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topology_optimize_submit

Submit a topology optimization job to maximize stiffness for a 2D or 3D design domain under a mass constraint, returning a job ID for asynchronous polling.

Instructions

Minimum-compliance topology optimization (in-house SIMP; NO external solver), asynchronous because each iteration solves an FE system. Optimizes a 2-D rectangular design domain (nelx×nely unit cells) — or, when nelz is set, a 3-D nelx×nely×nelz grid of trilinear hexahedra — to the stiffest layout that holds Σdensity = keep_fraction (the Optimality-Criteria update holds it exactly); penal is the SIMP penalty (≈3), rmin the cone filter radius. Default BCs (both): the whole left face clamped + a unit downward load at the right-face centre. 2-D overrides: fixed_dofs / load=[dof_index, value]. 3-D overrides: loads=[[i,j,k,axis,value],...] point loads at node grid coords (axis 'x'|'y'|'z'), fixed_nodes=[[i,j,k],...] clamped nodes, and keep_out/keep_in lists of half-open element-index boxes [i0,i1,j0,j1,k0,k1] forced void / forced solid (keep-out regions and must-keep pads).

Returns immediately {job_id, status, cache_hit}; poll job_result for {density (2-D: nely×nelx grid; 3-D: nelz×nely×nelx voxel field, density[k][j][i] with j=0 at the bottom — this IS geometry), mass_fraction (==keep_fraction), compliance, compliance_initial, iterations, converged, gray_fraction, solver (3-D: which linear-solve backend ran)}. Threshold + voxel→solid back in the modeller with topology_to_solid, then gate with mass_properties (mass ≤ keep_fraction·original) and interference_check vs keep-outs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tolNo
loadNo
nelxNo
nelyNo
nelzNo
rminNo
loadsNo
penalNo
keep_inNo
keep_outNo
max_iterNo
fixed_dofsNo
fixed_nodesNo
keep_fractionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and discloses rich behavior: in-house SIMP with no external solver, asynchronous execution, immediate return of job_id/status/cache_hit, required polling via job_result, default boundary conditions, 2-D vs 3-D overrides, and returned quantities including geometry interpretation.

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?

The description is dense and lengthy, but appropriately sized for a complex 14-parameter optimization tool. It front-loads the core purpose, then groups default BCs, 2-D overrides, 3-D overrides, return values, and workflow in a usable order.

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 annotations and no output schema, the description supplies the missing return structure and workflow, including job polling and voxel-to-solid post-processing. It covers enough of the parameter space and behavior for an agent to call the tool correctly.

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 description coverage is 0% across 14 parameters, so the description must compensate. It explains nelx, nely, nelz, keep_fraction, penal, rmin, load/fixed_dofs, loads/fixed_nodes, and keep_out/keep_in in useful detail, but does not clarify tol or max_iter semantics.

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

Purpose4/5

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

States a specific verb and resource: minimum-compliance topology optimization using in-house SIMP. It clearly describes the 2-D and 3-D domains and objectives, but does not explicitly distinguish itself from sibling optimization tools such as optimize_submit or study_submit.

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?

Provides clear context that it is an asynchronous computational job, tells the agent to poll job_result, and specifies downstream workflow with topology_to_solid, mass_properties, and interference_check. It does not explicitly state when to choose it over alternative optimization tools or when not to use it.

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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