mcp-server-getalife

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

The description adds some behavioral context beyond annotations: it mentions that the explanation is 'structured' with 'practical examples,' which gives insight into the output format. However, annotations already cover key traits (read-only, non-destructive, idempotent, closed-world), so the bar is lower. The description doesn't contradict annotations, as 'explains' aligns with read-only behavior.

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 concise and front-loaded: it starts with the core purpose, adds key details (step-by-step, effectiveness, structured explanation with examples), and ends with usage guidelines. Every sentence adds value without redundancy, making it efficient 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?

Given the tool's complexity (educational explanation with parameters), annotations cover safety and idempotency, and schema fully describes inputs, the description is mostly complete. It lacks output details (no output schema), but explains the return format ('structured explanation with practical examples'), which helps. Slight deduction as it could mention idempotency or response structure more explicitly.

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 description does not mention any parameters, but schema description coverage is 100%, meaning the schema fully documents the three parameters (detail_level, include_example, currency). This meets the baseline of 3, as the description adds no param semantics but the schema compensates adequately.

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 clearly states the tool's purpose: 'Explains what Zero-Based Budgeting (ZBB) is, how it works step-by-step, and why it is the most effective budgeting method.' It specifies the verb ('explains'), the resource (ZBB), and distinguishes it from sibling tools like 'analyze_budget' or 'create_budget_plan' by focusing on education rather than analysis or creation.

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 explicitly states when to use this tool: 'Use this when someone asks about ZBB, how to budget, or how to manage their money better.' This provides clear context for invocation, distinguishing it from alternatives like 'suggest_budget_categories' or 'plan_savings_goal' that focus on specific budgeting tasks rather than explanations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.