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 G1Joshi/Agent-Skills --skill db2git clone --depth 1 https://github.com/G1Joshi/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/g1joshi/agent-skills/db2)<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.
<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>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 | $0.00046 | $0.01168 |
| Opus 5.5 | $0.00018 | $0.00467 |
| Sonnet 5.5 | $0.00009 | $0.00234 |
| Haiku 4.5 | $0.00005 | $0.00117 |
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 26d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Mission-Critical Enterprise Systems: Running core banking, financial transaction processing, and mainframe legacy enterprise workloads.
- PureXML & Hybrid Relational Workloads: Storing and indexing hierarchical XML and JSON documents alongside relational SQL tables.
- IBM z/OS Mainframe & Linux/Power Integration: Interfacing with enterprise IBM infrastructure with absolute data durability.
- High Availability Disaster Recovery (HADR): Mission-critical zero-data-loss failover architectures across physical datacenters.
Quick Start
-- Minimal Db2 Table Creation with Index
CREATE TABLE HR.EMPLOYEES (
EMP_ID INT NOT NULL GENERATED ALWAYS AS IDENTITY (START WITH 1000 INCREMENT BY 1),
FIRST_NAME VARCHAR(50) NOT NULL,
LAST_NAME VARCHAR(50) NOT NULL,
DEPARTMENT VARCHAR(50),
HIRE_DATE DATE DEFAULT CURRENT DATE,
SALARY DECIMAL(10,2),
PRIMARY KEY (EMP_ID)
);
CREATE INDEX HR.IDX_EMP_DEPT ON HR.EMPLOYEES (DEPARTMENT, SALARY DESC);
Core Concepts
Table Spaces & Storage Groups Architecture
Fine-grained control over physical storage containers, buffer pools, and disk layouts:
-- Create Enterprise Storage Space
CREATE TABLESPACE TS_ORDERS
PAGESIZE 32K
MANAGED BY AUTOMATIC STORAGE
BUFFERPOOL BP32K;
CREATE TABLE ENTERPRISE.ORDERS (
ORDER_ID BIGINT NOT NULL GENERATED ALWAYS AS IDENTITY (START WITH 1000, INCREMENT BY 1),
CUSTOMER_ID VARCHAR(32) NOT NULL,
ORDER_DATE TIMESTAMP NOT NULL DEFAULT CURRENT TIMESTAMP,
TOTAL_AMOUNT DECIMAL(15,2) NOT NULL,
CONSTRAINT PK_ORDERS PRIMARY KEY (ORDER_ID)
) IN TS_ORDERS;
pureQuery & Static SQL Execution
Pre-compiles and optimizes SQL queries into static execution plans for maximum mainframe execution efficiency:
-- Optimized Stored Procedure
CREATE OR REPLACE PROCEDURE GET_CUSTOMER_SUMMARY (
IN p_customer_id VARCHAR(32),
OUT p_total_orders INT,
OUT p_total_spend DECIMAL(15,2)
)
LANGUAGE SQL
BEGIN
SELECT COUNT(*), COALESCE(SUM(TOTAL_AMOUNT), 0.0)
INTO p_total_orders, p_total_spend
FROM ENTERPRISE.ORDERS
WHERE CUSTOMER_ID = p_customer_id;
END@
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.
- 26d ago Changed 6de74cf84b2e
- 1mo ago Changed · +82 lines · +30 tokens per session 948c550c1425
- 1mo ago First seen · 45 lines · 16 tokens per session scan A 938b7a6db0ae
db2 is a skill published in the GitHub repository G1Joshi/Agent-Skills (15 stars, last pushed 26d ago), licensed MIT. It adds 46 tokens to every session and 1,168 once invoked, about $0.0002 per session on Opus 5.5. 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
deprecation-and-migration
Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when migrating a database schema in production, such as renaming or dropping a column without downtime (expand/contract). Use when deciding whether to maintain or sunset…
awesome-database-audit
Read-only audit of a database layer: schema anti-patterns, query and index fit, integrity, concurrency, migrations, tenancy, with a verdict. Use when asked to review a schema, migrations or data model.
data-engineering
Guides data pipeline design, ETL/ELT workflows, schema evolution, and data quality assurance. Use when building data pipelines, designing data warehouses, migrating schemas, or ensuring data integrity across systems. Use when you need reliable, testable, and observable data flows.
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high…
observability-and-instrumentation
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.