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rulebook-mcp

rulebook-mcp

search_rules

Find relevant 2026-27 NBA playing rules by natural-language query, returning cited section IDs and excerpts for grounded answers.

Instructions

Search the 2026-27 NBA playing rules. Returns the most relevant sections with ids and an excerpt.

Input Schema

NameRequiredDescriptionDefault
kNo
queryYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and only partially meets it: it discloses the corpus (2026-27 rules) and that ranking is by relevance, returning ids plus excerpts. It says nothing about how many results come back, whether results are truncated, or how excerpts relate to full sections.

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?

Two sentences, no filler, purpose stated first and return shape second. Every clause earns its place.

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?

An output schema exists, so the description needn't explain return values in detail and it covers the essentials of what the tool searches. However, a search tool with an unexplained result-count parameter and unnamed sibling alternatives is only minimally complete.

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 0%, so the parameters 'query' and especially 'k' are undocumented structurally. The description implies relevance ranking but never explains that k controls the number of results or its default of 5, leaving the main non-obvious parameter unaddressed.

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 names a specific verb and resource ('Search the 2026-27 NBA playing rules') and states the return shape (relevant sections with ids and excerpts). It implicitly contrasts with get_section by focusing on retrieval rather than lookup, though it never names the siblings explicitly.

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 statement of when to use this versus list_sections or get_section, no mention of prerequisites, and no note that results are relevance-ranked or limited. The agent must infer that search is for unknown-section queries and that ids feed get_section.

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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