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zacharytran26

Fantasy-Football-Draft-MCP

model_settings

Adjust the influence of pace, offensive line, injury, schedule, and consistency on player rankings, then rebuild your draft board to reflect the changes.

Instructions

Tune how much each factor moves a player. Rebuilds the board.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pace_weightNo
oline_weightNo
injury_weightNo
schedule_weightNo
consistency_weightNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the burden falls on the description. It discloses a key behavioral trait ('Rebuilds the board'), indicating a mutating side effect, but lacks details about persistence, reversibility, or any other side effects. The description is too sparse to fully inform an agent about consequences.

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 extremely concise, just two short sentences. It front-loads the primary purpose ('Tune how much each factor moves a player') and adds a crucial side-effect note ('Rebuilds the board') without any redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters with zero schema descriptions, no annotations, and a mutating behavior, the description is insufficient. It doesn't explain parameter semantics, side effects beyond rebuilding, or any usage context. The presence of an output schema does not compensate for the missing parameter and behavior details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only generically references 'each factor' without explaining the individual parameters (pace_weight, oline_weight, etc.). It does not clarify value ranges, impact of nulls, or how weights affect the board. The description adds minimal meaning beyond the parameter names.

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 clear action ('Tune how much each factor moves a player') with a specific resource (model settings affecting player movement). It uses a specific verb and indicates the purpose, though it doesn't explicitly differentiate from sibling tools like configure_league. The phrase 'Rebuilds the board' adds clarity about the tool's effect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage context ('Tune how much each factor moves a player') but gives no explicit instructions on when to use this tool versus alternatives like configure_league or reset_draft. No when-not-to-use or alternative guidance is present.

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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