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Check ABAP released-API status

check_released_api
Read-onlyIdempotent

Check ABAP repository objects against SAP's Cloudification list to report released, deprecated, or not-released API status and provide CDS successor hints for classic tables.

Instructions

Look up ABAP repository objects (DB tables, CDS view entities, function modules, classes, interfaces, …) in SAP's published ABAP Cloudification list and report, per object, whether it is a 'released' API (safe to use in ABAP Cloud / Clean Core), 'deprecated' (released but being retired), or 'not-released' (a classic/internal object that is not a public API — e.g. most classic DDIC tables) — with a curated CDS successor hint for common tables. This reflects SAP's official Cloudification list as bundled in this package (snapshot 2026-06-10); it ships offline with the server. Use this when you need to know if your code may reference a given object in ABAP Cloud, or which released CDS view to use instead of a classic table — the released-API half of readiness that check_cloud_readiness deliberately leaves to a system's ATC. It does not connect to any SAP system, does not run ATC, and is only as current as the bundled snapshot — a system's own released-API list (ATC check API_RELEASE_STATE_CHECK / SAP_CP_READINESS) remains authoritative; treat an 'absent from the list' result as 'not-released as of the snapshot', not as proof. Example: check_released_api({ "objects": ["MARA", "I_Product", "BAPI_MATERIAL_GET_DETAIL"] }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectsYesObjects to check, 1–200 per call. Each is a bare name string or a { name, type? } object, e.g. ["MARA", { "name": "I_Product", "type": "CDS_STOB" }].

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesURL of the SAP Apache-2.0 source the snapshot was built from.
resultsYes
snapshotDateYesDate of the bundled SAP Cloudification snapshot these results reflect.
Behavior5/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true; the description adds critical context: offline snapshot, snapshot date, non-authoritative behavior, and conservative interpretation of absent results. This goes beyond annotations without contradicting them.

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 paragraph that front-loads the purpose, then details use cases, limitations, and an example. Every sentence contributes substantive information with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, the description covers all essential aspects: what it does, status categories, successor hints, offline/snapshot limitations, authoritative alternative, and example invocation. An output schema exists to handle return-value details, which are sufficiently referenced.

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 input schema already provides 100% coverage of parameter semantics, so baseline is 3. The description adds a concrete example (check_released_api with mixed string/object array) and clarifies per-object output, which slightly improves usability beyond 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 specifies the verb ('look up'), the resource ('ABAP repository objects'), and the result (released/deprecated/not-released status per object). It explicitly distinguishes this tool from check_cloud_readiness, making sibling differentiation strong.

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?

It explicitly states when to use the tool ('when you need to know if your code may reference a given object in ABAP Cloud'), names check_cloud_readiness as the alternative that delegates system ATC, and provides exclusions (does not connect to SAP, not authoritative). This is model usage guidance.

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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