SmartTools

CSV to SQL converter

csv_to_sql

Turn CSV/TSV rows into SQL INSERT statements with standard double-quoted identifiers and escaped values. Runs on smart-tools.xyz.

Input Schema

TableJSON Schema

Name	Required	Description
`text`	Yes	CSV/TSV text to convert
`nulls`	No	Emit NULL for empty cells (default true)
`locale`	No	Language for the source_url link (default en)
`quote_all`	No	Quote every value, even numeric ones (default false)
`batch_size`	No	Rows per INSERT statement (default 50)
`has_header`	No	Use the first row as column names (default true); if false, columns are named col1, col2, …
`table_name`	No	Target table name (default my_table)

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It adds some behavioral detail ('standard double-quoted identifiers and escaped values') but does not disclose other important behaviors like the inclusion of a source_url link or how batch_size affects output. This is minimal transparency.

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 first sentence is informative and compact. The second sentence, 'Runs on smart-tools.xyz,' is filler that does not earn its place for an agent selecting a tool, slightly reducing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 7 parameters and no output schema, the description should clarify the output format more thoroughly (e.g., that it includes a source_url comment). It covers the core conversion but omits parameter interactions and output details, making it adequate but incomplete.

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 the schema already fully documents all 7 parameters. The description adds no parameter semantics beyond that, meeting the baseline of 3.

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 'Turn CSV/TSV rows into SQL INSERT statements' with specific output formatting details (double-quoted identifiers, escaped values), making it easy to distinguish from siblings like csv_to_json or data_converter.

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?

No explicit guidance on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or alternative tools; usage context is only implied by the purpose.

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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TDQS

B3.3/5.0

Disambiguation3/5

Most tools are clearly distinct, but there are notable overlaps. 'hash_generator' and 'file_hash' effectively do the same thing (SHA hashing of text), and several CSV/TSV converters (csv_to_json, csv_to_sql, table_to_csv, markdown_table) have similar input handling, though outputs differ. The sheer number of converters is clear, but these near-duplicates create some ambiguity.

Naming Consistency4/5

Names follow a generally consistent pattern: lowercase with underscores, often ending in 'converter', 'calculator', or 'generator'. A few names like 'base64', 'lorem_ipsum', and 'transliteration' deviate from the suffix pattern, but the naming style is uniform and predictable overall.

Tool Count2/5

With 73 tools, this server is far over the typical well-scoped range. While the broad utility-toolkit purpose might justify a larger set, 73 is unwieldy and pushes well into 'too many' territory, making it harder for an agent to select the right tool efficiently.

Completeness4/5

The server covers a remarkably wide range of common utilities: unit conversions, calculators, text transformations, development helpers (JSON, regex, JWT, subnet), and generators. Minor gaps exist (e.g., currency converter, time zone converter), but for a general-purpose toolkit, it is largely comprehensive.

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