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apex_generate_from_schema

Build complete Oracle APEX apps from table names: generates CRUD pages, a dashboard, and navigation automatically.

Instructions

Generate a complete app from a list of tables: CRUD pages + dashboard + navigation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tablesYesList of table names to generate CRUDs for. Example: ["EMPLOYEES", "DEPARTMENTS", "PROJECTS"]
nav_icon_mapNoDict mapping table name to Font Awesome icon class. Example: {"EMPLOYEES": "fa-users", "DEPARTMENTS": "fa-building"} Defaults to "fa-table" for unmapped tables.
start_page_idNoFirst page ID for the first CRUD list (default 10). Pages are allocated: 10/11, 12/13, 14/15...
include_dashboardNoGenerate a dashboard page with record counts (default True).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description discloses the main output (app with CRUD, dashboard, navigation) but does not reveal important behavioral details such as whether it creates a new app or adds to the current one, whether it overwrites existing pages, or whether it is idempotent. Annotations are all false, offering no safety hints, so the description carries the burden but falls short of full transparency.

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 a single, concise sentence that front-loads the core purpose and key deliverables. Every word earns its place, with no fluff or unnecessary detail.

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 complex generation tool with an output schema present, the description provides a clear high-level picture and the schema covers parameter details. It is missing some contextual information about side effects and prerequisites (e.g., whether it requires an existing app), which prevents a perfect score, but it is sufficiently complete for an agent to understand the tool's main function.

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% with well-documented parameters including examples and defaults. The description does not add any parameter-specific meaning beyond the schema, so it does not go beyond the baseline. However, the schema is thorough, so the description does not need to compensate.

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: 'Generate a complete app from a list of tables: CRUD pages + dashboard + navigation.' It uses a specific verb ('Generate'), identifies the resource ('complete app'), and specifies the key components (CRUD pages, dashboard, navigation). This distinguishes it from sibling tools like apex_generate_crud (which likely handles a single table) and apex_create_app (which may create an empty app).

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 gives a clear context for when to use the tool: when you have a list of tables and want a complete app with CRUD, dashboard, and navigation. It does not explicitly mention alternatives or when not to use it, but the context is strong enough for an agent to infer appropriate usage.

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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