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Get Pokemon Info

get_pokemon

Retrieve Pokemon data by name, including types, abilities, and base stats. Handles partial and misspelled names, listing candidate matches when ambiguous.

Instructions

Look up a Pokemon by name. Supports exact, partial, and misspelled names. Returns types, abilities, base stats, and other pokedex info. If the name is ambiguous, a list of candidate names is returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPokemon name, e.g. 'pikachu', 'pika', or even a typo like 'charmandr'
Behavior4/5

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

No annotations are present, so the description carries the full burden. It discloses fuzzy matching (exact, partial, misspelled) and the ambiguity fallback (list of candidate names). It does not explicitly state read-only behavior, but for a lookup tool this is obvious from context. It also does not mention error cases or rate limits, but the disclosed behaviors are meaningful and beyond the schema.

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?

Two sentences, no fluff. The purpose and key behaviors are front-loaded, and the example-based parameter hint is in the schema. Every sentence earns its place.

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

Completeness4/5

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

For a one-parameter lookup tool with a fully documented schema and no output schema, the description explains return types (types, abilities, stats) and the ambiguity behavior. It is complete enough for an agent to know what to expect. Minor omissions like error handling or pagination are not critical for this simple tool.

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

Parameters3/5

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

Schema description coverage is 100% – the 'query' parameter is fully described with examples ('pikachu', 'pika', 'charmandr'). The description reiterates that the tool looks up by name but adds no new parameter-level meaning. Baseline 3 is appropriate since the schema already provides complete semantics.

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

Purpose5/5

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

The description states a specific verb ('Look up') and resource ('a Pokemon by name') and clearly distinguishes from the sibling tool predict_battle, which implies a different purpose (battle prediction). The mention of 'types, abilities, base stats, and other pokedex info' further clarifies scope.

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

Usage Guidelines4/5

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

The description implicitly clarifies when to use the tool (when you need Pokemon information) and contrasts with the sibling predict_battle by function. However, it does not explicitly state 'use this for lookups, use predict_battle for battles' or list any exclusions (e.g., when not to use). This is clear enough for an agent to decide, but lacks explicit routing.

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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