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kks32

designsafe-mcp

by kks32

list_systems

Lists accessible Tapis systems with optional filtering by category and output format, returning IDs, hosts, and credential status.

Instructions

List Tapis systems you have access to.

Filters out internal and project-specific systems by default.

Args: category (str, optional): "hpc" for execution systems, "storage" for storage systems, "all" for everything, None for HPC + storage (default). output (str, optional): "df" for DataFrame (default), "list" for dicts.

Returns: DataFrame or List[Dict]: Systems with id, host, category, authn, credentials.

Example: >>> ds.systems.list() # HPC + storage >>> ds.systems.list("hpc") # HPC only with credential status >>> ds.systems.list("storage") # Storage only >>> ds.systems.list("all") # Everything including internal

[schema introspected from dapi 0.6.1 (systems.list); this tool is generated, not maintained by hand]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputNodf
categoryNo
Behavior4/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses the default filtering behavior, the 'all' option to override it, and the return format (DataFrame or dicts with specific fields). This adds meaningful context beyond just the tool name.

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 well-structured with clear sections for purpose, arguments, returns, and examples. It's slightly longer than necessary due to the meta-note about auto-generation, but every instructional sentence earns its place, and the examples are highly illustrative.

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 tool with two optional parameters, no annotations, and no output schema, the description thoroughly covers purpose, behavior, parameters, return format, and usage examples. Nothing important is missing for an agent to select and invoke this tool correctly.

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?

The schema has zero description coverage, so the description fully compensates. Both parameters ('category' and 'output') are explained in detail with accepted values and defaults, and examples demonstrate usage. This goes well beyond the schema's bare property definitions.

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 opens with 'List Tapis systems you have access to.' which is a specific verb+resource pairing that immediately clarifies the tool's function. It also distinguishes itself by noting the default filtering of internal and project-specific systems, setting it apart from generic system listing tools.

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 clearly explains the context for use (listing systems you have access to) and provides examples for each category option. It doesn't explicitly mention alternative tools or when not to use it, but the context is clear enough given the sibling tools are mostly unrelated to listing systems.

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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