Deconstruct cross-border contractor invoicing fee drag, comparing landed local currency across Wise, Deel, Stripe, Payoneer, PayPal, and SWIFT wire against mid-market benchmark rates.
| Name | Required | Description | Default |
|---|---|---|---|
| invoiceUsd | Yes | Gross invoice amount in USD ($) | |
| targetCurrency | No | Target local payout currency code | EUR |
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, so the description carries the full burden of behavioral disclosure. It communicates that the tool compares providers and benchmarks, but does not state what the tool returns, assumptions, data freshness, or whether results are estimates. The verb 'Deconstruct' is metaphorical and does not clarify 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?
One sentence, dense with relevant detail including the provider list and benchmark comparison. It is front-loaded with the action and resource, and contains no filler. The phrasing is slightly jargon-heavy but still efficient.
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?
With no output schema or annotations, the description should explain expected output and use context, but it does not. It tells the agent the comparison dimensions but not what a call returns or any caveats, leaving significant gaps for a two-parameter calculation tool.
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 input schema already documents invoiceUsd and targetCurrency with defaults and enum values. The description adds little beyond the schema—'local currency' maps to targetCurrency, 'invoice' maps to invoiceUsd—so baseline 3 applies.
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?
Description names a specific resource—cross-border contractor invoicing fee drag—and lists concrete providers compared (Wise, Deel, Stripe, etc.). It clearly identifies the tool's function, though it does not explicitly distinguish it from sibling tools like contractor_parity.
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; it never mentions sibling tools or conditions that select this over others. The 'deconstruct/compare' phrasing implies use for fee comparison, but that is left to inference.
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.
