Chessigma

Calculate Elo

calculate_elo

Read-onlyIdempotent

Estimate a player's new Elo rating after a single game with the Elo formula. Pure arithmetic, no chess engine. The system field picks a K-factor default for FIDE, Chess.com or Lichess, but the result is an Elo estimate: Chess.com and Lichess use Glicko ratings, so their real rating changes differ.

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": {
      "yourRating": "<yourRating>",
      "opponentRating": "<opponentRating>",
      "result": "<result>"
    },
    "name": "calculate_elo"
  }
}

Input Schema

Name	Required	Default
`result`	Yes
`system`	No	fide
`kFactor`	No
`yourRating`	Yes
`opponentRating`	Yes

Output Schema

Name	Required	Description	Default
`change`	Yes
`result`	Yes
`system`	Yes
`kFactor`	Yes
`newRating`	Yes
`yourRating`	Yes
`calculatorUrl`	Yes
`expectedScore`	Yes
`opponentRating`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real value beyond them: it discloses that this is pure arithmetic (not an engine), that 'system' selects a K-factor default, and that Chess.com/Lichess use Glicko so real rating changes will differ from this estimate.

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 tight sentences, front-loaded with the core action and followed immediately by the two things an agent most needs: no engine involved, and the Glicko caveat. No filler.

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?

With an output schema present, return values need no explanation, and annotations cover the safety profile. The description supplies the arithmetic scope and the accuracy caveat, though it could do more on the un-annotated numeric parameters.

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 0%, so the description must compensate. It explains the non-obvious 'system' parameter's role in picking a K-factor default and acknowledges the result (win/draw/loss) context, but says nothing about yourRating, opponentRating, or the kFactor override parameter, leaving several fields undocumented.

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?

States a specific verb and resource ('Estimate a player's new Elo rating after a single game') and explicitly rules out engine work ('Pure arithmetic, no chess engine'), which cleanly separates it from siblings like analyze_game and analyze_position. An agent can identify it without opening the schema.

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 (single-game Elo estimation, not full analysis) and warns where the estimate is unreliable, but never explicitly says when to prefer this over analysis tools or what prerequisites exist. Usage is inferable rather than stated.

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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