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Lumify Sports Intelligence

resolve_player

Read-onlyIdempotent

Resolve messy sports player names to a Lumify player_id using sport, team, or event clues. Prefer this before grade_slip when the name is a fragment, initial, or nickname. Returns ambiguous instead of guessing — never auto-pick candidates[0]. A sport-scoped key binds the in-scope side of a collision and returns not_found when every hit is out of scope. Does not grade props.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluesNoOptional sport, team, event, or position clues.
queryYesMessy player name or fragment, e.g. J. Chase.
optionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportNo
statusNoresolved | ambiguous | not_found | error
messageNo
team_idNo
player_idNo
candidatesNo
clues_usedNo
confidenceNo
display_nameNo
match_reasonsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses the ambiguity policy ('Returns ambiguous instead of guessing — never auto-pick candidates[0]'), collision behavior for sport-scoped keys, and the not_found result when all hits are out of scope. These are critical behavioral traits not visible in annotations or schema.

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?

Four compact sentences, with the core purpose first and every sentence adding distinct information. No filler or repetition of schema fields.

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

Completeness5/5

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

Given the readOnly annotations, nested input schema, output schema, and sibling context, the description covers purpose, ambiguity behavior, collision handling, and exclusion of prop grading. Nothing critical for selecting or invoking the tool is 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 already documents query, sport slug, and team_text, and has 67% coverage. The description adds meaning by tying clues to resolution, explaining the 'fragment, initial, or nickname' use case, and describing sport-scoped collision semantics. It doesn't explain mode/max_candidates/min_confidence, but those are largely self-describing with defaults.

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?

Description states a specific verb (resolve), resource (messy sports player names), output (Lumify player_id), and clue inputs (sport/team/event). It also contrasts with grade_slip, so an agent can distinguish it without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to prefer resolve_player before grade_slip when the name is a fragment, initial, or nickname, and clarifies what the tool does not do ('Does not grade props'). This is direct when-to-use and when-not-to-use guidance.

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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