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femm_mesh_arrays

Exports solved mesh nodes, elements, and physics fields (B, A, V, D, T, F, J) to NPZ/CSV in the session work dir, returning path, shape, and column min/max/mean stats.

Instructions

Dump the solution mesh and fields to a file in the session work dir and return the path, shape and min/max/mean per column (never the raw arrays). which: all, or a comma list of nodes, elements, and per physics: magnetics b (B1,B2 per element), a (A per element); electrostatics v (per node), d; heatflow t (per node), f; currentflow v (per node), j. Element rows are n1,n2,n3 (node indices), cx, cy, area, group. fmt: npz (numpy) or csv. Load with numpy.load(path).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fmtNonpz
nameNo
whichNoall
sessionNomain

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
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 that raw arrays are never returned, the returned summary (path, shape, min/max/mean per column), the file location (session work dir), and the file format. It omits any failure/overwrite/permission behavior, keeping it from a 5.

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?

Front-loaded with the primary action and the key constraint (never raw arrays), followed by the 'which' vocabulary and format details. Dense and information-bearing, though somewhat run-on with the physics enumeration.

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

Completeness4/5

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

No output schema and no annotations, so the description must supply return semantics, which it does (summary stats + load path). It also describes the element row layout. The main gap is the unexplained 'name' and 'session' parameters.

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

Parameters3/5

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 richly documents 'which' (all vs comma list, per-physics quantity names) and 'fmt' (npz/csv), but leaves 'name' and 'session' unexplained even though 'session work dir' hints at the session concept. Partial compensation for a 4-param tool.

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?

States a specific verb+resource: dumps the solution mesh and fields to a file and returns path/shape/min-max-mean. This clearly separates it from siblings like femm_export_dxf, femm_save_bitmap, and femm_field_stats, and names the concrete payload (node/element rows, physics quantities).

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

Usage Guidelines3/5

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

Usage is implied by 'Load with numpy.load(path)' and by the detailed 'which' enumeration, signaling a bulk-array export for Python post-processing. However, it never states when to choose this over siblings such as femm_point_values, femm_field_stats, or femm_block_integral, nor any exclusions.

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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