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Sportsdataio Projections

sportsdataio_projections
Read-onlyIdempotent

Projected player stats for a slate — fantasy points plus key projected stats per player. Daily sports (NBA / MLB / NHL / CBB) take a date; weekly sports (NFL / CFB) take season + week. Note: a free trial key returns scrambled sample data. Example: sportsdataio_projections({ league: "nba", date: "2026-01-15", _apiKey: "your-key" }) or sportsdataio_projections({ league: "nfl", season: "2025REG", week: 5, _apiKey: "your-key" })

Input Schema

NameRequiredDescriptionDefault
dateNoGame date in YYYY-MM-DD format (used for NBA/MLB/NHL/CBB), e.g. "2026-01-15"
weekNoWeek number for weekly sports (NFL/CFB), e.g. 5
leagueYesLeague to query. One of: nfl / nba / mlb / nhl / cfb / cbb.
seasonNoSeason for weekly sports (NFL/CFB), e.g. "2025REG", "2025POST", or "2025"
_apiKeyYesSportsDataIO API key

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/openWorld/non-destructive, so the safety profile is handled. The description adds a genuinely useful behavioral caveat not present in structured data: a free trial key returns scrambled sample data, which explains surprising results. It does not cover rate limits or result volume.

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?

Three sentences, front-loaded with what the tool returns, then the parameter-routing rule, then the trial-key caveat. The two inline examples are partly duplicative of the schema's own examples array, which is a minor redundancy, but nothing else is wasted.

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?

With no output schema, the description usefully names what comes back (fantasy points plus key projected stats per player). Combined with the league-based parameter routing and the trial-key warning, an agent has enough to call it correctly; pagination/result size and exact return shape remain unstated.

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 the baseline is 3, but the description goes further by explaining the cross-parameter conditional structure (which fields are required for which league families) rather than just restating individual field docs. It adds routing logic the per-field schema descriptions do not express on their own.

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 concrete verb+resource: projected player stats per player, including fantasy points and key projected stats, for a slate. It is clearly distinguishable from the closest siblings sportsdataio_player_props and sportsdataio_injuries, which cover different data domains.

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 explicit conditional routing: daily sports (NBA/MLB/NHL/CBB) use `date`, weekly sports (NFL/CFB) use `season` + `week`. That tells an agent how to invoke it correctly, but it never states when to prefer this over sportsdataio_player_props or injuries, so no alternatives or exclusions are named.

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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