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jeongho54

loadbench-mcp

by jeongho54

solve_supports

Calculate vertical reaction forces on each support of a rigid object under applied loads. Identifies supports exceeding capacity or experiencing lift-off.

Instructions

Compute how much vertical force each support (leg, bracket, foot) carries.

Models a rigid object resting on point supports of equal stiffness and solves static equilibrium so the reactions balance every applied load in force and moment. Handles any number of supports. Flags supports that exceed their rated capacity, and supports with a negative reaction (the object is lifting off / would tip rather than rest evenly).

Args: supports: [{"id": str, "x": m, "y": m, "capacity_n": N (optional)}]. loads: downward point loads [{"x": m, "y": m, "magnitude_n": N}]. self_weight_n: optional self-weight of the object (N), applied at the centroid of the supports.

Returns: per-support reaction forces, over-capacity / lift-off flags, total load, max utilisation, any warnings, and a short explanation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
loadsYes
supportsYes
self_weight_nNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses behavioral traits: equal stiffness model, handling any number of supports, flagging over-capacity and lift-off. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with summary, model details, and clear Args/Returns sections. Every sentence is informative and necessary without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately covers return values (reactions, flags, warnings, explanation). It explains assumptions and scope, providing a complete picture for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema coverage, the description provides detailed arg format and semantics (arrays of objects with specific fields like id, x, y, capacity_n, magnitude_n), adding essential meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it computes vertical force on supports for a rigid object, which is a specific verb+resource pair. It distinguishes from sibling tools like 'check_tipping' by focusing on support reaction forces rather than tipping stability.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explains the modeling scenario (rigid object on point supports of equal stiffness, solving static equilibrium) and lists capabilities. It does not explicitly contrast with alternatives but provides enough context for appropriate use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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