Skip to main content
Glama

Ingest materials

ingest_materials

Extracts text and topic inventory from source documents, transcribes image-only PDFs, and returns a materials ID for building presentations.

Instructions

Extract text + topic inventory from source files (pdf/docx/pptx/md/txt) within the allowed roots. Image-only PDFs are transcribed via vision. Returns a materialsId used by define_scope/plan_presentation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathsYesAbsolute paths within allowed ingest roots.
courseContextNo
Behavior3/5

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

Since no annotations are provided, the description carries the burden. It discloses a specific behavior (image-only PDFs are transcribed via vision) and a constraint (allowed roots), but it omits details about side effects, permissions, error handling, or whether it modifies files. The return of a materialsId implies some stored artifact, but that is not made explicit.

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 only two sentences, immediately states the core action, lists formats, highlights a special case, and specifies the output usage. Every sentence contributes value without redundancy, making it efficiently scannable.

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?

The description covers the primary function, output, and even a special case, but it does not explain 'courseContext', error scenarios, or the exact nature of the materialId. Given the tool's moderate complexity and lack of output schema, more detail about return behavior and constraints would be needed for full completeness.

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?

The schema covers only 'paths' with a description; 'courseContext' is undescribed. The description adds useful context for 'paths' by enumerating supported file types and emphasizing 'allowed roots', but it completely fails to explain the purpose or format of 'courseContext', leaving a gap in parameter understanding.

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 a specific verb 'Extract' with a clear resource 'text + topic inventory from source files' and lists supported formats. It distinguishes itself from sibling tools by focusing on ingestion and returning a materialsId for downstream use by define_scope/plan_presentation.

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?

The description clearly implies usage context: it processes source files within allowed roots and the returned materialsId is used by other tools, suggesting it is an initial ingestion step. However, it does not explicitly state when not to use it or name alternative tools, but the sibling list makes the distinction fairly obvious.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/CompSciGuyIT/PresentationMcpServer'

If you have feedback or need assistance with the MCP directory API, please join our Discord server