Calculate structural engineering beam deflection, max bending moment, and peak stress (Euler-Bernoulli beam).
| Name | Required | Description | Default |
|---|---|---|---|
| loadNewtons | Yes | Point load P in Newtons (N) | |
| lengthMeters | Yes | Beam span L in meters (m) | |
| elasticModulusGpa | No | Young's Modulus E in GPa (e.g. 200 for structural steel) | |
| momentOfInertiaCm4 | Yes | Area moment of inertia I in cm^4 | |
| distanceFromNeutralAxisMm | Yes | Distance y to extreme fiber in mm |
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 lists three outputs but does not reveal the support conditions assumed (e.g., simply supported, cantilever), which materially affect results. It also does not mention unit conversions or constraints such as positive load, leaving the agent to infer behavior from the raw formula.
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?
A single, front-loaded sentence with no filler. It names the outputs and the theory in an efficient, scannable way.
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 and no annotations, the definition is incomplete for a tool with four required parameters and three outputs. It fails to specify support conditions, output units, or formula assumptions, leaving notable ambiguity for an agent deciding how to interpret and verify results.
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 schema already documents each parameter with units. The description adds only the Euler-Bernoulli context, which implies linear elastic behavior but does not explain how the parameters combine or what the outputs will be. Baseline 3 is appropriate because the description neither compensates nor detracts from the already-complete 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 states a specific verb ('Calculate') and a specific resource ('structural engineering beam deflection, max bending moment, and peak stress'), and further identifies the theory ('Euler-Bernoulli beam'). This clearly distinguishes it from sibling tools like projectile_motion or rlc_circuit, which address unrelated domains.
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 is given about when to use this tool versus alternatives, nor are prerequisites or boundary conditions stated. The description only implies use when beam deflection/moment/stress calculations are needed, but offers no explicit when-to-use or when-not-to-use context.
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.
