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TsvetanG2

cognigy-ai-mcp-management-server

delete_knowledge_connector

DestructiveIdempotent

Delete a Cognigy.AI knowledge connector to stop automated content ingestion from an external source. Use dryRun=false to perform the deletion.

Instructions

Deletes a Cognigy.AI knowledge connector. Stops automated content ingestion from the external source. MUTATING: Set dryRun=false to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNoIf true (default), validates without deleting. Set to false to actually delete.
connectorIdYesThe knowledge connector ID to delete
knowledgeStoreIdYesThe knowledge store ID containing the connector
Behavior4/5

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

Annotations already signal destructive behavior (destructiveHint=true, readOnlyHint=false). The description adds context that deletion stops automated ingestion and explains the dryRun flag for safe validation. This goes beyond annotations by clarifying the side effect and safe usage pattern.

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?

Two concise sentences with no superfluous information. The first sentence is the primary purpose, the second adds critical usage detail. Perfectly front-loaded and efficient.

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?

For a deletion tool with 3 parameters, no output schema, and strong annotations, the description covers purpose, side effect, and dryRun behavior. It does not specify return values or confirm deletion, but given the annotations and schema, it is sufficiently complete. Lacks comparative guidance against siblings but overall adequate.

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 input schema covers 100% of parameters with descriptions. The description adds a note about dryRun (set to false to delete) but this is already implied by the schema's description of dryRun. No additional semantic value beyond the schema.

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 action ('Deletes') and the resource ('Cognigy.AI knowledge connector'), and additionally explains the consequence ('stops automated content ingestion'). This distinguishes it from sibling delete tools like delete_knowledge_store.

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 guidance on when to use this tool versus alternatives (e.g., delete_knowledge_store). The description implies use when you need to delete a connector and stop ingestion, but does not provide exclusion criteria or context for other deletion tools.

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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