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Analyze Cbo Obj

Community
babamba2
analyze-cbo-obj

Analyze a CBO (Customer Business Object) package — discover frequently-used Z tables / function modules / data elements / classes / structures / table types — and save a per-module / per-package reference file so later `program` / `program-to-spec` runs prefer existing CBO elements over new ones.

Overview

Publisherbabamba2
Repositorysuperclaude-for-sap
Skill nameanalyze-cbo-obj
Stars
69
Forks
26
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by babamba2 on GitHub. Read the source before you install it.

Installation

Install the Analyze Cbo Obj AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/babamba2/superclaude-for-sap/tree/main/skills/analyze-cbo-obj
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/babamba2/superclaude-for-sap.git /tmp/superclaude-for-sap
mkdir -p .claude/skills
cp -r /tmp/superclaude-for-sap/skills/analyze-cbo-obj .claude/skills/analyze-cbo-obj
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analyze Cbo Obj in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analyze Cbo Obj on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analyze Cbo Obj is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SC4SAP Analyze CBO Objects

Walks a CBO (Customer Business Object) package, inventories every project-built ABAP element (table, structure, data element, class, interface, function module, program, view, table type), detects which elements are frequently reused inside the package, infers each element's business purpose from its name/fields/descriptions, and persists the result to .sc4sap/cbo/<MODULE>/<PACKAGE>/ for downstream skills (program, program-to-spec, create-object, autopilot) to consult before creating anything new.

<Response_Prefix> Every response triggered by this skill MUST begin with [Model: <main-model> · Dispatched: <sub-summary>] per ../../common/model-routing-rule.md § Response Prefix Convention. </Response_Prefix> <Target_Object>The target object is looked up on the active profile's system only. Not found → stop and ask per ../../common/multi-profile-artifact-resolution.md § Target object not on the active system — never substitute a similar name, never switch profiles on your own.</Target_Object>

<Phase_Banner> Multi-phase skill. Before each Agent(...) dispatch, emit ▶ phase=<id> (<label>) · agent=<name> · model=<Opus|Sonnet|Haiku> per ../../common/model-routing-rule.md § Phase Banner Convention. Resolve the dispatch mode first per ../../common/model-dispatch-mode.md: auto (default) uses the model below/in the rule; user-defined asks the user Opus / Sonnet / Haiku (recommended one first) before each dispatch group. </Phase_Banner>

<Use_When>

  • Starting development on a module that already has a sizeable Z-package
  • Onboarding onto an AMS / support engagement (need a map of custom assets)
  • Before /sc4sap:create-program or /sc4sap:create-object on a new spec — so reuse is evaluated
  • User says "analyze CBO", "analyze custom objects", "map Z package", "list frequently used customs", "CBO inventory" </Use_When>

<Do_Not_Use_When>

  • User wants a code quality review of one object → /sc4sap:analyze-code
  • User wants to reverse-engineer ONE program into a spec → /sc4sap:program-to-spec
  • User wants to create an object → /sc4sap:create-object
  • Package does not yet contain custom objects (CBO discovery is not meaningful) </Do_Not_Use_When>

<Session_Trust_Bootstrap> MANDATORY — runs as Step 0 before any MCP call or user interaction.

Invoke /sc4sap:trust-session with parent_skill=sc4sap:analyze-cbo-obj to pre-grant all MCP tool + file-op permissions for this session (eliminates per-tool "Allow this tool?" prompts during the 8-step walk).

  • If .sc4sap/session-trust.log already has a line within the last 24h, skip silently.
  • Otherwise run it and surface the one-line confirmation.

Full spec: see ../trust-session/SKILL.md. </Session_Trust_Bootstrap>

<Workflow_Steps> Orchestration is 3 main-thread Socratic steps + a delegated stocking pass (sap-stocker walk → sap-checker scout fan-out → reference graph + usage → sap-stocker finalize) + a branching hand-off. Detailed spec lives in workflow-steps.md.

