GridIron Data

Boom/bust vs projections

get_deviations

Read-onlyIdempotent

Returns how a player's actual fantasy points compared with his projections: the average deviation and each week's projected vs actual. Use it to judge boom/bust tendencies or whether a player keeps beating (or missing) his projection. Basic plan and above.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "player_id": "<player_id>"
    },
    "name": "get_deviations"
  }
}

Input Schema

Name	Required	Description	Default
`season`	No	Season year, 2020 or later. Default: the current season.
`player_id`	Yes	GridIron player id, "First Last#POS", matched case-insensitively. Defenses are "Team Name#DST". Unsure of the id? Call search_players first.

Output Schema

Name	Required	Description
`note`	No	A sentence for the user saying which plan is needed.
`error`	No	Present only when the call failed: what went wrong.
`reason`	No	Machine-readable failure reason, e.g. basic_required or pro_required.
`season`	No	Season.
`status`	No	HTTP status of the failed API call.
`position`	No	Position.
`player_id`	No	GridIron player id.
`player_name`	No	Player name.
`upgrade_url`	No	Where to see the plans.
`avg_deviation`	No	Average actual minus projected points.
`required_plan`	No	The plan that unlocks this data: basic or pro.
`weeks_analyzed`	No	Weeks compared.
`weekly_deviations`	No	Per week: actual vs projected points.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The annotations already declare a safe, idempotent, closed-world read, so the description is not carrying the safety burden. It adds meaningful context beyond them: the per-week breakdown shape of the response and the "Basic plan and above" subscription gate, which an agent cannot infer from structured fields.

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 short sentences: the first front-loads what is returned, the second gives the interpretive use case, followed by a terse plan requirement. There is no filler and the shape of the answer precedes the motivation for calling it.

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?

For a two-parameter read tool with an output schema, the description covers purpose, return structure, intended analysis, and access tier. Nothing an agent needs in order to decide to call it and interpret the response is missing.

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 100%, with season defaults and player_id format ("First Last#POS", search_players fallback) fully documented in the schema. The description adds nothing about parameter semantics beyond implying that the season scope drives the week-by-week comparison, so the baseline of 3 applies.

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 resource and computation: how a player's actual fantasy points compared with his projections, returning both the average deviation and week-by-week projected vs actual. That framing cleanly separates it from projection-only siblings such as get_projections, since the output is a actual-vs-projected comparison rather than raw projections.

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?

"Use it to judge boom/bust tendencies or whether a player keeps beating (or missing) his projection" gives a concrete analytical use case that maps directly to the tool's output. It stops short of naming when NOT to use it or pointing to alternatives, so it does not reach the top tier.

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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