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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

nba_draft_combine_anthro

Retrieve NBA draft combine anthropometric measurements for a specified draft year, including player height, weight, wingspan, standing reach, and hand dimensions.

Instructions

NBA draft combine anthropometric measurements. Returns one draft class's combine anthropometric measurements (the DraftCombinePlayerAnthro table). Verified columns are PLAYER_ID, FIRST_NAME, LAST_NAME, POSITION, HEIGHT_WO_SHOES, WEIGHT, WINGSPAN, STANDING_REACH, HAND_LENGTH and HAND_WIDTH. The draft year is required: the endpoint has no all-years mode that was verified.

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": {
      "season_year": "<season_year>"
    },
    "name": "nba_draft_combine_anthro"
  }
}

Input Schema

NameRequiredDescriptionDefault
league_idNoLeague id; only 00 (NBA) is verified
season_yearYesFour-digit draft year

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.20

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the underlying table, that output is scoped to a single draft class, that the column list is 'verified,' and that no all-years mode exists — useful operational context. It says nothing about error behavior, empty results, or whether unverified columns could appear.

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?

Purpose is front-loaded, followed by return contents and then the required-parameter constraint. Four sentences, each earning its place; the column list is long but justified because no output schema exists.

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 two-parameter lookup with no output schema, the definition is nearly complete: it substitutes a column list for a return schema and explains the mandatory year. Only failure modes and sibling differentiation are missing.

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%, so both parameters are already documented; the description reinforces season_year as the draft year and explains why it is mandatory, which adds modest framing beyond the schema's 'Four-digit draft year'.

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 — returns one draft class's combine anthropometric measurements from the DraftCombinePlayerAnthro table — and enumerates the returned columns, so an agent can distinguish it from player bio/stat siblings.

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?

Communicates the key operating constraint: the draft year is required because no verified all-years mode exists. That effectively says when the tool can be used, but it never names an alternative for combine data or explains how it differs from other draft-related siblings.

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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