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lichman0405

raspa-mcp

by lichman0405

parse_msd_output

Compute self- or collective-diffusion coefficients by parsing RASPA2 MSD output files from MD simulations.

Instructions

Parse RASPA2 MSD files and compute self- or collective-diffusion coefficients (2-1/3-1/3-2).

Requires a completed NVT-MD or NPT-MD simulation with 'ComputeMSD yes' set. RASPA2 writes MSDSelf_.dat (self-diffusion) and MSDCollective_.dat.

The Einstein relation D = MSD(t) / 6t is fitted to the linear regime (latter 50% of trajectory). Result is given in A²/ps and m²/s.

Typical self-diffusivities in MOFs:

  • Fast gas (H2, He): 10⁻⁸ – 10⁻⁷ m²/s

  • CO2, CH4 in wide pores: 10⁻⁹ – 10⁻⁸ m²/s

  • Slow diffusers (large MOF pores, tight channels): < 10⁻¹¹ m²/s

Args: output_dir: Path to RASPA2 Output directory. molecule: Optional filter by molecule name (e.g. "CO2"). diffusion_type: "self" (MSDSelf) or "collective" (MSDCollective).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
moleculeNo
output_dirYes
diffusion_typeNoself
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the calculation method (Einstein relation, linear regime, latter 50% of trajectory), units (A²/ps and m²/s), and typical expected values. It does not mention error handling or missing files, but provides substantial behavioral context.

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 somewhat long but well-structured, starting with purpose, then prerequisites, method, expected output, and args. Every sentence adds value; typical diffusivity ranges are useful for sanity checks. It is appropriately sized but could be slightly trimmed without losing key information.

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?

There is no output schema, so the description must explain return values. It states 'Result is given in A²/ps and m²/s' and mentions diffusion coefficients, which is sufficient. However, it does not describe the exact return structure (e.g., dictionary, list) or whether it returns values for all molecules or only filtered ones, leaving some ambiguity.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description compensates fully with an 'Args' section that explains output_dir, molecule, and diffusion_type. It clarifies the meaning of 'self' and 'collective' and gives an example molecule filter ('CO2'). This goes beyond the minimal schema information.

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 begins with a specific verb and resource: 'Parse RASPA2 MSD files and compute self- or collective-diffusion coefficients'. It clearly identifies the tool's function, distinguishes it from generic parse tools like parse_raspa_output, and specifies the types of diffusion coefficients.

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 states prerequisites: 'Requires a completed NVT-MD or NPT-MD simulation with ComputeMSD yes set.' It also explains the file naming conventions (MSDSelf_<mol>.dat and MSDCollective_<mol>.dat). However, it does not explicitly mention when not to use this tool or name alternative tools, but the context is 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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