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 lucaspressi/claudekit-engineer --skill databasesgit clone --depth 1 https://github.com/lucaspressi/claudekit-engineerWrote 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/lucaspressi/claudekit-engineer/databases)<a href="https://agentmods.dev/skills/lucaspressi/claudekit-engineer/databases"><img src="https://agentmods.dev/badge/skills/lucaspressi/claudekit-engineer/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/lucaspressi/claudekit-engineer/databases"><img src="https://agentmods.dev/badge/skills/lucaspressi/claudekit-engineer/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 | $0.00042 | $0.00799 |
| Opus 5.5 | $0.00017 | $0.00320 |
| Sonnet 5.5 | $0.00008 | $0.00160 |
| Haiku 4.5 | $0.00004 | $0.00080 |
Grade A, and why
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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
27 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.
- analytics.md 5.3 KB
- db-design.md 6.3 KB
- incremental-etl.md 5.4 KB
- references/mongodb-aggregation.md 9.1 KB
- references/mongodb-atlas.md 9.1 KB
- references/mongodb-crud.md 8.2 KB
- references/mongodb-indexing.md 10 KB
- references/postgresql-administration.md 12 KB
- references/postgresql-performance.md 11 KB
- references/postgresql-psql-cli.md 10 KB
- references/postgresql-queries.md 9.9 KB
- scripts/.coverage 52 KB
- scripts/db_backup.py 16 KB runs code
- scripts/db_migrate.py 14 KB runs code
- scripts/db_performance_check.py 16 KB runs code
- scripts/requirements.txt 558 B
- scripts/tests/coverage-db.json 46 KB
- scripts/tests/requirements.txt 69 B
- scripts/tests/test_db_backup.py 11 KB runs code
- scripts/tests/test_db_migrate.py 9.3 KB runs code
- scripts/tests/test_db_performance_check.py 12 KB runs code
- stacks/bigquery.md 5.1 KB
- stacks/d1_cloudflare.md 3.4 KB
- stacks/mysql.md 5.5 KB
- stacks/postgres.md 5.8 KB
- stacks/sqlite.md 6.4 KB
- transactional.md 4.7 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 · 84 lines · 42 tokens per session scan A cade02f05984
databases is a skill published in the GitHub repository lucaspressi/claudekit-engineer (6 stars, last pushed 8mo ago), with no licence file. It adds 42 tokens to every session and 799 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 2026-09-04.
Other skills, from other repositories
ring:mapping-service-resources
Mapping a Go service's Service -> Module -> Resource hierarchy for dispatch-layer registration: detects modules and per-module PostgreSQL/MongoDB/RabbitMQ resources, database names, and shared databases, generates MongoDB index migration pairs (.up.json/.down.json), detects existing Postgres migrations, emits an HTML…
fastapi-init-skill
A tool that creates a complete FastAPI web-service starting point, including database choices, login protection, file uploads, streaming responses, API documentation, and start or restart scripts.
database-expert
Advanced database design and administration for PostgreSQL, MongoDB, and Redis. Use when designing schemas, optimizing queries, managing database performance, or implementing data patterns.
database-migrator
Migrates databases between providers (Postgres, MySQL, Supabase, PlanetScale, MongoDB). Reads source schema, generates migration scripts, handles data type mapping, foreign keys, indexes, triggers, stored procedures. Validates migration with row counts and checksums. Generates migration-plan.md with step-by-step…
database-schema-designer
Designs relational and document database schemas from requirements or an existing app - tables and collections, keys, relationships, constraints, indexes driven by real query patterns, ERDs, and reversible migration scripts - with PostgreSQL (including Supabase) as the default and MySQL, SQLite, and MongoDB supported.…
agent-database-expert
Specialist subagent: Expert database architect and engineer for PostgreSQL, MongoDB, Redis, and all major databases. Use when designing schemas, optimizing queries, planning migrations, implementing caching, or troubleshooting database performance.