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Crawlora MCP

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cricinfo_stats

Fetch cricket batting, bowling, fielding, and other stats from Cricinfo Statsguru. Returns normalized, bounded tables filtered by match class, team, player, ground, and more.

Instructions

Query Cricinfo Statsguru. Returns a bounded normalized Statsguru table. class must be one of 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 20, 21, 22, or 23; type must be one of batting, bowling, fielding, allround, fow, team, official, or aggregate; view may be innings, match, series, ground, host, opposition, year, or season.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostNoNumeric host-country identifier
teamNoNumeric Cricinfo team identifier
typeYesStatsguru statistic family
viewNoStatsguru table view
classYesStatsguru match-class. Allowed values: 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 20, 21, 22, 23
limitNoMaximum rows returned, from 1 to 100
groundNoNumeric ground identifier
playerNoNumeric Cricinfo player identifier
seasonNoSeason formatted as YYYY or YYYY/YY
orderbyNoStatsguru sort column
span_maxNoStatsguru ending date
span_minNoStatsguru starting date
oppositionNoNumeric opposition team identifier
orderby_descNoSort descending when true

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions a 'bounded normalized' return format; it does not cover whether output can be empty, how bounds behave, any rate limits, or what happens with invalid identifiers.

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 one compact paragraph that front-loads purpose before enumerations. It is efficient and contains no filler; the long list of enum values is justified because it carries information absent from the schema.

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?

This is a complex 14-parameter tool with no output schema and no annotations, so the description must carry more weight. It explains required enums but omits how optional filters interact, defaults, output shape, and whether numeric identifiers can be sourced from sibling tools.

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

Parameters4/5

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

Schema coverage is 100%, which sets a baseline of 3, but the description adds value by enumerating valid values for `type` and `view` that the schema does not list. This helps an agent choose parameter combinations without accessing external Statsguru knowledge.

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

Purpose4/5

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

The description clearly names the resource ('Cricinfo Statsguru') and the operation ('Query'), and states the output is a bounded normalized table. It does not explicitly contrast itself with sibling tools like cricinfo_squads, so it stops short of full sibling differentiation.

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?

No guidance is given about when to use this tool versus alternatives, or how to decide between parameters like view, span, or orderby. The description enumerates allowed values but does not explain practical selection criteria or expected use cases.

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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