Skip to main content
Glama

list_knowledge_documents

Retrieve and display all knowledge base documents with details like ID, name, type, status, chunk count, and file size for the current tenant.

Instructions

Lists all knowledge base documents for the current tenant. Returns document id, name, type, status, chunks count, and file size.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of documents to return (default: 50)
offsetNoNumber of documents to skip for pagination (default: 0)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the return fields (e.g., id, name, type) but doesn't disclose behavioral traits like pagination behavior (implied by parameters but not explained), rate limits, authentication needs, or whether it's a read-only operation. The description is minimal and misses key operational details.

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?

The description is concise and front-loaded, stating the core purpose in the first sentence and detailing return fields in the second. Both sentences add value: the first defines the action and scope, and the second informs about output structure. No wasted words, though it could be slightly more structured.

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?

Given no annotations and no output schema, the description is incomplete. It covers the basic purpose and return fields but lacks behavioral context (e.g., pagination, errors) and doesn't fully compensate for the missing structured data. For a simple list tool, it's minimally adequate but leaves gaps in operational understanding.

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 description coverage is 100%, with clear documentation for 'limit' and 'offset' parameters. The description adds no additional parameter semantics beyond what the schema provides, such as default values or usage examples. Baseline score of 3 is appropriate since the schema handles parameter documentation adequately.

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?

The description clearly states the action ('Lists') and resource ('knowledge base documents for the current tenant'), specifying the scope as 'all' documents. It distinguishes from siblings like 'delete_knowledge_document' by focusing on listing rather than modification. However, it doesn't explicitly differentiate from other list tools (e.g., 'list_agents') beyond the resource type.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing knowledge documents to exist, or compare it to other list operations like 'list_agents'. The description lacks context on usage scenarios or exclusions.

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/MarcoAR1/botuyo-mcp'

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