get_player_histograms

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

With no annotations, the description fully carries the behavioral transparency burden. It explains what the tool returns (histogram buckets), how values are grouped (ranges or exact values), the inclusion of win_rate, and nuances like 'Higher performance levels often correlate with higher win rates.' It also mentions flexible querying ('Supports both IDs and natural language'), pagination via offset, and the having threshold.

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?

Although long, the description is well-structured with clear sections: purpose, usage, exclusions, arguments, return values, and examples. Every section earns its place given 11 parameters and a nuanced output format. The example output is illustrative and not fluff.

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 is complete for a complex tool: it covers all 11 parameters, explains the return value semantics despite having an output schema, and provides concrete examples. It leaves no obvious gaps for the agent to select and invoke the tool 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?

Schema description coverage is 0%, but the description's Args section compensates fully. It explains every parameter, gives alternative names for fields (e.g., 'gpm' or 'gold_per_min'), and clarifies that hero/account parameters accept both IDs and names. This goes far beyond the bare schema.

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 opens with a specific verb+resource: 'Get the DISTRIBUTION of a specific statistic across matches (performance consistency analysis).' It clearly distinguishes itself from siblings like get_player_totals and get_player_win_loss by focusing on distributions, ranges, and consistency.

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?

Provides explicit when-to-use criteria with real user queries (e.g., 'How often does [player] get 10+ kills?') and explicit when-not-to-use instructions with named alternatives ('use get_player_totals() instead', 'use get_player_win_loss() instead'). This is model-level guidance.

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