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informatics-isi-edu

Deriva MCP Server

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delete_dataset_members

Remove records from a dataset's membership without deleting the underlying catalog records. Automatically increments the dataset's minor version for change tracking.

Instructions

Remove records from a dataset. Auto-increments minor version.

Removes the specified records from the dataset's membership. The records themselves are not deleted from the catalog, only their association with this dataset is removed.

Removing members automatically increments the dataset's minor version for change tracking.

Args: dataset_rid: The RID of the dataset to remove members from. member_rids: List of RIDs to remove (e.g., ["2-ABC", "2-DEF", "2-GHI"]).

Returns: JSON with status, removed_count, dataset_rid.

Example: delete_dataset_members("1-ABC", ["2-DEF", "2-GHI"]) -> removes 2 records from dataset

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataset_ridYes
member_ridsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden and discloses key behavioral traits: auto-increments minor version, records themselves are not deleted, and the return payload includes status, removed_count, and dataset_rid. This gives a solid understanding of side effects, though permissions or error behavior are not covered.

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 a summary, behavioral notes, Args, Returns, and Example. It loses a point because the minor version auto-increment is mentioned twice, which is redundant but not severely wasteful.

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?

For a two-parameter tool with no annotations and an output schema, the description covers the essential operation, side effects, and return format, plus an example. It omits edge cases and prerequisites, but given the simple scope, it is sufficiently complete for correct selection and invocation.

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%, so the description must compensate. It does so fully with a dedicated Args section that explains dataset_rid and member_rids clearly and provides an example of the expected list format. This leaves no ambiguity about parameter meaning.

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 the specific action 'Remove records from a dataset' and clarifies that only membership is removed, not the records themselves. This clearly distinguishes it from delete_dataset and positions it as the inverse of add_dataset_members.

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 provides clear context by explaining that records are not deleted from the catalog and that the operation only affects membership, which tells the agent when to use it. However, it does not explicitly name alternative tools or give 'use this instead' guidance, so it stops short of a 5.

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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