Summarize AIS maritime traffic data by vessel and time window.
npx skills add https://github.com/victorhramos-dev/ais_ai --skill ais-analysis-llm
Please help me install this Agent Skill. Skill: ais-analysis-llm Source: https://github.com/victorhramos-dev/ais_ai/tree/main/.claude/skills/ais-analysis-llm Command: npx skills add https://github.com/victorhramos-dev/ais_ai --skill ais-analysis-llm
This Skill automates maritime traffic analysis using an LLM to generate insights and period-based summaries from AIS data, enabling efficient monitoring and decision support.
Configure Minimax API credentials, trigger an analysis manually or via interval/batch flow, and run the RunAnalysis job to generate and broadcast the summary.
High-intent search queries and answers about installing and using this skill.
Maritime traffic analysis is automated by aggregating AIS messages by vessel MMSI, constructing context windows, and using a large language model to generate period-based summaries. This pipeline produces daily traffic volume and risk indicator reports.
Generating daily AIS summaries involves grouping vessel messages by MMSI and feeding that context into an LLM. This method extracts traffic volume, active vessels, notable movements, and risk indicators for shipping operations teams.
Configuring Minimax API integration requires setting up API credentials before triggering the analysis job. The system enforces exponential retries for external API calls and applies a 30-second LLM timeout to ensure reliable maritime report generation.
Yes, this AIS data analysis approach supports Portuguese system prompts specifically configured for the Port of Santos. It automatically generates maritime traffic summaries and risk indicators localized for regional shipping operations.
Monitoring LLM latency and token usage during maritime traffic analysis is handled through automated metric persistence. The system stores tokens used and response latency alongside the generated AIS summaries for ongoing monitoring and auditability.
Limitations of using LLMs for AIS data analysis include a strict 30-second timeout constraint and dependency on external API availability with exponential retries. The system focuses on period-based summaries rather than real-time vessel tracking.
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