nia

The Nia research agent provides a specialized framework for AI assistants to conduct deep technical research and manage external knowledge sources. By integrating the Nia MCP server, it allows agents to move beyond surface-level web searches into structured, high-fidelity data retrieval from GitHub repositories, documentation sites, and package managers. This skill is designed for developers and technical researchers who need consistent, accurate context for complex coding tasks or architectural discovery. It effectively bridges the gap between fragmented web information and deep codebase understanding by forcing agents to treat indexed repositories as primary sources of truth, thereby mitigating common LLM hallucination patterns.

• Full integration with Nia MCP tools including indexing, searching, and managing resources.

• Advanced capabilities for targeted repository exploration using nia_grep, nia_read, and nia_explore.

• Automated research workflows that prioritize internal indexes over truncated WebFetch or WebSearch results.

• Contextual knowledge preservation via integrated save and sync mechanisms.

• Support for multi-agent environments including Claude, Cursor, Windsurf, Roo, and Cline configurations.

• Before initiating any external lookup, the agent must check existing managed resources using manage_resource to minimize redundant API calls.

• Always index root documentation URLs (e.g., docs.stripe.com) to ensure comprehensive crawling rather than relying on search snippets.

• If a source is unknown, utilize nia_research in quick or deep modes to discover relevant entry points.

• Be prepared for asynchronous indexing; the agent should manage user expectations regarding latency when processing large codebases.

• Maintain a dedicated .md file to track indexed source IDs, links, and discovery history for future conversational reuse.

• Prefer structured data extraction from npm, PyPI, and GitHub over generic search results to maintain high-precision input.