Skip to main content
Glama
drkavner

ghl-internal-cli

by drkavner

ghl_knowledge_base_train_urls

Train an array of URLs into a knowledge base so AI agents can access updated information. Requires knowledgeBaseId, locationId, and urls.

Instructions

Train discovered URLs into a knowledge base (accepts an array of URLs)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYesList of URLs to train on
locationIdYesLocation ID (uses GHL_LOCATION_ID if omitted)
knowledgeBaseIdYesKnowledge base ID
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states the action without mentioning side effects, required permissions, rate limits, or whether the operation is asynchronous. The schema's contradictory required flag on locationId (description says it can be omitted) also adds ambiguity.

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 a single sentence that front-loads the core action and resource. It contains no filler or redundant phrases, making it appropriately sized for a simple tool description.

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?

Given the tool's state-changing nature and lack of an output schema, the description should clarify expected return values, prerequisites (e.g., valid knowledgeBaseId, prior URL discovery), and any side effects. It does none of this, leaving the agent under-informed for a tool with three required parameters.

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 100% and each parameter has a description, so the baseline is 3. The tool description adds no new parameter meaning beyond what the schema already provides; the 'array of URLs' note is redundant. It also fails to resolve the schema's internal contradiction regarding locationId requiredness.

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 clearly states the verb 'Train' and the resource 'knowledge base', making the action specific. It distinguishes from sibling tools like ghl_knowledge_base_list and ghl_knowledge_base_discover_website by focusing on training URLs, which is a different operation.

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?

The description implies a usage context ('discovered URLs' suggests a preceding discovery step) but does not explicitly state when to use this tool versus discover_website or list. No alternatives or exclusions are mentioned, so guidance is only implicit.

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/drkavner/ghl-internal-cli'

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