Parse API, webhook, file, and sensor data into validated structured payloads.
npx skills add https://github.com/synaptiai/agent-capability-standard --skill receive
Please help me install this Agent Skill. Skill: receive Source: https://github.com/synaptiai/agent-capability-standard/tree/main/skills/receive Command: npx skills add https://github.com/synaptiai/agent-capability-standard --skill receive
Ingests and parses incoming data from APIs, webhooks, files, and sensors into a consistent, structured representation for downstream processing and auditing.
Provide a data source and optional format to ingest data, then read the structured output for downstream processing.
High-intent search queries and answers about installing and using this skill.
To ingest and parse webhook payloads into a structured format, provide the data source and an optional format specification. The system detects the format, validates it against optional schemas, and outputs normalized messages ready for downstream processing.
Yes, you can validate API responses against optional schemas during data ingestion. The system detects formats like JSON or XML and validates the incoming data to ensure quality and provenance before outputting a structured payload.
The best way to normalize external data streams from APIs, files, and sensors is to use a parsing tool that detects formats automatically. This ensures all incoming data is converted into a consistent, schema-ready structure with provenance metadata.
Yes, data format detection works automatically for file uploads without requiring manual configuration. The system identifies formats such as JSON, XML, YAML, and text, then parses the content into a validated, structured representation.
To handle sensor data ingestion for downstream analytics, route the external data streams through the parsing tool. It ingests and parses the raw sensor inputs into a structured, validated representation with provenance metadata for safe downstream consumption.
Adding provenance metadata when parsing external data grounds the ingested payloads with source context and validation history. This ensures safe parsing, enables consistent output shape, and provides an auditable trail for downstream auditing.
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