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damoqiongqiu

mcp-local-rag

by damoqiongqiu

ingest_data

Add in-memory text, HTML, or Markdown to the local RAG index. Use a source identifier to update existing content on re-ingestion.

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
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals a key behavioral trait—re-ingestion with the same source identifier updates existing content—and specifies the return shape. While it does not mention auth, permissions, or side effects, it covers the main behavioral consequences for the typical use case.

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?

The description is two sentences long and front-loaded with the tool's core purpose. It efficiently packs the alternative tool reference, the re-ingestion behavior, and the return value into a compact, well-structured format with zero filler.

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 has 2 parameters (one nested), no annotations, and no output schema, the description provides a complete picture: what it does, when to use it, how the source identifier behaves, and what it returns. It lacks explicit error scenarios or prerequisites, but these are not critical for a simple ingestion tool. The return value statement covers the output side.

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 50% (content and format described in schema, metadata partially). The description adds significant value by explaining the 'source' identifier protocol with examples (e.g., 'clipboard://2024-12-30', 'chat://2024-12-30/project-discussion'), which is essential for correct invocation. This compensates well for the moderate schema coverage.

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 uses the specific verb 'Ingest' and clearly specifies the resource: 'in-memory content as a string'. It further distinguishes itself from a sibling tool by explicitly pointing to 'ingest_file' for disk files, making the purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool (in-memory string content) and when not to (files on disk, via 'use ingest_file for files on disk'). This provides clear alternatives and context for selection.

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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