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NoCodeCSV

Ask a question about a CSV

analyze_csv

Ask a question about CSV data in plain English and get a written answer back (totals, trends, outliers, comparisons, a recommended chart). The CSV text is analysed and discarded; nothing is stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesThe question to answer, in plain English.
csvContentYesThe raw CSV text to analyse, including the header row.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
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 does disclose a key behavioral trait: the CSV text is analysed and discarded and nothing is stored, which tells the agent this is a stateless, non-persisting operation. It does not cover size limits, error modes, or latency, so it is good but not comprehensive.

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?

Two sentences, front-loaded with the core action, with the data-retention caveat immediately following. Every clause earns its place and nothing is padded.

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?

There is no output schema, and the description does name the return shape (a written answer covering totals/trends/outliers/comparisons/chart), which is the key thing the agent needs. It stops short of stating input size limits or failure behavior, but for a two-parameter tool it is close to complete.

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 description coverage is 100%, so both parameters are already documented in the schema and the baseline is 3. The description reinforces that the question is plain English and that csvContent must contain a header row, but adds no parsing rules, size constraints, or format details beyond the 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 verb+resource (ask a question about CSV data, get a written answer) and even enumerates the answer types (totals, trends, outliers, comparisons, chart recommendation), so the tool's function is unambiguous. It does not, however, differentiate itself from the sibling csv_profile, leaving the agent to infer the split between profiling and question-answering.

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: ask a plain-English question when you want an analytical answer. There is no explicit when-to-use vs when-not guidance and the only sibling, csv_profile, is never mentioned, so the agent must guess which of the two to pick.

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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