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sap_syntax_check

Validate ABAP source code for syntax errors before activation. Use optional program context to identify issues without creating or activating the object.

Instructions

Validates ABAP source code for syntax errors without creating or activating it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesSource code lines to check
program_nameNoContext program name (optional)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed5 schema fields changedv0.1.2
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / additionalProperties
      Removed value: -false
    • changedInput schema / properties / program_name / description
      Previous value: -"Optional program name for context"New value: +"Context program name (optional)"
    • addedInput schema / properties / program_name / example
      Added value: +"ZPROG_TEST"
    • changedInput schema / properties / source / description
      Previous value: -"ABAP source code as an array of lines"New value: +"Source code lines to check"
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explicitly states the tool does not create or activate code, which is a meaningful non-destructive behavioral trait. It does not describe output format or potential failure modes, but the core side-effect profile is transparent.

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 sentence that is front-loaded with the key purpose and immediately clarifies the non-destructive nature. Every word earns its place; there is no waste or irrelevant 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 simple validation tool with only two parameters and no output schema, the description is mostly complete. It clearly states what code is checked and that nothing is created or activated. The main gap is not describing the shape of the validation result, but the purpose strongly implies a syntax-error response.

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 description coverage is 100%, so the schema already documents both parameters. The description does not add additional meaning about the source array or program_name beyond what the schema provides, which meets the baseline.

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 specifies a precise action ('Validates ABAP source code for syntax errors') on a clear resource. It distinguishes itself from siblings like sap_read_code and sap_write_code by focusing purely on validation rather than reading or writing code.

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 phrase 'without creating or activating it' clearly implies this is a safe validation step, likely before activation or program creation. It does not explicitly name alternative tools or state when not to use it, but the usage context is clear enough.

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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