Skip to main content
Glama
openl-tablets

OpenL MCP Server

Official

openl Cancel Trace

openl_cancel_trace

Cancel an ongoing trace execution for a project to stop monitoring and debugging processes.

Instructions

Cancel ongoing trace execution for a project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID returned by backend. Use the exact 'projectId' value from openl_list_projects() response without modification or reformatting.
response_formatNoResponse format: 'json' for structured data, 'markdown' for human-readable (default), 'markdown_concise' for brief summary (1-2 paragraphs), 'markdown_detailed' for full details with contextmarkdown
Behavior2/5

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

The description only states it cancels a trace, but does not disclose behavioral traits such as whether cancellation is reversible, what happens to partially collected data, or any auth/rate-limit requirements. The 'openWorldHint: true' annotation does not mitigate this lack of detail.

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 concise sentence that front-loads the core action: 'Cancel ongoing trace execution for a project.' No filler or redundant information. Every word earns its place.

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?

For a simple mutation tool with no output schema, the description provides the essential purpose but lacks details on effects (e.g., confirmation, failure modes, or data integrity). It is adequate but not complete, considering the tool's simplicity and available sibling context.

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%, so the baseline is 3. The projectId parameter includes a helpful instruction to use the exact value from openl_list_projects() without modification, adding some value. The response_format parameter is well-documented with enum and default. Overall, the description adds minimal extra meaning 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 uses a specific verb 'Cancel' and resource 'ongoing trace execution for a project', clearly distinguishing this tool from sibling tools like openl_start_trace which initiates traces. It succinctly conveys the tool's primary function.

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, such as when a trace should be cancelled, or any prerequisites (e.g., the trace must be actively running). The description lacks context for proper selection.

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/openl-tablets/openl-mcp'

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