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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

nba_team_years

Retrieve every NBA franchise and the range of seasons each has played, returned as one row per team for league history analysis.

Instructions

Returns every franchise and the range of seasons it has played, one row per team. Returns every franchise and the range of seasons it has played, one row per team.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "nba_team_years"
  }
}

Input Schema

NameRequiredDescriptionDefault
league_idNoOptional league id; only 00 (NBA) is verified.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.20

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full load. It does disclose the result grain (one row per team) and scope (all franchises), but says nothing about whether the call is read-only, how large the result is, ordering, or what happens when the optional league filter is omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The identical sentence appears twice verbatim, which is pure waste and suggests an assembly defect. What remains is short and front-loaded, but the duplication undermines the structure.

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

Completeness3/5

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

For a simple zero-required-parameter lookup with high schema coverage and no output schema, the description is close to sufficient: it names the entities and the grain. It still omits return columns and the effect of defaulting the league filter, which an agent would want.

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?

The single parameter is fully documented in the schema (100% coverage), including the enum value and the note that only 00 is verified. The description adds no meaning beyond that, so the baseline of 3 applies.

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 gives a specific verb ("Returns") and resource (every franchise plus the range of seasons each has played), and "one row per team" pins down the grain. It does not distinguish this from plausible siblings like nba_franchise_history, so an agent must still guess which one to pick.

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 when-to-use guidance, no prerequisites, and no named alternative. The only usage signal is the implicit one that the tool is a league-wide listing rather than a per-team lookup.

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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