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Topology Optimize Submit

topology_optimize_submit

Submit a topology optimization job for a 2-D or 3-D design domain to find the stiffest layout under a volume constraint. Returns a job ID to poll for density results, compliance, and convergence data.

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

A4.6/5.0
Behavior5/5

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

Annotations only carry readOnlyHint/openWorldHint/destructiveHint; the description carries the real behavioral burden and does so thoroughly. It discloses asynchronous execution, immediate return of {job_id, status, cache_hit}, exact density/mass_fraction semantics, output axis ordering, default boundary conditions, and 2-D/3-D override formats. No contradictions with annotations.

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 front-loaded with the most critical facts (solver, async nature, objective). It is long, but every sentence adds value and parameter formats are compactly specified. A bit more structure or bullet separation would improve readability, yet nothing is wasted.

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?

For a 14-parameter tool with no output schema and no schema property descriptions, the description is remarkably complete. It covers the submission result, required polling, result field meanings and axis conventions, exact constraint behavior, default boundary conditions, per-dimension overrides, and downstream verification steps. Nothing essential is missing for correct invocation.

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%, so the description must compensate. It explains the meaning and format of most parameters: nelx/nely/nelz grid, keep_fraction, penal, rmin, load as [dof_index, value], loads as [[i,j,k,axis,value]], fixed_dofs, fixed_nodes, and keep_out/keep_in half-open boxes. The only gaps are that tol and max_iter are not explicitly described, but defaults and context make them inferable.

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 names a specific verb and resource: 'Minimum-compliance topology optimization (in-house SIMP; NO external solver)' and clearly explains the asynchronous submit/poll pattern. It distinguishes itself from siblings such as topology_to_solid (the downstream post-processing step) and optimize_submit, optics_lens_optimize, etc.

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 provides clear usage context: it is asynchronous, returns immediately, and must be polled via job_result, with a follow-on workflow of topology_to_solid, mass_properties, and interference_check. It does not explicitly contrast itself against alternative optimization tools, but the 'in-house SIMP; NO external solver' scope and 2-D/3-D domain make the intended use clear.

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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