task_list
List all task IDs, names, and descriptions to provide an overview of available Figranium automation tasks.
Instructions
List all task IDs, names, and descriptions from Figranium.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List all task IDs, names, and descriptions to provide an overview of available Figranium automation tasks.
List all task IDs, names, and descriptions from Figranium.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. The verb 'List' implies a read-only, non-mutating operation, but it doesn't explicitly warn about potential large results, pagination, or performance. It's adequate but sparse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with no filler. It directly states the action and output, making it extremely concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with simple output, the description provides the essential information: what is listed and from where. It doesn't explain return format or edge cases, but the simplicity of the tool makes this sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema coverage is trivially 100%. The description doesn't need to elaborate on parameters, earning the baseline score for no-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and clearly identifies the resource: task IDs, names, and descriptions from Figranium. It effectively distinguishes this tool from siblings like create_task and task_execute, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when a list of tasks is needed. While it doesn't explicitly exclude alternatives like execution_list or schedule_list, the unique phrasing 'task IDs, names, and descriptions' makes the context unmistakable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/figranium/figranium-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server