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Predicted lineups

get_predicted_lineups
Read-onlyIdempotent

Use this for predicted Premier League starting XIs and team news for the next FPL gameweek (who starts, who is injured or rotated), from fplcopilot's expected minutes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_predicted_lineups"
  }
}

Input Schema

NameRequiredDescriptionDefault
teamsNoClubs, e.g. ['ARS', 'Chelsea'] (default: all 20)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / teams / anyOf
      Previous value: -[
      -  {
      -    "items": {
      -      "maxLength": 30,
      -      "minLength": 1,
      -      "type": "string"
      -    },
      -    "maxItems": 20,
      -    "type": "array"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "items": {
      +      "maxLength": 30,
      +      "minLength": 1,
      +      "type": "string"
      +    },
      +    "maxItems": 40,
      +    "type": "array"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is the temporal scope limitation (next gameweek only) and the provenance of the numbers (fplcopilot's expected minutes). That provenance/scope detail is genuinely useful context beyond the 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?

One front-loaded sentence that opens with the usage trigger and then packs scope, content, and data source with no filler. Nothing could be cut without losing information.

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 single optional-parameter read tool with full schema coverage, rich annotations, and no output schema, the description supplies everything an agent needs: what it returns, for which gameweek, and where the numbers come from.

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% and the single `teams` parameter already documents accepted formats and the default of all 20 clubs. The description adds nothing about the parameter, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete resource (predicted Premier League starting XIs plus team news) and enumerates the contents — who starts, who is injured or rotated. It is clearly distinct from every sibling (get_player, get_my_team, get_penalty_takers), though it never names an alternative explicitly.

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 this for..." gives a clear triggering context and scopes it to the next FPL gameweek, which tells the agent when the data is valid. It offers no when-not guidance or named alternative tool, so it stops short of a 5.

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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