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thermal_transient_submit

Submit asynchronous transient thermal FEM jobs via Elmer for analytic slabs, FreeCAD solids, or prepared cases; poll for temperatures.

Instructions

Transient thermal FEM via Elmer, asynchronous. Requires ElmerSolver (apt elmerfem-csc / conda); when absent this returns {ok:false, reason, install} rather than raising. Three modes:

  • Build the analytic-slab case (no solver case prep needed): pass the plane-wall transient — half_thickness_mm, h_conv (W/m²K), duration_s, and either k+rho+cp (SI) or a material name, with optional t_initial_c / t_ambient_c and mesh/step counts n_elements / n_steps. The handler writes the 1-D conduction case (symmetry at the centre, convection at the surface), runs ElmerSolver, and returns the centre/surface temperatures — the same plane-wall BVP thermal_transient_1d solves analytically, so the two are directly comparable (the kickoff's relative gate).

  • Solve a real FreeCAD solid — the geometry bridge: pass a body handle plus convection_faces (1-based indices into the solid's faces; those faces get the h_conv/t_ambient_c convective BC, every other face is adiabatic), the physics (h_conv, duration_s, k+rho+cp or material), and an optional char_length_mm Gmsh element size and element_order ('1st'|'2nd'). The solid is Gmsh-meshed and solved as a true 3-D body (ElmerGrid + ElmerSolver); the result's {t_max_c, t_min_c} are the interior/convective-surface temperatures (for a slab-like body, directly gateable against thermal_transient_1d). Prefer element_order='2nd' for a sharp transient — quadratic tets resolve the wall gradient accurately even on a coarse mesh.

  • Run a prepared case_dir containing its own .sif + mesh.

Returns the degradation dict, or {job_id, status, cache_hit}; poll job_result for {ok, returncode, solver, case_dir, stdout_tail} plus, for the slab case, {t_center_c, t_surface_c, n_steps_written}, for a body {t_max_c, t_min_c, nodes, tets} (or {scalars_final} for a prepared case).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNo
cpNo
rhoNo
sifNocase.sif
bodyNo
h_convNo
n_stepsNo
case_dirNo
materialNo
duration_sNo
n_elementsNo
t_ambient_cNo
t_initial_cNo
element_orderNo
char_length_mmNo
convection_facesNo
half_thickness_mmNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the async job model (returns {job_id,...}, poll job_result), the graceful degradation dict {ok:false, reason, install} when ElmerSolver is absent, and exact return payloads per mode. It doesn't state estimated solve time, resource limits, or cache_hit semantics.

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

Conciseness3/5

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

Front-loaded with the key async/degradation facts and cleanly structured with a three-mode list, but it is very long and repeats physics-parameter names and return details in each mode. The density is justified by the 17-param complexity, yet some sentences could be tightened.

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 17-parameter, no-annotation, no-output-schema async tool, the description covers invocation modes, degradation behavior, and exact per-mode return fields — everything an agent needs to call and interpret it 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 coverage is 0% across 17 undocumented parameters, so the description must compensate — and it explains the role of nearly every mode-specific parameter (h_conv, k/rho/cp or material, convection_faces as 1-based face indices, char_length_mm, element_order, sif, case_dir). It leaves a few defaults (t_initial_c/t_ambient_c, n_elements, n_steps) to inference, so not a full 5.

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 (submit/solve), resource (transient thermal FEM via Elmer), and explicitly enumerates three distinct modes, including the geometry bridge and the prepared case_dir path. It distinguishes itself from sibling thermal_transient_1d by explaining the analytic-comparability relationship rather than just restating the name.

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 clearly states the three modes and what inputs select each one (slab params, body+convection_faces, or case_dir), and routes to thermal_transient_1d for comparison. It does not explicitly say when NOT to use this vs. other solvers (e.g., cht_channel_submit, fem_modal) or the tradeoffs between modes beyond a mesh-order tip.

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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