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edit_datasource

Update a datasource's metadata by providing its name and a new description, ensuring the semantic layer reflects current information.

Instructions

Update a datasource's metadata.

Args: name: Datasource name to update. description: New description for the datasource.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.10.0

TDQS

B3.4/5.0
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 behavioral disclosure. It only says 'Update' and does not explain what happens when 'description' is omitted (leave unchanged vs clear to null), whether the datasource must already exist, or what side effects occur. This ambiguity is significant because the schema gives 'description' a default of null.

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 short, front-loaded with the purpose, and includes only a compact Args list that adds necessary parameter semantics. There is no filler or redundancy.

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

Completeness3/5

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

For a simple two-parameter tool with an output schema, the description is mostly adequate. However, it lacks guidance on optional parameter behavior, error cases, and when to prefer this tool over related datasource/model tools, leaving minor but real gaps for an agent deciding how to invoke it.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must define the parameters. It does add meaning: 'Datasource name to update' clarifies that 'name' is an identifier, and 'New description for the datasource' clarifies the intended value. It stops short of explaining null/omission semantics, but still compensates for the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Update') on a resource ('a datasource's metadata') and the Args section clarifies that 'name' identifies the target while 'description' supplies the new value. It is clear enough to distinguish from create/delete/describe datasource tools, though 'metadata' is somewhat broad.

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: use this when you want to update an existing datasource's metadata. However, there is no explicit when-to-use vs alternatives, no mention of when not to use it, and no comparison to sibling tools like edit_model or delete_datasource.

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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