db2

db2 is a skill for Claude Code, Codex from G1Joshi/Agent-Skills. It costs 16 tokens per session (351 once invoked), scanned A, original, MIT.

An enterprise relational database from IBM that stores structured data and is widely used on mainframes, as well as Linux, Unix, and Windows systems. It also supports data warehousing and analytics.

In plain words
What is it for?
Use it for mainframe databases, hybrid-cloud systems, analytical workloads, and migrations from compatible relational databases.
Why use it?
It helps teams run and modernise large, long-running business systems, including banking and insurance applications.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for mainframe databases, hybrid-cloud systems, analytical workloads, and migrations from compatible relational databases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/g1joshi/agent-skills/db2
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.

Any agent
npx skills add G1Joshi/Agent-Skills --skill db2
Clone the repo
git clone --depth 1 https://github.com/G1Joshi/Agent-Skills

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 db2

README.md
[![agentmods](https://agentmods.dev/badge/skills/g1joshi/agent-skills/db2/github.svg)](https://agentmods.dev/skills/g1joshi/agent-skills/db2)
Your own site
<a href="https://agentmods.dev/skills/g1joshi/agent-skills/db2"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/db2/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 db2

Your own site · 80×15
<a href="https://agentmods.dev/skills/g1joshi/agent-skills/db2"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/db2.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 351 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 $0.00016 $0.00351
Opus 5 $0.00008 $0.00176
Sonnet 5 $0.00003 $0.00070
Haiku 4.5 $0.00002 $0.00035

Measured 9d ago against content hash 938b7a6db0ae, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

db2 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 9d 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.

skills/databases/db2/SKILL.md · 45 lines

What it actually says

IBM Db2

Db2 is a family of data management products, including the relational database. It is famous for running on Mainframes (z/OS) but also runs on Linux/Unix/Windows (LUW).

When to Use

  • Legacy/Mainframe: The backbone of banking and insurance legacy systems.
  • Hybrid Cloud: IBM's "Cloud Pak for Data" strategy makes Db2 run anywhere (OpenShift/Kubernetes).
  • Analytics: Db2 Warehouse (formerly BLU Acceleration) offers column-store in-memory acceleration.

Core Concepts

BLU Acceleration

Columnar storage + In-memory computing. Drastically speeds up analytics queries without complex indexes.

pureScale

Clustering technology (similar to Oracle RAC) for unlimited scalability and high availability on distributed systems.

SQL Compatibility

Db2 has good compatibility with Oracle PL/SQL, making migrations easier.

Best Practices (2025)

Do:

  • Use In-Database AI (2025): Use watsonx.ai integration to run ML models or Vector similiarity search directly inside DB2.
  • Cloud Modernization: Move to Db2 on Cloud or containerized Db2 on OpenShift for easier management.
  • Administration Foundation: Use the new browser-based admin tools instead of the deprecated Data Studio.

Don't:

  • Don't ignore maintenance: Runstats (statistics collection) is critical for the DB2 optimizer to pick the right path.

References

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. 9d ago First seen · 45 lines · 16 tokens per session scan A 938b7a6db0ae

Subscribe to this mod's changes

db2 is a skill published in the GitHub repository G1Joshi/Agent-Skills (12 stars, last pushed 7mo ago), licensed MIT. It adds 16 tokens to every session and 351 once invoked, about $0.0001 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.