climb_calculator

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

With no annotations provided, the description carries the burden of disclosing behavior. It adds useful context about LP totals being cumulative and gives an example (Gold IV to Plat IV = 400 LP), which clarifies the calculation basis. However, it does not explain edge cases like winrate extremes or what 'runs backward' means precisely, so transparency is only partial.

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 two sentences, both of which add value. The first states the core purpose, and the second provides a clarifying example. There is no redundancy or unnecessary detail, making it appropriately sized and front-loaded.

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?

For a simple calculator with an output schema, the description provides a reasonable overview of the calculation and a concrete LP example. However, the lack of annotation coverage and the 0% schema description coverage mean the agent must infer several parameter semantics. The description is adequate for selection but not fully complete for confident invocation without further reasoning.

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%, so the description must compensate for parameter explanations. The LP cumulative example helps interpret current_lp_total and target_lp_total, but it does not explain winrate_pct, lp_per_win, or lp_per_loss. These are left to the schema's basic type/default info, which is insufficient for an agent to correctly set values without additional domain knowledge.

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 states the tool calculates how many games a climb takes at a given winrate, or if it runs backward. This clearly identifies the tool's function as a climb calculator, distinguishing it from sibling tools like estimate_mmr or kda. However, the phrasing is indirect ('How many games... takes') rather than an explicit verb like 'calculates,' so it is not perfectly crisp.

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?

Usage is implied by the first sentence: use this tool when you need to know the number of games a climb requires at a given winrate. There is no explicit guidance on when not to use it or how it compares to alternatives such as estimate_mmr. The LP context helps but does not provide exclusions or direct alternatives.

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