SymKit

Overview Schema Source Related Servers Discussions Admin

formula_categories

List available formula categories from local library or legacy sources like Wikidata and BioModels to organize mathematical formulas.

Instructions

List available formula categories.

    Get the categories currently present in the local formula library.

    Args:
        source: Data source
               - "local": Local YAML library (default)
               - "all": Local + legacy sources
               - "wikidata", "biomodels", "scipy": Legacy source only

    Returns:
        {
            "success": true,
            "categories": {
                "local": ["fluid_dynamics", "mechanics", "thermodynamics"],
                "wikidata": [...]
            }
        }

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "formula_categories"
  }
}

Input Schema

Name	Required	Description	Default
`source`	No		local

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jul 8, 2026

TDQS

A4.7/5.0

Behavior5/5

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

With no annotations, the description fully discloses behavior: it lists categories from specified sources, returns a structured JSON with success flag and category lists. It implies a read-only operation without side effects.

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 description is slightly lengthy due to complete parameter and return documentation, but it is well-structured with 'Args' and 'Returns' sections. Every sentence adds value, making it efficient for its completeness.

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?

The tool has only one parameter and an output schema-like return description. The description fully covers the tool's purpose, parameters, and return structure, leaving no gaps.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description provides extensive semantics for the 'source' parameter, explaining each allowed value ('local', 'all', 'wikidata', etc.) and their meanings, far exceeding 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 states 'List available formula categories' with a specific verb and resource. It clearly distinguishes from sibling tools by focusing on category listing, which is unique among many siblings.

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?

The description explains when to use different sources via the 'source' parameter, including defaults and options. However, it does not explicitly state when not to use this tool or mention alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.