Fetch one stored PlayStation Store game record by product ID. Use datasets_playstation_games_search to find games or datasets_playstation_games_facets to inspect available filters.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | PlayStation product id, e.g. UP0001-PPSA01491_00-GAME000000000000. |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | The tool result payload (shape varies per tool; see each tool's docs resource). |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered by structured data. The description adds only that the record is 'stored', hinting at a dataset lookup rather than a live fetch, but gives no further behavioral context such as what happens on a missing/invalid product ID. With annotations carrying the main burden, this is adequate but thin.
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?
Two sentences, zero waste. The core action is front-loaded in the first sentence and the disambiguation/routing guidance follows immediately.
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?
An output schema exists, so the description need not explain return values. With the single parameter fully specified in the schema, sibling routing named, and annotations covering safety, an agent has everything required to call this correctly.
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 100% and the product_id parameter is fully documented with an example format in the schema itself. The description adds no additional semantics (e.g., case sensitivity, accepted ID forms) beyond what the schema already provides, so the baseline 3 applies.
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?
States a specific verb ('Fetch'), a specific resource ('one stored PlayStation Store game record'), and the lookup key ('by product ID'). It is clearly distinguished from the sibling search/facets tools, so an agent can select it without opening any schema.
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?
Explicitly routes the agent: use datasets_playstation_games_search to find games, and datasets_playstation_games_facets to inspect filters. Both the when-to-use-this-tool and the when-to-use-something-else conditions are stated, leaving nothing to inference.
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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