estimate_mmr

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the conceptual basis (asymmetry in LP flow) but does not disclose what the tool returns, the role of current_rank, or any limitations/caveats. This leaves significant behavioral unknowns for an agent.

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 concise (three sentences) and front-loaded with the purpose. The following sentences explain the underlying signal, adding useful context without wasted words. Every sentence earns its place.

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?

Even with an output schema, the description fails to explain key interface details: how current_rank influences the estimate, what the output format is, and whether there are prerequisites beyond LP gain/loss. Combined with absent annotations, the description is incomplete for confident invocation.

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 descriptions cover 0% of parameters, so the description must compensate. It offers partial context: 'LP flow' and 'wins and losses' suggest lp_gain and lp_loss are LP changes on win/loss, but it never explicitly defines them, and current_rank is not mentioned at all. This is insufficient for the agent to understand all parameters.

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 clearly states the tool's purpose with a specific verb and resource: 'Estimate where your MMR sits relative to your rank, from LP flow.' This distinguishes it from sibling tools like climb_calculator or readiness_reference, which address different questions.

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 provides clear context for when to use the tool: whenever you need to estimate MMR from LP gain/loss patterns. It does not explicitly mention alternatives or exclusions, but the context is unambiguous about its intended use case, which aligns with a score of 4.

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