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 vaquarkhan/data-engineering-agent-skills --skill mainframe-modernization-and-data-offloadgit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skillsWrote 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/vaquarkhan/data-engineering-agent-skills/mainframe-modernization-and-data-offload)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/mainframe-modernization-and-data-offload"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/mainframe-modernization-and-data-offload/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.
<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/mainframe-modernization-and-data-offload"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/mainframe-modernization-and-data-offload.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00067 | $0.00671 |
| Opus 5 | $0.00034 | $0.00336 |
| Sonnet 5 | $0.00013 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
mainframe-modernization-and-data-offload 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 8d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mainframe Modernization And Data Offload
Overview
Use this skill when a modernization effort involves mainframe systems, batch schedules, and legacy data structures rather than only modern ETL tooling. It helps agents design offload, replication, contract mapping, coexistence, reconciliation, and cutover paths for mainframe-origin data.
When to Use
- modernizing
COBOL,JCL,VSAM,IMS, orDB2 for z/OSdata flows - offloading mainframe data to lakes, warehouses, or downstream APIs
- mapping copybooks and legacy record layouts into modern contracts
- designing coexistence between batch mainframe outputs and modern platforms
- planning phased cutover, replay, and reconciliation for legacy estates
Do not treat mainframe modernization as only a transport problem. Semantics, batch windows, restart behavior, and operational dependencies matter.
Workflow
-
Inventory the legacy behavior. Capture:
- source systems
- copybooks or record layouts
- batch schedules
- restart and rerun behavior
- downstream consumers
-
Define the modernization target. Decide:
- offload versus replication versus coexistence
- target storage and serving platforms
- contract and schema mapping
- latency and batch-window expectations
-
Design parity and reconciliation. Require:
- source-to-target field mapping
- control totals and reconciliation
- correction and replay behavior
- cutover acceptance criteria
-
Plan coexistence and cutover. Cover:
- dual-run period
- dependent consumer migrations
- backout plan
- ownership and incident routing during cutover
-
Validate operational readiness. Check restart, failure recovery, performance windows, and support responsibilities before moving critical consumers.
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "We only need to copy the files out." | Mainframe jobs often encode business rules, restart behavior, and sequencing that must be preserved or redesigned. |
| "Schema mapping is straightforward once we read the copybook." | Field semantics, packed decimals, dates, and code tables often require careful domain translation. |
| "We can switch consumers after one successful run." | Mainframe modernization usually needs parity evidence and a deliberate coexistence period. |
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.
- 8d ago First seen · 79 lines · 67 tokens per session scan A c9e97122bec6
mainframe-modernization-and-data-offload is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 671 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 2026-09-03.
Other skills, from other repositories
event-store-design
Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
cqrs-implementation
Implement Command Query Responsibility Segregation for scalable architectures. Use when separating read and write models, optimizing query performance, or building event-sourced systems.
supabase-cli
This skill should be used when user asks to "use supabase CLI", "supabase init", "supabase start", "run migrations", "deploy edge functions", "manage Supabase project", or works with the supabase command-line tool for local development and project management.
supabase-js
This skill should be used when user asks to "use supabase-js", "query Supabase database", "supabase auth", "supabase storage", "supabase realtime", "supabase edge functions", or works with the @supabase/supabase-js JavaScript/TypeScript SDK.
durable-objects
Build, debug, or review Cloudflare Durable Objects code for persistent state and coordination.
architect/data-api-design
A guide to designing data models and application programming interfaces (APIs), which are the rules software uses to exchange data.