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Get recently played

get_recently_played
Read-only

Retrieve a player's recently played games from the last two weeks to assess current gaming interests and mood, based on playtime history.

Instructions

What the player has actually played in the last two weeks. The best read on current mood, as opposed to the lifetime habits get_taste_profile describes. Requires a Steam API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userNoSteamID64, vanity name, or profile URL. Omit to use the configured default player.
Behavior4/5

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

The annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe read operation that works across the open Steam world. The description adds that it requires a Steam API key, which is a behavioral constraint beyond the annotations. This is valuable context. There's no contradiction, and the description adds meaningful context about authentication requirements.

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?

Three sentences with zero waste. The core purpose and scope are front-loaded in the first sentence, followed by the contrast with a sibling and the API key requirement. Every sentence earns its place, and the structure is logical and readable.

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 single-parameter, read-only tool with a 100%-covered schema and no output schema, the description is quite complete. It includes the typical use case, a distinguishing contrast, and the authentication prerequisite. The only minor omission is that it doesn't describe the return format, but that's typically expected from the tool's response and the description already covers the choice criteria and invocation requirements.

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 coverage is 100%, so the schema already documents the single parameter 'user' with its description. The description does not add additional semantics beyond the schema, but it's not required because coverage is complete. The baseline of 3 applies here; the description doesn't compensate further, but it doesn't need to.

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 what the tool does: it retrieves recently played games in the last two weeks. It explicitly contrasts this with get_taste_profile, which describes lifetime habits, making the purpose unambiguous and differentiating it from a key sibling. The verb 'get' combined with the specific resource 'recently played' and the explicit timeframe provides a strong, specific purpose.

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 provides clear context for when to use this tool: when you need current mood based on recent activity, versus lifetime habits from get_taste_profile. It explicitly names the alternative and the condition differentiating them. However, it does not explicitly state when not to use it or mention other alternatives like search_games or get_game_reviews, but the context given is sufficient for most selection scenarios.

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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