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Fantasy Football Draft Assistant

by com.predictionmarketspicks

Explain a Player Ranking

explain_player
Read-only

Explain WHY the 2026 draft board ranks a player where it does, factor by factor: projection, floor/ceiling band, boom/bust week shape, and the three separate ranks a board row carries — our model's own positional rank, the market's ADP, and the published blend between them — plus the edge between model and market. Also states what the projection does NOT model (injuries, camp news, schedule). Free, no key. Use for "why do you have there", "explain ranking", "what's driving 's projection", "why is a sleeper/bust". For a plain outlook or a verdict rather than the reasoning, use player_outlook.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
playerYesPlayer full name (e.g. "Bijan Robinson", "Jaxon Smith-Njigba").
scoringNoScoring format: standard, half_ppr (default), or ppr (full PPR). Overrides a platform preset. Works for Yahoo/ESPN/Sleeper defaults. One of: standard · half_ppr · ppr.
platformNoLeague platform — applies its default scoring, size, roster + best-ball settings (overridable by explicit scoring/teams). Underdog/DraftKings are best ball. One of: yahoo · espn · sleeper · nfl · cbs · fantrax · draftkings · underdog.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed8 schema fields changed
    • addedInput schema / properties / platform / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "enum": [
+      "yahoo",
+      "espn",
+      "sleeper",
+      "nfl",
+      "cbs",
+      "fantrax",
+      "draftkings",
+      "underdog"
+    ],
+    "type": "string"
+  }
+]
    • changedInput schema / properties / platform / description
      Previous value: -"League platform — applies its default scoring, size, roster + best-ball settings (overridable by explicit scoring/teams). Underdog/DraftKings are best ball."New value: +"League platform — applies its default scoring, size, roster + best-ball settings (overridable by explicit scoring/teams). Underdog/DraftKings are best ball. One of: yahoo · espn · sleeper · nfl · cbs · fantrax · draftkings · underdog."
    • removedInput schema / properties / platform / enum
      Removed value: -[
-  "yahoo",
-  "espn",
-  "sleeper",
-  "nfl",
-  "cbs",
-  "fantrax",
-  "draftkings",
-  "underdog"
-]
    • removedInput schema / properties / platform / type
      Removed value: -"string"
    • addedInput schema / properties / scoring / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "enum": [
+      "standard",
+      "half_ppr",
+      "ppr"
+    ],
+    "type": "string"
+  }
+]
    • changedInput schema / properties / scoring / description
      Previous value: -"Scoring format: standard, half_ppr (default), or ppr (full PPR). Overrides a platform preset. Works for Yahoo/ESPN/Sleeper defaults."New value: +"Scoring format: standard, half_ppr (default), or ppr (full PPR). Overrides a platform preset. Works for Yahoo/ESPN/Sleeper defaults. One of: standard · half_ppr · ppr."
    • removedInput schema / properties / scoring / enum
      Removed value: -[
-  "standard",
-  "half_ppr",
-  "ppr"
-]
    • removedInput schema / properties / scoring / type
      Removed value: -"string"
  2. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, and the description adds valuable behavioral context beyond that: it explicitly states what the projection does NOT model (injuries, camp news, schedule) and notes that the tool is free with no key. No contradiction with annotations exists. It could add rate-limit or staleness details, but for a read-only explanation tool the disclosure is strong.

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 dense but every clause earns its place: it front-loads the core purpose, enumerates the output factors, states exclusions, notes cost/auth, gives concrete invocation phrasings, and routes to the sibling alternative. Nothing is redundant or padding.

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?

Even without an output schema, the description fully conveys what the explanation will contain (factor-by-factor breakdown, ranks, edge, and non-modeled items) and when to use it. It covers the tool's scope, limitations, and differentiation, so an agent has everything needed to call it correctly.

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%, so the schema already documents the player, scoring, and platform parameters. The description does not add much parameter-level detail beyond what the schema provides, though it does mention platform/scoring concepts indirectly via the explanation factors. Baseline 3 is appropriate given the high schema coverage.

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 verb ('Explain WHY') and resource ('2026 draft board'), then enumerates exactly which factors are covered: projection, floor/ceiling band, boom/bust week shape, model rank, ADP, blend, and edge. It clearly differentiates from the sibling player_outlook by stating it is reasoning rather than an outlook/verdict.

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?

The description gives explicit trigger phrases ('why do you have <player> there', 'explain <player> ranking', 'what's driving <player>'s projection', 'why is <player> a sleeper/bust') and names the alternative tool to use when a plain outlook or verdict is wanted. This leaves no ambiguity about when to invoke this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Fantasy Football Draft Assistant toolsInspect
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TDQS

A3.9/5.0
Disambiguation3/5

best_available and who_do_i_draft overlap heavily in mid-draft recommendation scenarios, and player_outlook vs explain_player both cover single-player analysis. The other tools are fairly distinct, and the descriptions provide enough usage cues to separate them, but the boundary between the recommendation tools remains blurry.

Naming Consistency3/5

All names are lowercase snake_case, but the semantic pattern is mixed: compare_players, draft_board, and explain_player are verb_noun, while adp_market_gaps, best_available, player_outlook, and sleepers_and_busts are noun/adjective phrases, and who_do_i_draft is a question. Still readable and predictable in style, but not consistently verb-first.

Tool Count5/5

Eight tools is a well-scoped size for a fantasy draft assistant. Each tool addresses a meaningful draft task—rankings, best available, comparisons, outlooks, and market gaps—without feeling padded or redundant.

Completeness4/5

The toolset covers the core draft workflow: full board, best remaining players, player comparisons, single-player outlooks, sleepers/busts, and cross-platform ADP gaps. Minor missing pieces like historical ADP trends or league-specific mock drafting exist, but agents can complete typical draft tasks without dead ends.

Resources