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Lumify Sports Intelligence

grade_slip

Read-onlyIdempotent

Grade settleable player-prop legs (over / under / push / in_progress / dnp / no_stat) for NFL and MLB. Prefer structured event_id + player_id + market_key + line + side. Free text is interpreted with a rule-based parser and graded only when player and event resolve uniquely — never guesses an ambiguous name. A team span (CIN, vs Bills, Niners) is resolved first; unique team_id scopes the player, and ambiguous/not_found stays on team_resolve. Not live trading odds. Not wagering advice. Attribution is always Graded by Lumify.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
legsNo
textNoFree-text slip (e.g. Chase over 74.5 receiving yards). A team span is resolved first; unique team_id scopes the player, and ambiguous/not_found stays on team_resolve. Graded only when player and event are unique.
cluesNoOptional sport / league / event_id / team_id / team_text hints for free-text mode.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
legsNo
statusNograded | partial | pending | unmapped
honestyNo
slip_idNo
summaryNo
brandingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), but the description adds substantive behavior: a rule-based parser, a resolve-first/never-guess stance, team-span resolution ordering, and the fixed 'Graded by Lumify' attribution. It does not mention the 8-leg cap or any rate/limit behavior, which keeps it from a 5.

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?

Front-loaded with purpose, then mode guidance, then resolution rules and disclaimers; every sentence carries information. The clipped fragments ('Not live trading odds. Not wagering advice.') are slightly terse but compactly purposeful rather than wasteful.

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?

An output schema exists, so return values need no explanation, and the description covers input modes, ambiguity handling, and attribution. The only meaningful omission is that the 8-leg cap and any server-side validation limits live solely in the schema, leaving an agent without narrative context on batch behavior.

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?

At 67% schema coverage the description compensates by naming the canonical structured field set and explaining the free-text resolution path (team span first, unique team_id scopes player, else stay on team_resolve) plus the purpose of clues. This adds real meaning beyond the nested schema definitions.

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 (grade) and resource (settleable player-prop legs), enumerates the outcome set (over/under/push/in_progress/dnp/no_stat), and scopes the sport space (NFL and MLB). It also distinguishes itself from neighbors like get_odds and get_player_props by declaring it is neither odds nor wagering advice.

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

Usage Guidelines4/5

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

Gives a clear mode preference ('Prefer structured event_id + player_id + market_key + line + side') and explains when free-text mode applies and how ambiguity is handled ('ambiguous/not_found stays on team_resolve'). It does not name other grading alternatives, but for this tool the primary when-to-use decision (structured vs free text) is covered.

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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