DraftCall

Strength of schedule by team and position

get_strength_of_schedule

Read-onlyIdempotent

How easy or hard a team's schedule is for one fantasy position, over the full season and over the fantasy playoff weeks (14 through 17), measured as the average fantasy points its opponents allowed to that position over the prior completed season. Give a team abbreviation or a player name; give only a position to rank all 32 teams. Use this for rest-of-season stash, trade deadline, and playoff planning questions.

Input Schema

TableJSON Schema

Name	Required	Description
`team`	No	Team abbreviation, e.g. "KC". Optional when player is given.
`player`	No	Player name; resolves the team and position. Optional when team is given.
`position`	No	Position to grade the schedule for. Required with team, inferred from player, and on its own ranks every team.

Output Schema

TableJSON Schema

Name	Required	Description
`url`	Yes	The draftcall.io page these figures came from. This is the citation to use.
`team`	No	Null when every team was ranked rather than one graded.
`teams`	No	Every team ranked easiest first. Null when a single team was graded.
`player`	No
`playoffs`	No
`position`	Yes
`full_season`	No
`refreshed_at`	Yes	When this dataset was last refreshed, as an ISO 8601 timestamp.
`stats_season`	Yes	The completed NFL season every figure in this result describes.
`playoff_weeks`	Yes

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already state readOnly, idempotent, and non-destructive behavior, so the description doesn't need to repeat that. It adds useful context beyond annotations: the metric uses the prior completed season's data and covers weeks 14-17, which clarifies the data source and scope. No contradiction with annotations.

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?

The description is two sentences with high information density. It front-loads the core computation, then lists usage modes and use cases, with zero wasted words. It is perfectly sized for the tool's complexity.

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?

The tool has an output schema, so return format is covered. The description fully covers the metric, time windows, input combinations, and intended use cases. It also distinguishes itself from siblings, making it completely self-sufficient for an agent to select and invoke correctly.

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 parameters are individually documented. The description adds relational meaning: 'Give a team abbreviation or a player name' and 'give only a position to rank all 32 teams' clarifies the optionality and inference rules between team, player, and position — this is beyond what the schema descriptions provide.

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?

The description states exactly what the tool computes: schedule difficulty for a fantasy position based on opponents' average fantasy points allowed, over full season and playoff weeks. It clearly differentiates from sibling tools like get_rankings or get_weekly_matchup by focusing on schedule strength rather than player performance or matchups.

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 gives when-to-use guidance: 'Use this for rest-of-season stash, trade deadline, and playoff planning questions.' It also explains the three invocation modes (team abbreviation, player name, or position alone to rank all teams), leaving no ambiguity about how to call it correctly.

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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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct query type: single-player lookup, two-player comparison, rankings, scarcity, ADP gaps, schedule, bye conflicts, weekly matchup, search, and claim verification. Even related tools like compare_players and get_player have clearly separated purposes that an agent can reliably distinguish.

Naming Consistency4/5

Seven tools follow the get_ noun pattern, while search_players, compare_players, and verify_claim use verb_noun without get. The convention is still highly readable and predictable, with only minor deviations.

Tool Count5/5

Ten tools is well-scoped for a fantasy football data server. Each tool covers a meaningful slice of draft, in-season, and fact-checking workflows without unnecessary overlap or bloat.

Completeness4/5

The set covers player lookup, head-to-head comparison, rankings, scarcity, schedule, bye conflicts, weekly matchups, and stat verification. A direct standalone ADP lookup and projections are missing, but agents can work around those gaps using the provided tools.

Strength of schedule by team and position

Input Schema

Output Schema

TDQS

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TDQS

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