Skip to main content
Glama
EvgenVer

lira-sapr-mcp

by EvgenVer

lira_self_weight

Adds self-weight loads to a LIRA load case for elements with section density, scaled by safety factor; delete_all removes all such loads.

Instructions

Add self weight loads to load_case (LIRA creates the case if needed) for all elements, or only elements, whose sections have a density, multiplied by safety_factor. delete_all=true removes all self weight loads instead (load_case is then ignored). Check the loads with lira_read_loads (type 16).

Input Schema

NameRequiredDescriptionDefault
modelNo
elementsNo
load_caseYes
delete_allNo
safety_factorNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries real weight: it discloses the side effect that LIRA creates the load case if it doesn't exist, that delete_all wipes all self-weight loads regardless of load_case, and that only elements whose sections have a density are affected. It doesn't say whether repeated calls duplicate loads (idempotency) or whether existing loads are preserved.

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

Conciseness4/5

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

Four sentences, front-loaded with the core action, then the deletion alternative, then verification. The nested parenthetical and clause stacking make it dense but nothing is redundant.

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?

An output schema exists so return values need no explanation, and the description covers the operation, its side effects, the alternate destructive mode, and how to verify results. The only gap is the `model` selector, which is minor for a five-param tool.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate, and it does for four of five params: load_case (auto-created if missing), elements (optional subset filter), delete_all (mode switch that nullifies load_case), and safety_factor (multiplier). Only `model` is left unexplained.

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 gives a precise verb+resource: adding self-weight loads derived from element section densities, scaled by safety_factor, into a named load case. This is clearly separable from siblings like lira_set_loads or lira_fragment_loads, which deal with different load categories.

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?

It states the two operating modes clearly: the default additive mode, and delete_all=true which instead removes all self-weight loads and ignores load_case. It also directs the agent to verify with lira_read_loads (type 16). It stops short of explicitly contrasting against lira_set_loads for non-self-weight loads.

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