Analyze tiered public cloud data transfer egress fees vs Cloudflare Zero-Egress Bandwidth Alliance and edge caching proxy, calculating monthly and annual infrastructure cost savings.
| Name | Required | Description | Default |
|---|---|---|---|
| cacheHitRatio | No | Projected CDN edge cache hit ratio (0.0 to 1.0 or 0 to 100%) | |
| monthlyEgressGB | No | Monthly internet outbound data transfer in GB (e.g. 50,000 for 50TB) |
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. It transparently states the tool analyzes and calculates savings, which suggests a read-only estimation or calculator behavior. However, it does not disclose methodology, assumptions, or output format, leaving some ambiguity about exactly what results will be returned.
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, information-dense sentence with no filler or repetition. It front-loads the core purpose and communicates the comparison and output calculation efficiently. It is slightly long but every phrase earns its place.
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?
For a tool with only two well-documented parameters and no nested objects, this description is reasonably complete. It explains the purpose, the comparison scenario, and the expected output (monthly and annual cost savings). It does not detail formula specifics or output precision, but those are not required given the tool's moderate complexity.
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 already provides complete descriptions for both parameters, including defaults and ranges, so the schema coverage is 100%. The description adds contextual framing around cloud egress and edge caching but does not materially extend the meaning of cacheHitRatio or monthlyEgressGB beyond the schema.
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 identifies the tool's action ('Analyze'), the resource ('tiered public cloud data transfer egress fees'), and the comparison scenario ('vs Cloudflare Zero-Egress Bandwidth Alliance and edge caching proxy'). It also states the computed outcome: monthly and annual infrastructure cost savings. This is specific enough to distinguish it from siblings like fx_invoicing or black_scholes.
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 implies the tool is for analyzing public cloud egress costs against Cloudflare alternatives, so an agent can infer when to use it. However, it does not explicitly say when not to use it or mention any alternative tools. The usage context is present but relies on inference rather than direct guidance.
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.
