oracle_list_recipes
List all predefined scene recipes — curated multi-table compositions that produce coherent narrative prompts
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| game | No | Filter by game system (omit for all) |
List all predefined scene recipes — curated multi-table compositions that produce coherent narrative prompts
| Name | Required | Description | Default |
|---|---|---|---|
| game | No | Filter by game system (omit for all) |
Changes observed during successful MCP inspections.
Input schema / properties / game / descriptionPrevious value: -"Filter by game. Omit to see all."New value: +"Filter by game system (omit for all)"Input schema / properties / game / descriptionPrevious value: -"Filter by game system (omit for all)"New value: +"Filter by game. Omit to see all."Input schema / properties / game / descriptionPrevious value: -"Filter by game. Omit to see all."New value: +"Filter by game system (omit for all)"Input schema / properties / game / enumRemoved value: -[
- "starforged",
- "ironsworn",
- "maze-rats"
-]Input schema / properties / game / enumPrevious value: -[
- "starforged",
- "ironsworn"
-]New value: +[
+ "starforged",
+ "ironsworn",
+ "maze-rats"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It reveals the conceptual nature of the output ('curated multi-table compositions that produce coherent narrative prompts') and implies a read-only listing operation, but it does not mention return format, ordering, or any side effects. This is adequate but leaves gaps.
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 a single, front-loaded sentence that defines the tool's action and clarifies the nature of the recipes without any redundant filler. Every word contributes to understanding.
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 low-complexity listing tool with one optional, fully-specified parameter and no output schema, the description sufficiently conveys what the tool does and what kind of items it returns. It would benefit from a brief note on the response shape, but the current information is largely sufficient.
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?
The input schema has 100% description coverage for the single 'game' parameter, explaining it is an optional filter. The description adds no extra parameter-level meaning beyond what the schema already provides; the baseline of 3 is appropriate.
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 uses a specific verb 'List' and a specific resource 'predefined scene recipes', and further clarifies them as 'curated multi-table compositions that produce coherent narrative prompts'. This clearly distinguishes the tool from sibling listing tools like oracle_list_tables and oracle_list_games.
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?
The description implies use when the agent needs to enumerate all available scene recipes, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it name alternative tools for different purposes. The usage context is implied rather than stated.
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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