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netcafe-tables

by com.ainetcafe

Messy CSV → tidy CSV, with a report of every change

clean_table
Read-onlyIdempotent

Tidies a spreadsheet export: removes duplicate rows, trims whitespace (half-width and full-width — Chinese exports are full of 　), unifies the half-dozen ways a cell can say "empty" (NA / null / - / 无), drops empty rows and columns, and can split one column into several. Returns the cleaned CSV plus exactly what changed: rows in, rows out, duplicates removed, cells trimmed per column. It can also transpose rows/columns and unpivot a wide table into a long one. The row arithmetic is verified in code — if in − removed ≠ out, the response says so instead of handing back a table nobody can check. Use when a CSV came out of Excel or an export and needs cleaning before analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opsNoComma-separated, default "dedupe,trim,drop_empty,unify_blank". Also available: split_column, transpose (swap rows/columns), wide_to_long (unpivot a wide table into the long format analysis tools expect).
urlNoLink to the CSV. Provide this or text.
keepNoFor wide_to_long: comma-separated id columns to keep as-is. Defaults to the first column.
textNoThe CSV content itself. Provide this or url.
split_byNoSeparator to split on, default a single space.
split_columnNoColumn name to split (requires ops to include split_column).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false; the description adds valuable context: handles full-width whitespace, unifies blank representations, splits columns, and verifies row arithmetic ('if in − removed ≠ out, the response says so'). This goes beyond what structured annotations provide.

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 dense paragraph (~100 words) with no filler. It front-loads the core purpose and packs each sentence with operational detail, making it efficient and well-structured.

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?

With 6 optional parameters and an output schema, the description sufficiently covers the tool's behavior: what it cleans, how it reports changes, usage context, and available operations. It doesn't leave major gaps for an agent to misuse the tool.

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?

Input schema covers 100% of parameters, so baseline 3. The description adds meaning beyond schema by explaining the ops options (e.g., 'transpose (swap rows/columns)', 'wide_to_long (unpivot...)') and the default for keep. This is helpful context not present in the schema.

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 uses a specific verb 'Tidies' plus resource 'spreadsheet export' and enumerates concrete operations (dedupe, trim, drop empty, unify blank), distinguishing it from sibling converters like csv_to_json. The phrase 'with a report of every change' further clarifies its unique function.

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

Usage Guidelines4/5

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

Provides clear when-to-use guidance: 'Use when a CSV came out of Excel or an export and needs cleaning before analysis.' It doesn't explicitly name alternatives or exclusions, but the context is sufficient to differentiate from sibling tools like csv_to_md_table.

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

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct functions (conversions, cleaning, xlsx I/O, reconciliation), but diff_tables, reconcile_ledger, and match_transactions all involve comparing or matching records, which could cause initial confusion. However, each has a specific use case—generic column diff, amount-focused reconciliation, and keyless fuzzy matching—and the descriptions provide enough detail to disambiguate them.

Naming Consistency4/5

The conversion tools follow a consistent 'csv_to_*' or 'json_to_csv' pattern, while operation tools use a verb_noun style (e.g., clean_table, merge_tables, reconcile_ledger). This dual pattern is predictable by function type, but 'what_can_you_do' breaks convention as a question-like meta-tool, so the naming is mostly consistent with a minor deviation.

Tool Count5/5

With 15 tools, the server sits at the upper edge of the well-scoped range, but each tool earns its place in the CSV/spreadsheet domain—covering conversions, cleaning, merging, diffing, reconciliation, matching, and Excel I/O. The count feels appropriate for the server's broad yet focused scope.

Completeness5/5

The toolset covers the full lifecycle of table manipulation: reading (read_xlsx), encoding repair, cleaning and transforming (clean_table), merging (merge_tables), comparing (diff_tables, reconcile_ledger), matching without keys (match_transactions), entity deduplication, and output to various formats (JSON, MD, chart, QBO, XLSX). No obvious gaps are evident for common tasks.

Resources