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Fantasy Football Draft Assistant

by com.predictionmarketspicks

ADP Market Gaps

adp_market_gaps
Read-only

Find the 2026 fantasy players whose Average Draft Position swings most between platforms — consensus vs ESPN, Sleeper, Yahoo, Underdog, etc. A wide gap (e.g. "consensus RB18 but ESPN drafts him RB30") is a platform-specific value: grab him where he goes latest. All 154 gaps are FREE — no key, no email. Pro adds the judgment layer on each row. Use for "ADP differences by platform", "where is a player cheapest", "ADP arbitrage", "who falls on ESPN vs Sleeper". Filter by position (QB/RB/WR/TE/FLEX).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax players to return, widest gap first (default 25). All 154 gaps are free.
scoringNoScoring format: standard, half_ppr (default), or ppr (full PPR). Overrides a platform preset. Works for Yahoo/ESPN/Sleeper defaults.
positionNoOptional position filter (FLEX = RB/WR/TE).

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark the tool read-only; the description adds that all 154 gaps are free with no key/email and that Pro adds a judgment layer. It conveys the arbitrage philosophy but does not detail output shape or sort behavior, though limit schema covers widest-gap-first.

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?

The description is front-loaded with the core value proposition and includes useful examples in a compact form. Minor repetition of the free-data point and the Pro mention add a small amount of marketing weight but do not obscure the operational meaning.

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?

For a read-only list tool with fully described parameters and no output schema, the description gives enough to select and call the tool: what it returns conceptually, the platform set, and example queries. It does not enumerate output fields, but the examples imply the row-level comparison like 'consensus RB18 but ESPN drafts him RB30'.

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?

All three parameters are fully described in the schema (limit, scoring, position), so the description's mention of position filtering adds little beyond schema. Baseline 3 applies because the schema bears the semantic load.

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 names a specific deliverable ('players whose ADP swings most between platforms') and contrasts consensus against named platforms (ESPN, Sleeper, Yahoo, Underdog), making it easy to distinguish from siblings like sleepers_and_busts or player_outlook.

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?

It provides concrete query intents ('ADP differences by platform', 'where is a player cheapest', 'ADP arbitrage') and a position filter. It does not explicitly name sibling alternatives or state when not to use this tool, so the guidance stops short of full exclusion.

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

A4/5.0
Disambiguation3/5

Most tools have clear boundaries, but best_available and who_do_i_draft both target mid-draft pick recommendations and even share similar trigger phrases, while adp_market_gaps and sleepers_and_busts both concern market gaps. The detailed descriptions mitigate the overlap, but an agent could still misroute a draft-time 'who should I take' query.

Naming Consistency3/5

All names are readable snake_case, but they follow no single convention: compare_players and explain_player use verb_noun, while draft_board, player_outlook, and adp_market_gaps are noun phrases, and who_do_i_draft is a full question. It is not chaotic, but there is no predictable pattern to help an agent infer tool purpose from the name.

Tool Count5/5

Eight tools is a well-scoped size for a draft assistant: rankings, player outlook, comparisons, draft recommendations, and value analysis all have a dedicated tool without redundancy or bloat. Each tool has a place in the pre-draft and mid-draft workflow.

Completeness5/5

The surface covers the full draft decision lifecycle: full board, position filters, single-player outlooks, head-to-head comparisons, sleepers and busts, platform ADP gaps, and just-in-time pick recommendations. The only absence is deeper league management features, which are outside the stated assistant purpose.

Resources