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ZeroWidth Caliper

Read a Caliper dataset (items paged)

caliper_datasets_get
Read-only

One dataset with a page of its items — read this BEFORE editing items (caliper_datasets_update_item needs the item id) and before extending coverage, so you don't add cases that already exist. Items come limit at a time (default 25) from offset; total is the full count. Long fields are cut at ~800 characters with a truncation marker. Get the datasetId from caliper_datasets_list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoItems per page, 1-100. Default 25.
offsetNoItems to skip. Default 0.
datasetIdYesDataset id, from caliper_datasets_list.
workspaceNoWorkspace slug. Personal tokens with no default workspace MUST pass this; tokens with a default can override per call. Ignored for workspace API keys.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, so safety is covered. The description still adds real behavioral context beyond them: page size default (25) via limit/offset, that total is the full count not the page, and that long fields are truncated at ~800 chars with a marker.

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?

Front-loaded with the core operation and the read-before-write guidance; every clause carries distinct information (dependency, paging, truncation, id source) with no filler.

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?

No output schema exists, so the description must cover return shape, and it does: one dataset plus a paged item list, total count, and truncation behavior. Combined with annotations and full schema coverage, nothing an agent needs to call it correctly is missing.

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 coverage is 100%, so the baseline is 3 and the schema already documents all four params. The description goes a bit further by framing limit/offset as the paging mechanism and stating the source of datasetId (caliper_datasets_list), tying parameters to workflow rather than restating types.

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?

States a specific verb (read) and resource (a Caliper dataset) and adds the scope detail 'with a page of its items', which separates it from caliper_datasets_list (no items) and the item-mutating siblings. An agent can identify the tool without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says to read this BEFORE editing items and BEFORE extending coverage, and names the dependency (caliper_datasets_update_item needs the item id) plus a preventive reason (avoid adding duplicate cases). When-to-use and the alternative are both spelled out.

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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