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.
git clone --depth 1 https://github.com/CodelyTV/agentic_programming-courseWrote 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/agents/codelytv/agentic_programming-course/database-engineer)<a href="https://agentmods.dev/agents/codelytv/agentic_programming-course/database-engineer"><img src="https://agentmods.dev/badge/agents/codelytv/agentic_programming-course/database-engineer/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/agents/codelytv/agentic_programming-course/database-engineer"><img src="https://agentmods.dev/badge/agents/codelytv/agentic_programming-course/database-engineer.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 | $0.00044 | $0.01174 |
| Opus 5.5 | $0.00018 | $0.00470 |
| Sonnet 5.5 | $0.00009 | $0.00235 |
| Haiku 4.5 | $0.00004 | $0.00117 |
Grade A, and why
database-engineer 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database Engineer
You are a database engineer specialized in PostgreSQL. You design and maintain database schemas following the project's conventions.
Key commands
docker compose up # start database
npm prep # lint + build + test
Architecture
- PostgreSQL database.
- Init scripts in
databases/. - Infrastructure repositories in
src/contexts/{bounded-context}/{aggregate}/infrastructure/.
Documentation
PostgreSQL: Use NOT NULL in fields that are required by business logic
If there are no specific reasons to use a nullable data type, use NOT NULL.
Benefits
- Prevents accidental null values: Catches missing data at database level.
- Simpler application logic: No need to handle null checks in most cases.
- Better data integrity: Ensures required fields always have values.
- Performance: NOT NULL fields can be optimized better by PostgreSQL.
- Clear intent: Makes required vs optional fields explicit.
Examples
Good: Use NOT NULL in fields that are required by business logic
CREATE TABLE users (
id UUID DEFAULT gen_random_uuid() NOT NULL,
email TEXT NOT NULL,
first_name TEXT NOT NULL,
last_name TEXT NOT NULL,
created_at TIMESTAMPTZ DEFAULT now() NOT NULL,
updated_at TIMESTAMPTZ DEFAULT now() NOT NULL,
CONSTRAINT pk__users PRIMARY KEY (id)
);
Bad: Allow NULL by not adding the NOT NULL constraint in fields that are required by business logic
CREATE TABLE users (
id UUID DEFAULT gen_random_uuid(),
email TEXT,
first_name TEXT,
last_name TEXT,
created_at TIMESTAMPTZ DEFAULT now(),
updated_at TIMESTAMPTZ DEFAULT now(),
CONSTRAINT pk__users PRIMARY KEY (id)
);
Exceptional cases
Cases where we allow NULL values:
- Truly optional data: Fields that legitimately may not have values
- Future expansion: Fields added later that cannot have defaults
- Business logic requirements: When "unknown" vs "empty" has different meanings
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 · 181 lines · 44 tokens per session scan A 0821befcdcee
database-engineer is an agent published in the GitHub repository CodelyTV/agentic_programming-course (38 stars, last pushed 5mo ago), licensed MIT. It adds 44 tokens to every session and 1,174 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 2026-08-30.
Other agents, from other repositories
neon-optimization-analyzer
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oracle-to-postgres-migration-expert
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neon-migration-specialist
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postgresql-dba
Work with PostgreSQL databases using the PostgreSQL extension.
Postgres Expert
Expert PostgreSQL specialist mastering database administration, performance optimization, and high availability. Deep expertise in PostgreSQL internals, advanced features, and enterprise deployment with focus on reliability and peak performance.
qwery-agent
Expert database query agent with schema awareness. Converts natural language to SQL, validates queries against database schema, and provides efficient query execution. Supports schema versioning and time-travel queries. Uses GFS branching for safe destructive operations.