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memo

memo

by ngabzar02
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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versions

Retrieve the complete release history for a library using its library ID. Checks npm or PyPI for past and current releases when available, providing a chronological list of all known releases.

Instructions

List known versions for a library (history dari npm/PyPI bila tersedia).

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": {
      "library_id": "<library_id>"
    },
    "name": "versions"
  }
}

Input Schema

NameRequiredDescriptionDefault
library_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the transparency burden. It discloses that data comes from npm/PyPI and may be unavailable, which is useful. However, it does not mention behavior for unknown library_id or provide details beyond the output schema, leaving some gaps.

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 sentence, front-loaded with the action and resource. It contains no unnecessary words, making it highly concise and well-structured.

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?

For a simple one-parameter list tool with an output schema, the description covers the core action and a data availability caveat. However, it lacks explicit usage guidance and parameter details, and with no annotations, the overall context remains somewhat incomplete.

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

Parameters2/5

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. 'for a library' indicates library_id identifies a library, but it does not specify the format, range, or how to obtain the ID (e.g., via resolve_library_id). This adds minimal semantic value.

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 'List known versions for a library' uses a specific verb and resource, and further specifies the data source (npm/PyPI). It clearly distinguishes from sibling tools get_docs and resolve_library_id, which serve different purposes.

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?

The phrase 'bila tersedia' (if available) implies when the tool might return no results, but it does not explicitly compare with alternatives or state when to prefer this tool over siblings. Usage context is only partially implied.

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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