Skip to main content
Glama

cricket_player_career

Read-only

Career aggregate statistics for a player (men's and women's cricket) from Cricsheet ball-by-ball archives: innings, runs, strike rate, average, high score, wickets, economy — per format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesplayer name, e.g. 'Rachin Ravindra'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered and nothing is contradicted. The description adds valuable context beyond annotations: data provenance (Cricsheet ball-by-ball archives), gender coverage (men's and women's), and per-format aggregation behavior — all non-obvious traits the agent would not know otherwise.

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?

A single front-loaded sentence: purpose leads, followed by source, stat list, and the per-format qualifier. There is no filler, no repetition of schema content, and every clause adds information an agent needs to select and invoke the tool.

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 one-parameter read-only tool with no output schema, the description covers scope, data source, returned fields, and per-format grouping — enough to form an accurate mental model of the result. Minor gaps are the lack of explicit return-structure detail and name-matching behavior for unknown or ambiguous players, but these are unlikely to block correct invocation.

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 100% — the single `name` parameter already has a description with a concrete example ('Rachin Ravindra'). The tool description adds no parameter-specific meaning beyond what the schema provides, so the baseline 3 applies.

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 names a precise scope — 'Career aggregate statistics for a player' — with a specific resource (player), a concrete stat list (innings, runs, strike rate, average, high score, wickets, economy), and per-format grouping. The single-player career framing differentiates it from siblings like cricket_head_to_head (two players), cricket_leaders (rankings), and cricket_phase_stats without needing to inspect their schemas.

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?

When to use the tool is implied by the purpose statement — when an agent needs career aggregates for a single player — but no explicit when/when-not guidance or alternative tools are named. An agent must infer that head-to-head comparisons belong to cricket_head_to_head or that phase-level breakdowns belong to cricket_phase_stats.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.