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 rileyhilliard/agentrc --skill managing-databasesgit clone --depth 1 https://github.com/rileyhilliard/agentrcWrote 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/rileyhilliard/agentrc/managing-databases)<a href="https://agentmods.dev/skills/rileyhilliard/agentrc/managing-databases"><img src="https://agentmods.dev/badge/skills/rileyhilliard/agentrc/managing-databases/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/rileyhilliard/agentrc/managing-databases"><img src="https://agentmods.dev/badge/skills/rileyhilliard/agentrc/managing-databases.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 | $0.00060 | $0.01344 |
| Opus 5.5 | $0.00024 | $0.00538 |
| Sonnet 5.5 | $0.00012 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
managing-databases 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 1mo 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Management
Decision guidance for PostgreSQL, DuckDB, and Parquet in hybrid storage architectures.
Contents
- When to use which database
- PostgreSQL quick reference
- DuckDB quick reference
- Parquet quick reference
- PGVector quick reference
- Cross-database conventions
- Performance debugging checklist
When to use which database
| Workload | Use | Why |
|---|---|---|
| Transactional (CRUD, users, sessions) | PostgreSQL | ACID, row-level locking, indexes |
| Analytical (aggregations, scans) | DuckDB | Columnar, vectorized, parallel |
| Data storage/interchange | Parquet | Compressed, columnar, portable |
| Metadata + relationships | PostgreSQL | Foreign keys, constraints |
| Ad-hoc exploration | DuckDB | Fast on Parquet, no ETL needed |
| Time-series with point lookups | PostgreSQL + partitioning | Partition pruning + indexes |
| Time-series analytics | DuckDB on Parquet | Scan performance |
| Vector similarity search | PostgreSQL + PGVector | HNSW/IVFFlat indexes, hybrid search |
| RAG / semantic search | PostgreSQL + PGVector | Embeddings + metadata in same DB |
Hybrid pattern example:
- PostgreSQL: transactional data, relationships, users (metadata)
- DuckDB + Parquet: analytical content, aggregations, time-series
PostgreSQL quick reference
Use for: Metadata, relationships, OLTP workloads, anything needing ACID.
Key decisions:
- Partition tables >100M rows or with retention requirements
- Index columns in WHERE/JOIN clauses, not everything
- Tune autovacuum for high-churn tables
See references/postgres-architecture.md for maintenance patterns. See references/postgres-querying.md for advanced query techniques.
What ships with it
8 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.
- references/duckdb-architecture.md 4.9 KB
- references/duckdb-querying.md 5.6 KB
- references/parquet-architecture.md 6.0 KB
- references/parquet-querying.md 6.7 KB
- references/pgvector-architecture.md 6.8 KB
- references/pgvector-querying.md 7.8 KB
- references/postgres-architecture.md 5.7 KB
- references/postgres-querying.md 7.4 KB
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.
- 1mo ago First seen · 149 lines · 60 tokens per session scan A f0a0e7235758
managing-databases is a skill published in the GitHub repository rileyhilliard/agentrc (3 stars, last pushed 8mo ago), licensed MIT. It adds 60 tokens to every session and 1,344 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 2026-08-31.
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