Skip to main content
Glama
Sign In
Cortex Intelligent

Cortex Intelligent

by adyoi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

knowledge_ingest_text

Ingest raw text into a searchable knowledge base by chunking and embedding it for later retrieval.

Instructions

Store raw text as a knowledge document (chunked + embedded for later retrieval)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "content": "<content>",
      "title": "<title>"
    },
    "name": "knowledge_ingest_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleYesDocument title
contentYes
metadataNo
contentTypeNoe.g. markdown, typescript, text, json

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the processing pipeline ('chunked + embedded for later retrieval'), which is real value beyond the schema, but omits idempotency/dedup behavior, permissions, and what happens on re-ingest of the same title.

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

Conciseness4/5

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

A single front-loaded sentence with zero wasted words, and the parenthetical behavior note is packed efficiently. Terse rather than padded, though it sacrifices some detail for brevity.

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

Completeness2/5

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

A mutation tool with no annotations, no output schema, and half its parameters undocumented needs more than one sentence. Missing dedup/idempotency behavior, permission requirements, and metadata semantics leave an agent under-informed before calling it.

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

Parameters2/5

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

Schema coverage is only 50%, and the two undocumented params (content, metadata) are the most consequential — content is required and metadata is a nested object. The description adds no meaning for any parameter, so it fails to compensate for the coverage gap.

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

Purpose4/5

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

States a specific verb+resource (store raw text as a knowledge document) with a clear scope. 'Raw text' implicitly contrasts it with the file/dir ingestion siblings, though it never names them explicitly, so sibling differentiation is only implicit.

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?

No explicit when-to-use or when-not-to-use guidance. The 'raw text' phrasing hints that inline text is the input and file/dir siblings handle other sources, but the agent must infer the alternative rather than being routed to it.

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

Deploy Server

Other Tools