start_study_app
Activate the local study app to manage flashcard decks, take quizzes, and review cards through natural language interactions.
Instructions
Local study app tool
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Activate the local study app to manage flashcard decks, take quizzes, and review cards through natural language interactions.
Local study app tool
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits but does not. It does not explain what 'starting' entails (e.g., launches a process, opens a UI, requires prerequisites), leaving agents uncertain about side effects.
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 too short (5 words) and fails to convey necessary information; it is under-specified rather than concise. Every sentence should add value, but this lacks substance.
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?
Given the presence of many sibling tools and no output schema or annotations, the description is completely inadequate. It provides no behavioral context, return info, or differentiation, making it nearly useless for an agent.
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?
No parameters exist, so schema coverage is 100% by default. The description adds minimal context but is not required to elaborate on parameters. Baseline of 4 is appropriate.
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 'Local study app tool' indicates the tool relates to a study app but does not specify the action 'start' or 'launch', which is only implied by the name. It vaguely describes the resource but lacks a clear verb.
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?
No guidance on when to use this tool versus siblings like open_study_app, get_study_app_status, or stop_study_app. The description fails to differentiate usage context.
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/resace3/mcp-local-study-app'
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