get_adjusted_points_per_game

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

Annotations already declare readOnly=True, destructive=False, and idempotent=True, so the safety profile is clear. The description adds behavioral context by explaining the adjustment formula (avg_opponent_ppg / league_average_ppg) and how to interpret values relative to raw PPG. This goes beyond what annotations provide and helps the agent reason about the computation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main purpose, followed by a compact formula explanation and an arguments line. Every sentence adds value, and the structure is clean. The 'Args' block is redundant with the schema but serves as a useful inline reminder given that the schema lacks descriptions.

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

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

The description explains what the tool returns (raw and adjusted PPG) and the reasoning behind the adjustment. With an output schema present, return values do not need to be spelled out. It does not cover error conditions or rate limits, but for a simple read-only tool this is adequate. The description is complete enough for an agent to invoke it correctly.

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

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

The input schema only defines team_id as a string with no description (0% coverage). The description compensates by stating 'team_id: ESPN numeric team ID', which clarifies the expected format and meaning. This is sufficient for the single parameter, though it could also mention that the team must exist in ESPN systems.

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

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

The description uses a specific verb+resource ('Get a team's raw points-per-game alongside an opponent-quality-adjusted PPG') and clearly distinguishes this from sibling tools like get_standings or get_strength_of_schedule. It names the exact metric and includes a concise definition.

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

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

The description implies the primary use case: retrieving a team's PPG with an adjustment for opponent quality. It does not explicitly discuss exclusions or alternatives, but the formula explanation gives context for when this metric is relevant. A clear alternative comparison is missing, so it does not fully reach a 5.

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