axiomatic-mcp

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AxMeep_get_results

Retrieve results from a completed Meep job, including summarized arrays, inline PNG figures, and local file paths for loading with numpy. Check simulation status first to ensure completion.

Instructions

Fetch the exports of a completed Meep job. Check get_simulation_status first — calling this early reports that the job is still running, it does not wait. Each export is summarized (arrays as shape/dtype/min/max/mean, scalars exactly), PNG figures are returned inline as images, and every artifact is written to a local file whose path is returned so it can be loaded with numpy. Pickled objects are reported but never decoded.

Input Schema

TableJSON Schema

Name	Required	Description
`task_id`	Yes	The task_id returned by execute_code.
`output_dir`	No	Directory to write artifacts into; a per-task subdirectory is created inside it. Defaults to $AXIOMATIC_MEEP_OUTPUT_DIR if set, else the working directory. An absolute path is recommended.
`max_inline_images`	No	How many PNG figures to return inline as images (the rest are written to disk and referenced by path).

Output Schema

TableJSON Schema

Name	Required	Description
`error`	No
`exports`	No	Per export: kind, size_bytes, path and a one-line summary. Never the raw payload.
`success`	No
`task_id`	No
`error_type`	No
`output_dir`	No	Directory the artifacts were written to.
`status_code`	No
`failed_objects`	No
`console_output_path`	No
`console_output_excerpt`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.1.20Sep 15, 2026

TDQS

A4.7/5.0

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 it delivers: it discloses non-blocking early-call behavior, export summarization conventions, inline-image limits, local file writing, returned paths, and that pickled objects are never decoded. These are important behavioral traits beyond the schema.

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

Conciseness5/5

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

The description is compact, front-loaded with the core purpose, and every sentence adds a distinct piece of useful information. The long third sentence is structured with clear clauses and is not wasteful.

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 the output schema exists and all parameters are documented, the description covers the essential operational context: prerequisite status check, non-blocking behavior, output formatting, file persistence, and handling of unsupported artifacts. Nothing needed for correct invocation is missing.

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 100%, and each parameter already has a clear description covering defaults and meaning. The tool description adds behavioral context around outputs but not much parameter-level detail beyond what the input schema already provides.

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 states a specific verb ('Fetch') and resource ('exports of a completed Meep job'), making the tool's purpose immediately clear. It also distinguishes itself from the sibling get_simulation_status by framing this as the post-completion retrieval step.

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

Usage Guidelines5/5

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

It explicitly instructs the agent to check get_simulation_status first and warns that calling this tool early reports the job as still running rather than waiting. This gives clear when-to-use guidance and names the relevant alternative.

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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