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validate_ddic_references

Validates ABAP source code against DDIC metadata, detecting invalid table-field references in TYPE, SELECT, WHERE, and New SQL to prevent syntax errors.

Instructions

Statically analyzes ABAP source code and checks all referenced table fields against DDIC metadata. Returns a list of invalid field names. ⚡ Recommended to call before write_abap_source to avoid 'Field unknown' syntax errors. Detects: (1) TYPE/LIKE tab-field, (2) table~field (New SQL), (3) SELECT field list FROM table, (4) WHERE clause fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesABAP source code to validate program logic for
Behavior4/5

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

With no annotations, the description carries full burden. It discloses read-only analysis, return of invalid field names, and detection patterns. However, it omits error handling details (e.g., malformed source) and does not specify the return format—though this is acceptable for a simple validation tool.

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?

Two sentences plus a bulleted list of detection patterns. Front-loaded with the main purpose and usage recommendation. Every sentence adds value, no redundancy.

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?

Given one string input, no output schema, and no annotations, the description sufficiently explains the tool's function and output. It could optionally detail the format of the invalid field names list, but the current level is adequate.

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?

The schema covers 100% of parameters (source) with a description. The tool description adds context by explaining what happens to the source during validation (DDIC reference checking), which provides meaning beyond the schema alone.

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 does static analysis of ABAP source code to check DDIC references, naming four specific detection patterns. This verb+resource definition distinguishes it from sibling tools like SAPWrite or analyze_abap_context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly recommends calling before write_abap_source to prevent syntax errors, providing a concrete when-to-use scenario. No exclusion criteria needed for such a targeted tool.

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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