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 agentmods add skills/artivilla/agents-config/databasenpx skills add artivilla/agents-config --skill databasegit clone --depth 1 https://github.com/artivilla/agents-configWhat 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 | $0.00072 | $0.01909 |
| Opus 5 | $0.00036 | $0.00955 |
| Sonnet 5 | $0.00014 | $0.00382 |
| Haiku 4.5 | $0.00007 | $0.00191 |
Grade A, and why
database 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 2d 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database
Add official Railway database services. These are maintained templates with pre-configured volumes, networking, and connection variables.
For non-database templates, see the templates skill.
When to Use
- User asks to "add a database", "add Postgres", "add Redis", etc.
- User needs a database for their application
- User asks about connecting to a database
- User says "add postgres and connect to my server"
- User says "wire up the database"
Decision Flow
ALWAYS check for existing databases FIRST before creating.
User mentions database
│
Check existing DBs first
(query env config for source.image)
│
┌────┴────┐
Exists Doesn't exist
│ │
│ Create database
│ (CLI or API)
│ │
│ Wait for deployment
│ │
└─────┬─────┘
│
User wants to
connect service?
│
┌─────┴─────┐
Yes No
│ │
Wire vars Done +
via env suggest wiring
skill
Check for Existing Databases
Before creating a database, check if one already exists.
For full environment config structure, see environment-config.md.
railway status --json
Then query environment config and check source.image for each service:
query environmentConfig($environmentId: String!) {
environment(id: $environmentId) {
config(decryptVariables: false)
}
}
The config.services object contains each service's configuration. Check source.image for:
ghcr.io/railway/postgres*orpostgres:*→ Postgresghcr.io/railway/redis*orredis:*→ Redisghcr.io/railway/mysql*ormysql:*→ MySQLghcr.io/railway/mongo*ormongo:*→ MongoDB
Available Databases
| Database | Template Code |
|---|---|
| PostgreSQL | postgres |
| Redis | redis |
| MySQL | mysql |
| MongoDB | mongodb |
Prerequisites
Get project context:
railway status --json
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 285 lines · 72 tokens per session scan A f67e2a8cf0c8
database is a skill published in the GitHub repository artivilla/agents-config (0 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 1,909 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
warehouse-init
Initialize warehouse schema discovery. Generates .astro/warehouse.md with all table metadata for instant lookups. Run once per project, refresh when schema changes. Use when user says "/astronomer-data:warehouse-init" or asks to set up data discovery.
analyzing-data
Queries the data warehouse with SQL and answers business questions about data. Use when answering anything that needs warehouse data - counts, metrics, trends, aggregations, joins across tables, data lookups, or ad-hoc SQL analysis (for example "who uses X", "how many Y", "show me Z", "find customers", "what is the…
tracing-upstream-lineage
Trace upstream data lineage. Use when the user asks where data comes from, what feeds a table, upstream dependencies, data sources, or needs to understand data origins.
checking-freshness
Quick data freshness check. Use when the user asks if data is up to date, when a table was last updated, if data is stale, or needs to verify data currency before using it.
profiling-tables
Deep-dive data profiling for a specific table. Use when the user asks to profile a table, wants statistics about a dataset, asks about data quality, or needs to understand a table's structure and content. Requires a table name.
aws-cloudformation-rds
Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups, subnet groups, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.