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 cockroachdbgit 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/cockroachdb)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/cockroachdb"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/cockroachdb/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/cockroachdb"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/cockroachdb.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 | $0.00045 | $0.01114 |
| Opus 5.5 | $0.00018 | $0.00446 |
| Sonnet 5.5 | $0.00009 | $0.00223 |
| Haiku 4.5 | $0.00005 | $0.00111 |
Grade A, and why
cockroachdb 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 19d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CockroachDB
CockroachDB is a cloud-native, distributed SQL database. It survives disk, machine, rack, and even datacenter failures with zero downtime. It speaks PostgreSQL.
When to Use
- Global Distributed SQL: Multi-region enterprise applications requiring PostgreSQL compatibility with multi-region write latency optimization.
- Zero-Downtime Surviving Outages: Applications requiring automated failover and self-healing data survival across region or datacenter outages.
- Strict Serializable ACID Transactions: Systems requiring the highest isolation level (Serializable) to prevent phantom reads and write skews.
- Horizontal Scaling without Sharding: Scaling relational databases beyond single-instance limits without manual application-layer sharding.
Quick Start
-- Create a table with UUID primary key for distributed scale
CREATE TABLE accounts (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
balance DECIMAL(19,4)
);
-- Distributed Transaction
BEGIN;
UPDATE accounts SET balance = balance - 100 WHERE id = 'uuid-1';
UPDATE accounts SET balance = balance + 100 WHERE id = 'uuid-2';
COMMIT;
Core Concepts
Raft Consensus Ranges & Distributed Storage
Tables are automatically split into 64MB ordered contiguous chunks called Ranges, replicated across nodes via Raft:
[ Table: orders ]
├── Range 1 (Keys: 000-100) ──→ Replicated via Raft (Node 1, Node 2, Node 3)
└── Range 2 (Keys: 101-200) ──→ Replicated via Raft (Node 2, Node 3, Node 4)
Multi-Region Table Topologies (REGIONAL vs GLOBAL)
Optimizes data locality to keep data close to users and comply with data residency regulations (GDPR):
-- Multi-region database and table definition
ALTER DATABASE enterprise_crm SET PRIMARY REGION "us-east-1";
ALTER DATABASE enterprise_crm ADD REGION "eu-west-1";
ALTER DATABASE enterprise_crm ADD REGION "ap-southeast-1";
-- Regional table colocates rows in the user's home region
CREATE TABLE enterprise_crm.customers (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
region crdb_region NOT NULL,
full_name STRING,
email STRING
) LOCALITY REGIONAL BY ROW AS region;
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.
- 19d ago Changed 48a2b19f91db
- 23d ago Changed · +60 lines · +27 tokens per session 2c50f45e87da
- 1mo ago First seen · 62 lines · 18 tokens per session scan A 61badc03df85
cockroachdb is a skill published in the GitHub repository G1Joshi/Agent-Skills (15 stars, last pushed 20d ago), licensed MIT. It adds 45 tokens to every session and 1,114 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…
saas-multi-tenant
Design and implement multi-tenant SaaS architectures with RLS, tenant isolation, and PostgreSQL / Desain dan implementasikan arsitektur SaaS multi-tenant dengan RLS, isolasi tenant, dan PostgreSQL.
vector-db-rag-expert
Expert guide for high-performance Vector Databases, Deep RAG architectures, pgvector 0.8+ HNSW, Reciprocal Rank Fusion (RRF), Cross-Encoder Re-ranking, and Late Chunking / Panduan ahli Vector DB, arsitektur Deep RAG, pgvector HNSW, RRF, dan Re-ranking.
backup-restore
PostgreSQL backup and restore with pgBackRest — full/incremental/WAL, PITR, K8s CronJob scheduling, and restore verification.
db-performance
PostgreSQL query performance — EXPLAIN ANALYZE, index design, pgstatstatements, slow query detection, connection pool tuning.
postgres-operations
PostgreSQL operational runbooks — health checks, vacuum, bloat, locks, PITR, connection pool management.