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Soham-Donode

data-analysis-agent

by Soham-Donode

save_dataset

Persist an in-memory dataset to a specified file path under data/outputs, allowing cleaned or analyzed data to be stored and reused.

Instructions

Save in-memory dataset to data/outputs/ directory (e.g. 'cleaned_sales.csv').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
formatNo
session_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing side effects. It states that saving writes to data/outputs/, but does not disclose overwrite behavior, directory creation, whether the path must include an extension, session validity requirements, or any other side effects of the write operation.

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 one compact, front-loaded sentence with no wasted words. The example filename is useful and placed naturally, making the intended argument value immediately understandable.

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

Completeness2/5

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

For a tool with three parameters, no annotations, and 0% schema description coverage, the description is incomplete. It tells the agent what saving does and where files go, but omits session_id semantics, format handling, and any guidance on how this relates to sibling session/dataset tools, so an agent cannot reliably call it without further inference.

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

Parameters2/5

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 clarifies the path parameter somewhat through the example 'cleaned_sales.csv' and the output directory, but it does not explain the required session_id parameter or the optional format parameter, leaving critical invocation details undocumented.

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 clear verb ('Save'), resource ('in-memory dataset'), and destination ('data/outputs/ directory'), with an illustrative filename example. It is readily distinguishable from sibling tools like load_dataset and restore_session because it names the persistence action explicitly.

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?

The description implies the tool is used when the agent wants to persist the current in-memory dataset after transformations. However, it does not explicitly say when to prefer it over alternatives such as restore_session or when not to use it, so usage guidance is only implicit.

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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