Calculate Solo 401(k) vs. SEP-IRA maximum legal tax-deductible retirement shelter and immediate cash tax savings under IRS Notice 2023-75 caps ($69,000 / $76,500).
| Name | Required | Description | Default |
|---|---|---|---|
| entityType | No | Entity structure: 'llc' or 'scorp' | llc |
| isAge50Plus | No | Eligible for $7,500 age 50+ catch-up | |
| netEarnings | Yes | Annual net business profit or W-2 salary ($/yr) | |
| marginalTaxRatePercent | No | Combined federal and state marginal tax bracket % |
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?
With no annotations provided, the description carries the full burden. It does state the core behavior (calculating maximum shelter and tax savings) and the governing legal caps, which gives useful context. However, it does not disclose assumptions, output format, or limitations such as whether results are annual estimates or how state taxes are incorporated.
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 sentence with no filler, and it starts with the main verb 'Calculate'. The noun phrase is somewhat dense but each element adds specificity. It could be slightly restructured for readability, but it is appropriately concise.
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?
There is no output schema, so the description must clarify return values. It names two outputs (shelter amount and cash tax savings) and the relevant cap, but it is ambiguous whether 'maximum' means the higher of the two plans or the max for each plan separately, and whether the result is a single recommendation or a comparison table. This leaves meaningful room for misinterpretation.
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?
Schema description coverage is 100%, so the parameters are already fully documented in the schema. The description adds no parameter-specific meaning beyond what the schema fields already convey, so the baseline of 3 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 uses a specific verb 'Calculate' and names the exact resource comparison: Solo 401(k) vs. SEP-IRA maximum legal tax-deductible retirement shelter and immediate cash tax savings, with explicit IRS Notice caps. This clearly distinguishes it from all sibling tools, none of which focus on retirement plan comparison.
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 gives no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The only contextual clue is the IRS Notice reference, but there is no explicit 'use when...' or comparison to sibling tools like scorp_optimizer or contractor_parity.
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.
Most tools are clearly separated by domain and target calculation, such as rocket_deltav versus projectile_motion or black_scholes versus compound_wealth. A few pairs like home_loan_emi/mortgage_piti and contractor_parity/billable_floor could be initially confused, but the descriptions resolve the intended use cases.
All tool names are lowercase snake_case and generally follow a topic-plus-suffix pattern, which is readable and consistent. The pattern is not a strict verb_noun convention, and acronym-heavy names like feie_nomad_tracker, scorp_optimizer, and casio_991_solve introduce stylistic variance.
At exactly 25 tools, this is at the heavy but still usable end of the scale. The broad spread across tax, finance, engineering, physics, math, and cloud cost makes the server feel more like several domain calculators merged into one service.
Each tool is a self-contained calculation with no missing follow-up operations, so there are no obvious dead ends for the workflows it targets. The main gaps are minor adjacent calculators—such as NPV, depreciation, or broader statistical inference—that agents could work around or obtain elsewhere.
