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timps-swarm

timps-swarm

by Sandeeprdy1729
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

timps_docstring_generator

Generate production-quality docstrings for raw source code in Google, Sphinx, NumPy, JSDoc, or Doxygen format without changing logic.

Instructions

Read raw source code and insert production-quality docstrings in your preferred format (Google, Sphinx, NumPy, JSDoc, Doxygen). Logic is never changed — only documentation is added.

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": {
      "source_code": "<source_code>"
    },
    "name": "timps_docstring_generator"
  }
}

Input Schema

NameRequiredDescriptionDefault
languageNoProgramming languagepython
doc_styleNo'google'|'sphinx'|'numpy'|'jsdoc'|'doxygen'google
source_codeYesSource code to document

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.2.1

TDQS

A3.8/5.0
Behavior3/5

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

The description discloses a key behavioral guarantee: 'Logic is never changed — only documentation is added.' This is valuable context. However, with no annotations, the description carries the full burden; it does not mention whether the tool modifies files in place, returns output, or handles errors, leaving some behavioral aspects ambiguous.

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 two sentences, concise, and front-loaded with the main action. Every sentence adds value: the first defines the operation and formats, the second reassures about behavioral safety. No wasted words.

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?

The description is sufficient for a straightforward transformation tool with fully documented parameters. However, since there is no output schema, it would be helpful to explicitly state the return value (e.g., updated source code as a string) to fully round out the context. Still, the implied output is clear from the action.

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 coverage is 100%, and the description adds a bit of context by naming specific docstring formats (Google, Sphinx, NumPy, JSDoc, Doxygen) that map to the doc_style parameter. However, it does not provide additional semantics beyond the schema for language or source_code beyond basic clarity.

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 the tool reads raw source code and inserts production-quality docstrings, with specific format options. It distinguishes itself from sibling tools by focusing solely on docstring generation, not testing, code writing, or analysis.

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 description implies usage (when you need to add docstrings to code) but does not explicitly state when to use it versus alternatives, nor does it provide exclusions or caveats. There is no mention of when not to use it, which would be helpful for a tool among many similar code-related agents.

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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