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xiuxiansk

mcp-local-rag

by xiuxiansk

ingest_data

Ingest text, HTML, or Markdown strings into a local RAG for hybrid semantic and keyword search, using a source identifier to update existing content.

Instructions

Ingest in-memory content as a string (use ingest_file for files on disk). The source identifier enables re-ingestion to update existing content. Returns { filePath, chunkCount, timestamp, fileTitle }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe content to ingest (text, HTML, or Markdown)
metadataYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return shape and re-ingestion behavior ('source identifier enables re-ingestion to update existing content'), which gives insight into idempotency/update semantics. However, it doesn't mention whether ingestion is destructive, how conflicts are handled, or any side effects beyond the return value.

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 sentences, front-loaded with the primary action, and no filler. The alternative reference and return type are included efficiently.

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

Completeness4/5

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

Given the tool's simplicity, the description covers the core purpose, sibling distinction, and return value. It doesn't discuss error cases or operational prerequisites, but the schema fills in parameter details. It is adequately complete for an ingestion tool with no annotations or output schema.

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

Parameters3/5

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

Schema coverage is 50%, but the description adds meaning to the 'source' parameter by explaining its role in re-ingestion. It also confirms 'content' is a string. The nested metadata format options are already well-described in the schema, so the description provides marginal added value.

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?

The description opens with a specific verb+resource: 'Ingest in-memory content as a string', immediately distinguishing it from 'ingest_file' for disk files. It clearly states what the tool does and the scope (in-memory content).

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

Usage Guidelines4/5

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

Explicitly names an alternative tool ('use ingest_file for files on disk') and implies this tool is for in-memory strings. It gives a clear when-to-use vs. alternative, though it doesn't cover all sibling tools.

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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