Skip to main content
Glama
debugg-ai

Debugg AI MCP

Official
by debugg-ai

Test Case

test_case
Destructive

Create, update, or delete test cases in a suite. Define agent tasks, descriptions, and configurations.

Instructions

Manage individual test cases within a suite. Pass an "action":

  • "create" {name, description, agentTaskDescription, suiteUuid|(suiteName+project), relativeUrl?, maxSteps?} → add a test case (NOT auto-run).

  • "update" {testUuid, name?, description?, agentTaskDescription?} → patch a test case.

  • "delete" {testUuid, confirm?} → soft-delete (DESTRUCTIVE; requires confirmation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesOperation to perform.
testUuidNo[update/delete] Test case UUID.
nameNoTest case name.
descriptionNoTest case description.
agentTaskDescriptionNoWhat the AI agent should do and verify.
suiteUuidNo[create] Suite UUID.
suiteNameNo[create] Suite name (requires a project identifier).
projectUuidNo[create] Project UUID (or projectName).
projectNameNo[create] Project name (or projectUuid).
relativeUrlNo[create] Starting path, must start with "/".
maxStepsNo[create] Max agent steps (1..100).
confirmNo[delete] Set true to confirm deletion (when the client cannot prompt).
Behavior4/5

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

Annotations already indicate destructiveHint=true and readOnlyHint=false. Description adds that delete is a soft-delete requiring confirmation, and create does not auto-run. No contradictions.

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?

Well-structured with bullet points separating actions. Efficiently communicates purpose and per-action details. Slightly lengthy but every sentence provides necessary context.

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?

Covers all three CRUD operations with parameter constraints. Without output schema, omission of return values is acceptable. Includes important behavioral notes like soft-delete and no auto-run.

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

Parameters4/5

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

Input schema covers all parameters (100% coverage). Description adds value by grouping parameters per action and clarifying conditional requirements (e.g., 'requires a project identifier' for suiteName).

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 'Manage individual test cases within a suite' and enumerates three actions (create, update, delete) with specific resources. It distinguishes from siblings like test_suite by focusing on test case CRUD.

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?

Explicitly lists actions and their required/optional parameters. Notes that create does not auto-run and delete is destructive requiring confirmation. Lacks explicit comparison to sibling tools but usage context is clear.

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/debugg-ai/debugg-ai-mcp'

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