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data_sort

Sort lines numerically or naturally, ascending or descending. Pure CPU, instant.

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": {
      "text": "<text>"
    },
    "name": "data_sort"
  }
}

Input Schema

NameRequiredDescriptionDefault
descNoDescending
textYesLines to sort
numericNoNumeric sort

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed4 schema fields changed
    • addedInput schema / properties / desc
      Added value: +{
      +  "description": "Descending",
      +  "type": "boolean"
      +}
    • addedInput schema / properties / numeric
      Added value: +{
      +  "description": "Numeric sort",
      +  "type": "boolean"
      +}
    • addedInput schema / properties / text
      Added value: +{
      +  "description": "Lines to sort",
      +  "type": "string"
      +}
    • addedInput schema / required
      Added value: +[
      +  "text"
      +]
  4. Added

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations at all, the description carries the full burden, and 'Pure CPU, instant' usefully signals local execution, no network calls, and no rate limits. It does not disclose whether the sort is stable, how ties or non-numeric lines behave in numeric mode, or whether the output is the sorted block of text — gaps that matter for a text transformation with no annotation coverage.

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?

Two short sentences, front-loaded with the operation and its options, with zero filler. The trailing 'Pure CPU, instant' is terse and informative, though it is closer to a performance note than core definition.

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?

For a simple three-parameter, single-purpose text transformer with full schema coverage and no annotations, the description covers the essential operation and modes. It could state the return value (sorted lines as text) since there is no output schema, which is the only notable omission.

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 explains 'text', 'numeric', and 'desc'. The description adds a small amount of extra meaning by introducing the 'natural' sort mode, which the boolean 'numeric' flag alone does not convey, but it does not clarify the default behavior or how natural ordering differs from lexicographic.

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 concrete verb and resource ('Sort lines') plus the two sort modes and both directions, so the agent immediately knows the operation. It does not name or contrast itself against nearby data utilities such as data_dedupe or data_filter, which is the only thing keeping it from a 5.

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 by the name and the mention of numeric/natural modes, but there is no explicit when-to-use or when-not-to-use guidance. The agent must infer that this is the choice over data_filter/data_dedupe when the goal is ordering rather than filtering or deduplication.

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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