Skip to main content
Glama

analyze_game

Analyze a complete standard-chess PGN with adaptive Stockfish searches to score moves, flag critical positions, and support whole-game review.

Instructions

Analyze a complete standard-chess PGN with adaptive Stockfish searches. Scores use White's perspective; nodes is the configured per-position budget.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pgnYes
sideNoboth
multipvNo
initial_nodesNo
critical_nodesNo
critical_loss_cpNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
movesYes
engineYes
resultYes
headersYes
initial_fenYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that scores use White's perspective and that nodes is a per-position budget, adding useful behavioral context. However, it omits key traits like expected runtime (likely long-running due to Stockfish), resource consumption, whether it blocks, or how to retrieve results—critical for an analysis tool.

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?

Two concise sentences with no waste, and the core purpose is front-loaded. The second sentence efficiently clarifies two important semantics.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 6 parameters with no schema descriptions, no annotations, and takes a full PGN—a complex operation. The description is far too brief, omitting parameter details, behavioral expectations (runtime, blocking), and distinctions from similar analysis tools. An output schema exists, so return values needn't be explained, but significant gaps remain.

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. It explains 'nodes' (initial_nodes/critical_nodes) and scoring perspective, but leaves multipv, side, and critical_loss_cp unexplained. With 6 parameters and 0% coverage, the description falls well short of providing needed semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource ('Analyze a complete standard-chess PGN'), which is clear. However, it provides no differentiation from siblings like analyze_position, analyze_positions, or review_game, which likely overlap in scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this tool versus alternatives such as analyze_position or evaluate_position. The phrase 'adaptive Stockfish searches' hints at a specific mode but doesn't state prerequisites or exclusions.

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