Krusgraph

Show a few rows of a table

sample_rows

Read-only

Returns the first rows of one table so that a column's meaning can be checked. Requires workspace, source and table. Returns JSON {table, columns, rows, personal_data}; long text is shortened, and columns that look like personal data are masked unless show_personal_data=true. Read-only. Errors: {error, kind, hint}.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "workspace": "<workspace>",
      "source": "<source>",
      "table": "<table>"
    },
    "name": "sample_rows"
  }
}

Input Schema

Name	Required	Description	Default
`n`	No	Number of rows, 1–20. Default 10. Example: 5.
`table`	Yes	Table to read, by name. Example: "orders".
`schema`	No	Schema in the source. Default "dbo".	dbo
`source`	Yes	Lakehouse, warehouse or SQL database, name or id.
`workspace`	Yes	Fabric workspace, name or id.
`show_personal_data`	No	true includes columns named like personal data; false (default) masks or omits them.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed6 schema fields changedOct 29, 2026

addedInput schema / properties / n / description

Added value: +"Number of rows, 1–20. Default 10. Example: 5."

addedInput schema / properties / schema / description

Added value: +"Schema in the source. Default \"dbo\"."

addedInput schema / properties / show_personal_data / description

Added value: +"true includes columns named like personal data; false (default) masks or omits them."

addedInput schema / properties / source / description

Added value: +"Lakehouse, warehouse or SQL database, name or id."

addedInput schema / properties / table / description

Added value: +"Table to read, by name. Example: \"orders\"."

addedInput schema / properties / workspace / description
```
Added value: +"Fabric workspace, name or id."
```

First observedOct 27, 2026

TDQS

A4.1/5.0

Behavior5/5

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

Goes well beyond the read-only/destructive annotations: it discloses the return envelope {table, columns, rows, personal_data}, truncation of long text, PII masking keyed to show_personal_data, and the error shape {error, kind, hint}. An agent knows exactly what it gets back and why values may appear redacted before it calls.

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?

Three compact sentences, front-loaded with purpose then contract then error shape; no filler and no repetition of the title. Every clause (masking, truncation, error envelope) carries usable information.

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 6-parameter preview tool with an output schema, annotations, and full schema coverage, the description supplies the remaining unknowns — masking rules, text truncation, and failure shape. Nothing an agent needs in order to call this correctly is missing.

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

Parameters3/5

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

Schema coverage is 100% and every parameter already carries a description with defaults and examples, so the baseline is 3. The description reinforces the show_personal_data default behavior and the three required fields, but adds no syntax or constraints beyond what the schema states.

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?

States a specific verb and resource ("Returns the first rows of one table") plus the reason for doing so ("so that a column's meaning can be checked"), which separates it from metadata tools like list_tables or analyze_schema by intent. It never names a sibling alternative explicitly, so the differentiation is inferential rather than stated.

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 use case (inspecting column meaning / previewing data) is implied by the purpose sentence, and required inputs are listed, but there is no explicit when-to-use-vs-alternative guidance, no prerequisite or permission framing beyond "Requires workspace, source and table", and no exclusions.

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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