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get_advanced_stats
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Use for tracking and advanced metrics the box score does not carry. Next Gen Stats (2016+): time to throw, air yards, completion percentage above expectation, separation, cushion, rush yards over expected. Pro Football Reference advanced (2018+): pressures, hurries, blitzes, drops, bad throws, missed tackles, coverage yards allowed. Pick a source, then filter by season, week, player or team. Costs 5 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamNoTeam code
weekNoWeek. NGS also publishes week 0 as the season aggregate.
limitNoMax rows (default 50)
seasonNoSeason year. Defaults to current. NGS from 2016, PFR from 2018.
sourceYesWhich dataset: ngs_passing, ngs_rushing, ngs_receiving, pfr_passing, pfr_rushing, pfr_receiving, pfr_defense
player_idNoGSIS id for an ngs_* source, PFR id for a pfr_* source; both are on search_players

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
countYes
statsYes
seasonYes
sourceYes
metric_keysYes
player_id_kindYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuinely non-annotation context: a 5-credit cost and per-source year availability (NGS 2016+, PFR 2018+), which affect whether the call is worth making. It stops short of return format or rate-limit behavior, so this is a modest add on top of annotations.

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 the use case, then the source/metric breakdown, then the filter workflow and cost. The two long metric enumerations are dense but each item is load-bearing for source selection; nothing is redundant.

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 7-value enum tool with an output schema, the description covers source choice, metric coverage per source, valid time ranges, filterable dimensions, and credit cost. Nothing an agent needs before calling is missing, and return values are correctly left to the output schema.

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 adds real semantic value by mapping each source family to what it returns (ngs_* vs pfr_* metric lists) and restating the year floors that gate valid season values. That helps an agent pick the right enum value, not just the right syntax.

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+resource — advanced metrics the box score does not carry — and enumerates the exact metric families available (time to throw, air yards, CPOE, pressures, missed tackles, etc.). The phrase 'the box score does not carry' implicitly separates it from get_player_stats/get_team_stats, so an agent can route correctly without opening a schema.

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 clear usage context ('Use for tracking and advanced metrics the box score does not carry') and a concrete workflow ('Pick a source, then filter by season, week, player or team'). It does not name the sibling it substitutes for or state exclusions, so it falls short of an explicit when-not.

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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