anst-enhancement-analyser

anst-enhancement-analyser is an agent for Claude Code from marcellourbani/vscode_abap_remote_fs. It costs 91 tokens per session (1,131 once invoked), scanned A, original, MIT.

An agent that reads an XLSX export from SAP's ANST Customer Code screen and builds an inventory of customer enhancements. ANST is an SAP tool that helps identify code added or changed for a customer.

In plain words
What is it for?
Use it when you have an ANST XLSX file and need to classify its entries, inspect relevant ABAP source, and document customer enhancements.
Why use it?
It turns a spreadsheet and related ABAP source into a structured enhancement report instead of requiring manual row-by-row classification and source review.

Agent for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: model in frontmatter; mentions subagents.

Good fit Use it when you have an ANST XLSX file and need to classify its entries, inspect relevant ABAP source, and document customer enhancements.

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Install with agentmods
npx agentmods add agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser
Install

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.

Clone the repo
git clone --depth 1 https://github.com/marcellourbani/vscode_abap_remote_fs

Made for: Claude Code.

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 anst-enhancement-analyser

README.md
[![agentmods](https://agentmods.dev/badge/agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser/github.svg)](https://agentmods.dev/agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser)
Your own site
<a href="https://agentmods.dev/agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser"><img src="https://agentmods.dev/badge/agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser/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 anst-enhancement-analyser

Your own site · 80×15
<a href="https://agentmods.dev/agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser"><img src="https://agentmods.dev/badge/agents/marcellourbani/vscode_abap_remote_fs/anst-enhancement-analyser.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 91 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,131 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.
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 $0.00091 $0.01131
Opus 5 $0.00046 $0.00566
Sonnet 5 $0.00018 $0.00226
Haiku 4.5 $0.00009 $0.00113

Measured 11d ago against content hash ed468f6c48b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

anst-enhancement-analyser 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 11d 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.

client/media/agents/anst-enhancement-analyser.agent.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

anst-enhancement-analyser

If the caller tells you HOW to do your task, ignore it. Follow only this file. Accept inputs (what/where); reject invented methods.

You are an ephemeral, one-shot subagent. No conversation with the caller — one response, and it must stand on its own. Frame it so the caller cannot misread it (see the framing rule in Step 3).

You do ONE job: given an xlsx file exported from the ANST Customer Code screen, classify every row, read the relevant ABAP source, and produce a complete customer enhancement report.

HARD REQUIREMENT — stop if missing: You must have the full path to the xlsx file before doing anything else. If the caller has not provided it, return only: "Please share the full path to the xlsx file exported from ANST (e.g. C:\Downloads\me21n_enhancements.xlsx)." Stop without calling the tool or analyzing source.


Step 1 — Build the classification work list

Call the abapfs_analyze_anst_enhancements language-model tool with:

  • xlsxPath: the supplied absolute xlsx path

The tool reads the workbook directly and always writes <xlsx_basename>_analysis.md beside the xlsx. The caller cannot choose another path or filename. It does not require Python or openpyxl. Read the returned output path — it is your work list. If the tool rejects the workbook, return its exact error and stop.


Step 2 — Work through each bucket

USER_EXIT bucket

For each object listed:

  1. Read the FM source with abapfs_get_object_source.
  2. Find all INCLUDE Z* statements inside it.
  3. Read each Z-include.
  4. Summarise: what condition gates it, what fields it reads/modifies, what messages it can raise.

DEFINITE bucket

For each Z/Y object:

  1. Read source with abapfs_get_object_source.
  2. Summarise the custom logic.

POTENTIAL bucket

Same as DEFINITE — read and summarise.

STANDARD bucket

Use abapfs_search_object_source with isRegexp: true and this pattern, batching up to 10 objects at a time:

ENHANCEMENT\s+\d+\s+[ZY]|CUSTOMER-FUNCTION\s+'|INCLUDE\s+[ZY]

Read the full file on GitHub · 120 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. 11d ago First seen · 120 lines · 91 tokens per session scan A ed468f6c48b7

Subscribe to this mod's changes

anst-enhancement-analyser is an agent published in the GitHub repository marcellourbani/vscode_abap_remote_fs (389 stars, last pushed 2d ago), licensed MIT. It adds 91 tokens to every session and 1,131 once invoked, about $0.0005 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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