abap_wiki: Skill for Claude Code

.agents/skills/ingest-l0/SKILL.md

ingest-l0 is a skill for Claude Code, Codex from Gixsy95/abap_wiki. It costs 64 tokens per session (643 once invoked), scanned A, original, MIT.

A deterministic workflow that creates starter documentation records for every custom object listed in an SAP TADIR export. TADIR is SAP’s catalog of development objects.

In plain words
What is it for?
Use it for a first-time repository setup or after receiving a new TADIR export, using the provided pipeline commands.
Why use it?
It bootstraps or refreshes the abapwiki knowledge base consistently, without AI sub-agents, and can safely be run again.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents; installed under .agents/ (shared by several agents).

This is Gixsy95/abap_wiki's own configuration. It tells Claude Code and Codex how to work on abap_wiki itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything abap_wiki configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python core/src/tools/pipeline.py init-db.

Reuse

Borrowing it

Nothing to install: this file belongs to Gixsy95/abap_wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/Gixsy95/abap_wiki/main/.agents/skills/ingest-l0/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/Gixsy95/abap_wiki

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ingest-l0

README.md
[![agentmods](https://agentmods.dev/badge/skills/gixsy95/abap_wiki/ingest-l0/github.svg)](https://agentmods.dev/skills/gixsy95/abap_wiki/ingest-l0)
Your own site
<a href="https://agentmods.dev/skills/gixsy95/abap_wiki/ingest-l0"><img src="https://agentmods.dev/badge/skills/gixsy95/abap_wiki/ingest-l0/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ingest-l0

Your own site · 80×15
<a href="https://agentmods.dev/skills/gixsy95/abap_wiki/ingest-l0"><img src="https://agentmods.dev/badge/skills/gixsy95/abap_wiki/ingest-l0.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 643 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.00643
Opus 5 $0.00032 $0.00321
Sonnet 5 $0.00013 $0.00129
Haiku 4.5 $0.00006 $0.00064

Measured 12d ago against content hash fcdbf9158a01, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ingest-l0 scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/ingest-l0/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ingest L0 - stub bootstrap from TADIR

Creates (or updates) the L0 stub for every custom object in the TADIR. Everything is deterministic: no sub-agents, parallelism via devclass partitioning. State lives in state/abap_wiki.db (see core/docs/01-pipeline-l0-l1.md).

When to use it

  • First-time initialization of the repo (empty DB).
  • Arrival of a new export raw/tadir/TADIR_Z_<YYYYMMDD>.XLSX.

Procedure

Shortcut: python core/src/tools/pipeline.py l0-run runs steps 1-6 as a single deterministic command (newest TADIR in raw/tadir/ or --file). The step-by-step procedure below remains the reference for diagnostics.

All commands must be run from the repo root with the venv active.

  1. Initialize the schema (idempotent):
    python core/src/tools/pipeline.py init-db
    
  2. Import the TADIR (dtype=str, excludes objects already removed from the L1 queue):
    python core/src/tools/pipeline.py import-tadir --file raw/tadir/<most recent TADIR>.XLSX
    
  3. Resolve sources (unique in-memory index, deterministic hash):
    python core/src/tools/pipeline.py resolve-sources
    
  4. Create L0 stubs (all, or by devclass partition in parallel across multiple sessions):
    python core/src/tools/pipeline.py ingest-l0            # all
    python core/src/tools/pipeline.py ingest-l0 --partition ZPACKAGE   # one package
    
    Idempotent: re-running on an already-processed package is a no-op.
  5. Enqueue L1 (only analyzable types with available source):
    python core/src/tools/pipeline.py enqueue-l1
    
  6. Verify and commit:
    python core/src/tools/pipeline.py progress
    python core/src/tools/pipeline.py export-excel
    python core/src/tools/pipeline.py git-commit --message "ingest L0: <export>"
    

Rules

  • Never modify raw/ (only the user stages it when updating the export).
  • Indexes (abap_wiki/_packages/, abap_wiki/index.md) are regenerated from queries: do not edit them manually.
  • If unknown TADIR types appear they are mapped to tadir-<x> and listed in output/reports/unknown-tadir-types.md (non-blocking).

Read the full file on GitHub · 58 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 58 lines · 64 tokens per session scan A fcdbf9158a01

Subscribe to this mod's changes

ingest-l0 is a skill published in the GitHub repository Gixsy95/abap_wiki (44 stars, last pushed 4d ago), licensed MIT. It adds 64 tokens to every session and 643 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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