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bluebot-609
by bluebot-609

get_match_history_by_name

Retrieve a player's recent Valorant match history by entering their name and tag. Get detailed stats like kills, deaths, assists, agents, and maps.

Instructions

Get recent match history for a player.

Returns matches across all game modes with detailed stats.

Args: name: Player's in-game name tag: Player's tag region: Region code (ap, na, eu, kr, br, latam) size: Number of matches (default: 10, max: 20)

Returns: List of matches with kills, deaths, assists, agents, maps, scores

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagYes
nameYes
sizeNo
regionNona

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the return format (list of matches with kills, deaths, assists, agents, maps, scores) and scope (all game modes), which is helpful. However, it does not mention potential errors, pagination, rate limits, or any side effects (though this is a read operation). The transparency is adequate but not exhaustive.

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?

The description is well-structured: a concise one-sentence summary followed by clearly labeled Args and Returns sections. Every sentence adds value, and the format is easy to parse. It is appropriately sized and front-loaded with the primary purpose.

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?

Given the tool's moderate complexity (4 params, 2 required, output schema present), the description adequately covers parameter semantics and return values. It does not explain failure modes or API-specific behaviors, but for a simple read operation with an output schema, it is sufficiently complete. Minor gaps like region validation or pagination are not catastrophic.

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

Parameters5/5

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

Schema description coverage is 0%, forcing the description to compensate. It does so effectively by providing explicit meanings for each parameter: 'name: Player's in-game name', 'tag: Player's tag', 'region: Region code (ap, na, eu, kr, br, latam)', and 'size: Number of matches (default: 10, max: 20)'. This adds critical semantics beyond the bare types in the schema, including enum-like values and constraints.

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 clearly states the tool's purpose with a specific verb ('Get') and resource ('recent match history for a player'). It adds 'across all game modes with detailed stats', which differentiates it from sibling tools like get_lifetime_matches_by_name (lifetime history) and get_match_details (specific match).

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

Usage Guidelines3/5

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

The description provides context ('recent', 'all game modes') but does not explicitly state when to use this tool versus alternatives like get_lifetime_matches_by_name or get_match_details. There are no explicit exclusions or alternative recommendations, leaving the agent to infer usage from the name and description.

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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