csv-mcp

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update_rows

Update rows in a CSV file that match specified filters, setting new values for chosen columns, with a dry-run preview before applying changes.

Instructions

Update filtered rows, returning a bounded change preview before optional output.

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": {
      "path": "<path>",
      "match": "<match>",
      "set": "<set>"
    },
    "name": "update_rows"
  }
}

Input Schema

Name	Required	Default
`set`	Yes
`path`	Yes
`match`	Yes
`dry_run`	No
`options`	No
`overwrite`	No
`output_file`	No
`column_types`	No
`spreadsheet_formula_policy`	No	escape

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Jul 29, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions a 'bounded change preview', which hints at the dry_run parameter, but omits disclosure of destructive nature, authentication needs, error handling, or impact on data. The preview behavior is the only behavioral detail.

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 a single, front-loaded sentence with zero waste. It communicates the core action and a key behavior efficiently.

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?

Given the tool's complexity (9 parameters, nested filters and CSV options, output schema), the description is far too sparse. It does not explain how to use the output, handle CSV options, or interpret the preview. The agent would need additional context to invoke the tool correctly.

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

Parameters1/5

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 by explaining parameters. It does not mention any of the 9 parameters (path, match, set, etc.), leaving the agent without guidance on their meaning or usage. The description adds no value beyond what the schema structure already conveys.

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 clearly states the action ('Update'), the resource ('filtered rows'), and a distinctive behavioral promise ('returning a bounded change preview before optional output'). This distinguishes it from sibling tools like delete_rows or append_rows.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives, such as delete_rows, append_rows, or query_csv. It does not mention prerequisites, context, or limitations.

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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