Project retirement savings against target spending horizon.
| Name | Required | Description | Default |
|---|---|---|---|
| current_age | Yes | ||
| rate_of_return | Yes | ||
| retirement_age | Yes | ||
| annual_expenses | Yes | ||
| current_savings | Yes | ||
| life_expectancy | Yes | ||
| annual_contributions | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks any behavioral details. It does not disclose whether the tool is read-only, if it triggers side effects, or what permissions are needed, leaving the agent uninformed about potential impacts.
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 only one sentence, which is concise, but it lacks essential information given the tool's complexity. It sacrifices completeness for brevity, resulting in an under-specified definition.
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?
Despite having 7 required parameters, no output schema, and no annotations, the description provides almost no context about return values, edge cases, or assumptions. It is wholly inadequate for an agent to 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 input schema has 7 parameters with zero description coverage, and the tool description adds no explanation of these parameters. The agent must infer meaning from names alone, which is insufficient for correct invocation.
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 projects retirement savings against a target spending horizon, identifying the verb 'project' and resource 'retirement savings'. It implies a financial planning use, which distinguishes it from siblings like budget building or salary comparison, though it lacks explicit differentiation.
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 alternatives is provided. The description does not mention prerequisites, limitations, or indicate when other tools might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct aspect of personal finance (budget, country comparisons, portfolio, net worth, retirement, salary, tax) with no apparent overlap in functionality.
All tools follow a consistent verb_noun pattern in snake_case, using verbs like 'build', 'compare', 'export', 'get', 'run' followed by a descriptive noun phrase.
With 11 tools covering various personal finance analysis tasks, the count is well-scoped—neither too few to be useful nor too many to cause confusion.
The set covers key areas like budget, portfolio, net worth, retirement, salary, and tax, but may lack more granular operations like transaction management, which could be intentional for an analysis-focused server.
