values()): # Dict of lists - columnar format return pd.DataFrame(data) else: flat = self.flatten_json(data) return pd.DataFrame([flat]) return pd.DataFrame() def extract_elements(self, data: Dict, path: str) -> List[Any]: """Extract elements using dot notation path.""" parts = path.split('.') current = data for part in parts: if isinstance(current, dict) and part in current: current = current[part] elif isinstance(current, list) and part.isdigit(): current = current[int(part)] else: return [] return current if isinstance(current, list) else [current] def validate_schema(self, data: Dict, required_fields: List[str]) -> Dict[str, Any]: """Validate JSON against required fields.""" flat = self.flatten_json(data) missing = [f for f in required_fields if f not in flat] present = [f for f in required_fields if f in flat] return { 'valid': len(missing) == 0, 'missing_fields': missing, 'present_fields': present, 'completeness': len(present) / len(required_fields) * 100 } # BIM JSON Parser class BIMJSONParser(ConstructionJSONParser): """Specialized parser for BIM JSON exports.""" def parse_bim_elements(self, data: Dict) -> pd.DataFrame: """Parse BIM elements from JSON export.""" elements = [] # Common BIM JSON structures if 'elements' in data: elements = data['elements'] elif 'objects' in data: elements = data['objects'] elif 'entities' in data: elements = data['entities'] elif isinstance(data, list): elements = data if not elements: return pd.DataFrame() # Flatten each element flat_elements = [] for elem in elements: if isinstance(elem, dict): flat = self.flatten_json(elem) flat_elements.append(flat) return pd.DataFrame(flat_elements) def extract_properties(self, element: Dict) -> Dict[str, Any]: """Extract properties from BIM element.""" props = {} # Common property locations in BIM JSON for key in ['properties', 'params', 'parameters', 'attributes']: if key in element and isinstance(element[key], dict): props.update(element[key]) return props # IoT JSON Parser class IoTJSONParser(ConstructionJSONParser): """Parser for IoT sensor data.""" def parse_sensor_reading(self, data: Dict) -> Dict[str, Any]: """Parse single sensor reading.""" return { 'sensor_id': data.get('sensor_id') or data.get('id'), 'timestamp': data.get('timestamp') or data.get('time'), 'value': data.get('value') or data.get('reading'), 'unit': data.get('unit', ''), 'location': data.get('location', '') } def parse_sensor_batch(self, data: List[Dict]) -> pd.DataFrame: """Parse batch of sensor readings.""" readings = [self.parse_sensor_reading(r) for r in data] return pd.DataFrame(readings) ### Quick Start parser = ConstructionJSONParser() # Parse from file result = parser.parse_file("bim_export.json") if result.success: df = parser.to_dataframe(result.data) print(f"Loaded {len(df)} records") # Flatten nested JSON flat = parser.flatten_json(result.data) # Extract specific path elements = parser.extract_elements(result.data, "project.building.floors") ### 1. BIM Metadata bim_parser = BIMJSONParser() result = bim_parser.parse_file("revit_export.json") elements = bim_parser.parse_bim_elements(result.data) ### 2. IoT Sensors iot_parser = IoTJSONParser() readings = iot_parser.parse_sensor_batch(sensor_data) ### 3. API Response parser = ConstructionJSONParser() result = parser.parse_string(api_response) df = parser.to_dataframe(result.data) ### Resources DDC Book: Chapter 2.1 - Semi-structured Data ## Trust - Source: tencent - Verification: Indexed source record - Publisher: datadrivenconstruction - Version: 2.1.0 ## Source health - Status: healthy - Item download looks usable. - Yavira can redirect you to the upstream package for this item. - Health scope: item - Reason: direct_download_ok - Checked at: 2026-05-04T14:53:49.802Z - Expires at: 2026-05-11T14:53:49.802Z - Recommended action: Download for OpenClaw ## Links - [Detail page](https://openagent3.xyz/skills/json-parser) - [Send to Agent page](https://openagent3.xyz/skills/json-parser/agent) - [JSON manifest](https://openagent3.xyz/skills/json-parser/agent.json) - [Markdown brief](https://openagent3.xyz/skills/json-parser/agent.md) - [Download page](https://openagent3.xyz/downloads/json-parser)