get_stats
Retrieve statistics about TODOs to track task completion and monitor project progress.
Instructions
Get quick statistics about TODOs
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve statistics about TODOs to track task completion and monitor project progress.
Get quick statistics about TODOs
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of disclosing behavior. It only says 'Get quick statistics,' implying a read-only operation, but it does not describe what statistics are returned, whether scope is project-wide or workspace-wide, or any other behavioral traits such as performance implications or required context.
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 short sentence, 'Get quick statistics about TODOs,' which is concise and front-loaded. It contains no fluff, but its brevity does leave out important details, though that is captured in other dimensions.
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 absence of an output schema and annotations, the description is the sole source of information about what the tool returns. 'Quick statistics about TODOs' is vague: it does not specify the type of statistics (e.g., counts, statuses), the scope (current project vs all projects), or the output format. This is insufficient for an agent to fully understand the tool's behavior.
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, so the input schema fully covers parameter semantics (vacuously). The description adds nothing about parameters because there are none to describe. This meets the baseline of 4 for 0-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 states a clear verb 'Get' and resource 'statistics about TODOs', indicating an aggregate summary. It does not explicitly distinguish from sibling tools like generate_report or list_todos, but the term 'quick statistics' suggests a lightweight overview, which differentiates it somewhat.
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 is provided on when to use this tool versus alternatives. The description does not mention when to choose get_stats over generate_report or list_todos, nor does it indicate exclusions. This leaves the agent without direction for tool selection.
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/w04m1/agent-todo-mcp'
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