Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add marcellourbani/vscode_abap_remote_fs --skill prepare-datagit clone --depth 1 https://github.com/marcellourbani/vscode_abap_remote_fsWrote 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.
[](https://agentmods.dev/skills/marcellourbani/vscode_abap_remote_fs/prepare-data)<a href="https://agentmods.dev/skills/marcellourbani/vscode_abap_remote_fs/prepare-data"><img src="https://agentmods.dev/badge/skills/marcellourbani/vscode_abap_remote_fs/prepare-data.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.07027 |
| Opus 5 | $0.00041 | $0.03513 |
| Sonnet 5 | $0.00016 | $0.01405 |
| Haiku 4.5 | $0.00008 | $0.00703 |
Grade A, and why
prepare-data 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 305 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prepare Data — Phase 5 (of 7)
For a cross-system staged scenario, also load multi-system-workflows. Do not cache a
runtime-produced predecessor key in data.json; resolve only genuine pre-run inputs here.
Phase order: analyze-and-plan (1) → explore-ui (2) → design-cases (3) → define-data (4) → prepare-data (5) → build-scripts (6) → run-scripts (7). This phase reads the TC-XXX.data.md specs authored in Phase 4 and resolves them into per-system data.json caches.
For bounded, self-contained support work, use sap-task-helper with explicit inputs, allowed writes, and an output contract.
Tool availability (read this if a tool seems missing)
Naming: when these docs say call X, X is a tool (you invoke it and get a result); delegate to / invoke X is an agent (a subagent you launch); load / follow X is a skill (a procedure you read). A name without a verb: see the overview's "Skills, tools, and agents" list.
The editor may hide tools until searched for. Before Step 0, ensure abapfs_get_test_folder, abapfs_get_connected_systems, abapfs_check_test_data, abapfs_verify_test_data_usage, abapfs_get_sql_syntax, and abapfs_run_sql_query are available; if any is missing, search your available tools for it by name. If one cannot be found, tell the user.
Non-negotiable execution gate
Every required step and artifact below is recorded as a Phase 5 prerequisite. The abapfs_run_playwright_tests tool verifies data preparation and will reject every affected case if preparation was skipped, deferred, incomplete, stale, or unverified. Complete each requirement now; runtime fallback, guessed values, and later phases cannot bypass the tool's validation.
Why
Tests that pass with the wrong data prove nothing. A material number that exists in DEV but was deleted in QAS turns a real regression into a spurious "data missing" error, and the actual bug slips through unnoticed. Preparing data honestly per landscape is what makes the entire suite trustworthy. Fabricating a value the SQL didn't return is worse than admitting the case is blocked — it lies to the audit trail.
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.
- 7d ago First seen · 305 lines · 82 tokens per session scan A 6ccc7460c144
prepare-data is a skill published in the GitHub repository marcellourbani/vscode_abap_remote_fs (388 stars, last pushed 5d ago), licensed MIT. It adds 82 tokens to every session and 7,027 once invoked, about $0.0004 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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