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Ingest Knowledge

neuron_ingest_knowledge
Idempotent

Ingest content into a knowledge base with deduplication and optional LLM processing for summarization, fact extraction, or custom instructions.

Instructions

Ingest content into a knowledge base. Supports deduplication via externalId and optional LLM processing (summarize, extract_facts, or custom instruction).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesTitle for the knowledge entry
folderNoFolder: 'general', 'skills', 'contexts', 'documents', or 'faqs' (default: general)
sourceNoSource type (default: mcp)mcp
contentYesContent to ingest
sourceUrlNoSource URL for reference
externalIdNoUnique external ID for deduplication (e.g. file path, URL)
processingNoOptional LLM processing before storage
knowledgeBaseIdYesKnowledge base ID to ingest into
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes idempotency via externalId and optional LLM processing, adding context beyond annotations (idempotentHint=true). No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, front-loaded key info. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema; description lacks information about return values or errors. Adequate for input behavior but could be more complete about post-ingest results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but description adds meaning by explaining dedup usage and processing modes (summarize, extract_facts, custom). Enhances understanding beyond property descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'Ingest content into a knowledge base' and mentions key features (deduplication, optional LLM processing). Distinguishes from siblings like neuron_create_kb_entry by highlighting dedup and processing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage through dedup and processing options, but no explicit when-to-use or when-not-to-use guidance compared to alternatives (e.g., create_kb_entry, sync_knowledge).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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