castle-clash-mcp

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combat_effects

Get Castle Clash combat effect types and status mechanics. No argument returns counts across all 59 buffer types; specify a buffer_type for its mechanic, state bit, and hard CC/immunity mapping.

Instructions

The effect-engine taxonomy recovered from the binary (docs/GAME_MATH.md sec 9). With no argument: counts by handler category across the 59 in-use BufferTypes. With a buffer_type: that type's mechanic + state bit. Status bits map to crowd control (type 39 = hard CC / halt; type 3 = immunity/cleanse).

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": "combat_effects"
  }
}

Input Schema

Name	Required	Description	Default
`buffer_type`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 5, 2026

TDQS

A4.5/5.0

Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure. It explains what data is returned for each input mode and adds interpretive context (status bits mapping to crowd control, type 39 = hard CC, type 3 = immunity/cleanse). It doesn't explicitly state read-only behavior, but the reference-taxonomy language strongly implies no mutation.

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?

Three dense sentences deliver all essential information with no filler. The purpose is front-loaded, followed by mode-specific behavior and useful encoding examples. Every sentence earns its place.

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 tool with one optional parameter, the description covers both modes, mentions the exact count (59 BufferTypes), and explains the semantic mapping of status bits. It doesn't specify the output schema, but no output schema is provided and the return shape is reasonably inferable from the content described.

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?

The schema only shows buffer_type as an integer/nullable field, so the description must compensate for the low coverage. It does so thoroughly: it explains that supplying buffer_type returns that type's mechanic and state bit, and gives concrete value mappings (39, 3) that help the agent use the parameter meaningfully.

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 resource (effect-engine taxonomy) and the two distinct actions: aggregating counts by handler category or retrieving a specific buffer type's mechanic and state bit. It differentiates itself from siblings like combat_math or simulate_fight by describing a unique reference taxonomy, not calculations or simulation.

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?

It gives explicit usage context for both invocation modes: no argument returns category counts, buffer_type returns specific mechanics. It doesn't name alternatives, but it provides enough conditionality for an agent to decide which call to make in a given scenario.

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