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CAP entity scaffold (all layers)

cap_scaffold_entity

Generate complete SAP CAP entity scaffolding including CDS model, service projection, annotations, mock CSV, and i18n. Returns content ready to write and validate.

Instructions

Generates the complete scaffolding of a CAP entity following the loaded conventions: CDS model, service projection, annotations.cds (labels + UI.LineItem), mock CSV header and i18n in two languages. Returns the content so you write it with cap_write_files and validate it with cap_validate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftNoEnable Fiori draft (@odata.draft.enabled) on the service. Defaults to false.
entityYesEntity name in PascalCase
fieldsYesEntity fields (without the technical ID key)
managedNoUse cuid+managed aspects (UUID key + audit fields). Defaults to true.
serviceYesName of the service that will expose it
namespaceYesModel namespace, e.g. ACME
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses the key behavioral trait that the tool only 'Returns the content' (i.e., it does not write files itself), which is critical for agents to avoid wrongly assuming side effects. It also transparently enumerates all generated artifacts, giving a clear expectation of output scope.

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?

A single dense sentence that front-loads the tool's purpose and enumerates the output artifacts without waste. Every clause adds information: what is generated, the conventions applied, and the workflow follow-through. No filler or repetition of schema details.

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 generative tool with no output schema, the description adequately communicates what will be returned (content for four artifact types) and how to proceed. It could explain return format/structure further, but given schema coverage is complete and the description names the follow-up tools, it is reasonably complete for a scaffold generator.

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

Parameters4/5

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

Schema coverage is 100%, so the schema thoroughly documents all 6 parameters. The description adds value by clarifying how fields map to generated output (inList -> UI.LineItem, managed -> cuid+aspects) and noting the fields array excludes the technical ID key, which reduces ambiguity beyond what the bare schema provides.

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 verb 'Generates' with a specific resource ('complete scaffolding of a CAP entity') and enumerates precisely what is produced (CDS model, service projection, annotations.cds, mock CSV, i18n). It differentiates from siblings by naming downstream tools (cap_write_files, cap_validate), showing the tool is a generator, not a writer or validator.

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 implies usage by noting the generated content should be written with cap_write_files and validated with cap_validate, effectively contextualizing the workflow. However, it doesn't explicitly state when NOT to use this tool or name alternatives like cap_analyze_legacy_ui5 or ui5_scaffold_section, leaving the exclusion boundary implicit.

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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