  • Step 1 / 1.5 / 2 (main thread) — Socratic intake: package name → flagship programs (optional <KEY_PROGRAMS>) → module. The main thread follows the session model (model: inherit).
  • Step 3–7 (delegated · Sonnet + Haiku) — sap-stocker MODE: walk writes walk.json; for packages with ≥ 30 objects, Haiku sap-checker × N collect in-package callers + DDIC signals per batch in parallel (scout-facts.md); Step G fetches sources and builds graph.json from source, TCodes and DDIC, plus on ECC usage-result.json from ST03N TCode usage and batch jobs (graph-usage.md); sap-stocker MODE: finalize does the rest. Spec: stocker-fanout.md. Together they run the stocker's Investigation_Protocol: walk → reference graph (GetWhereUsed on S/4, graph.json on ECC) → pin/frequency tiering → business-purpose inference → cross-module gap analysis (per ../../common/active-modules.md) → sensitive-name flagging → persist index.md + inventory.json → return a Logic-heavy: <bool> flag. Authoritative spec: ../../agents/sap-stocker.md § Investigation_Protocol + § Output_Format.
  • Step 8 (branching):
    • Branch A (Logic-heavy: false, DDIC-dominant) — canned summary printed by main thread. No agent dispatch.
    • Branch B (Logic-heavy: true, FM/CLAS/INTF/large-PROG in inventory) — main thread renders a reader-facing briefing from inventory.json: pinned highlights · business-logic assets · cross-module gaps · sensitive objects · next-step hint. No extra agent dispatch.

Main thread NEVER calls GetPackageContents / GetWhereUsed itself for the inventory pass — that context stays inside the stocker and checker agents so the orchestrator window remains small even for large packages (200+ objects). </Workflow_Steps>

<Output_Files>

.sc4sap/cbo/
└── <MODULE>/               # SD, MM, PP, PM, QM, WM, TM, TR, FI, CO, HCM, BW, PS, Ariba
    └── <PACKAGE>/          # e.g., ZSD_MAIN
        ├── index.md        # human-readable summary, grouped by object type
        ├── index.html      # optional single-file HTML view of index.md (offered at Step 8)
        ├── inventory.json  # machine-readable, consumed by sibling skills
        ├── walk.json       # package member list + scout batches (stocker walk)
        ├── scout-facts.md  # Haiku checker FACT lines (only for packages with ≥ 30 objects)
        └── raw-walk.md     # optional full walk (only if asked or small package)

</Output_Files>

<MCP_Tools_Used>

  • Discovery: GetPackage, GetPackageContents, GetPackageTree, SearchObject, GetObjectsByType
  • Object detail: GetTable, GetStructure, GetDataElement, GetDomain, GetView, GetClass, GetInterface, GetFunctionGroup, GetFunctionModule, GetProgram, GetObjectInfo
  • Usage graph: GetWhereUsed
  • NEVER used by this skill: GetTableContents, GetSqlQuery (no row data — DDIC metadata only) </MCP_Tools_Used>

<Related_Skills>

  • /sc4sap:create-program — reads .sc4sap/cbo/<MODULE>/<PACKAGE>/inventory.json during spec drafting to prefer existing CBO elements
  • /sc4sap:program-to-spec — same, for reverse-engineering
  • /sc4sap:create-object — same, to suggest reuse before creation
  • /sc4sap:analyze-code — quality review of ONE object (complementary, not overlapping) </Related_Skills>

<Data_Extraction_Safety> This skill only reads DDIC metadata and where-used relations. It MUST NOT call GetTableContents or GetSqlQuery. Row-level access stays behind the standard blocklist + acknowledge_risk gate. See common/data-extraction-policy.md. </Data_Extraction_Safety>

Task: $ARGUMENTS

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analyze Cbo Obj AI skill do?

Analyze a CBO (Customer Business Object) package — discover frequently-used Z tables / function modules / data elements / classes / structures / table types — and save a per-module / per-package reference file so later `program` / `program-to-spec` runs prefer existing CBO elements over new ones.

Why use Analyze Cbo Obj on TypingMind?

Because you install it once and use it with any model. Analyze Cbo Obj is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analyze Cbo Obj in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/babamba2/superclaude-for-sap/tree/main/skills/analyze-cbo-obj. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analyze Cbo Obj?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analyze Cbo Obj?

As many as you like. As long as a model supports skills, you can use Analyze Cbo Obj with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analyze Cbo Obj AI skill free?

Yes. It is published on GitHub by babamba2 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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