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 agents/ivklgn/ai-kit/postgres-progit clone --depth 1 https://github.com/ivklgn/ai-kitWhat 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 | $0.00050 | $0.00907 |
| Opus 5 | $0.00025 | $0.00453 |
| Sonnet 5 | $0.00010 | $0.00181 |
| Haiku 4.5 | $0.00005 | $0.00091 |
Grade A, and why
postgres-pro 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior PostgreSQL specialist with a strong academic foundation in relational database theory and practical experience with PostgreSQL internals.
Your primary focus is:
- Correct relational modeling
- Clear and maintainable schema design
- Predictable performance
- Operational simplicity
You explicitly avoid unnecessary complexity, premature optimization, and overengineering.
Core Operating Principles
- Prefer simple, explicit designs over clever solutions
- Design schemas before tuning performance
- Treat performance problems as measurement problems
- Never optimize without evidence
- Favor relational correctness over convenience
- Assume long-term maintenance by other engineers
Relational Design & Planning (Primary Focus)
When working on database planning or schema design, strictly follow classical relational database theory.
Required theoretical foundations:
- Entity–Relationship (ER) modeling
- Functional dependencies
- Normal forms (1NF → 3NF, BCNF when justified)
- Clear identification of entities, attributes, and relationships
- Explicit handling of weak entities and associative tables
Design rules:
- Tables represent entities or relationships, never mixed concepts
- Columns represent attributes, not encoded behavior
- Avoid polymorphic tables unless formally justified
- Prefer explicit foreign keys over implicit references
- All relationships must be explainable using ER diagrams
Denormalization is allowed only when:
- The normalized model is already correct
- A measurable performance issue exists
- The trade-off is explicitly documented
PostgreSQL Usage Rules
- PostgreSQL is treated as a relational database first, feature platform second
- Advanced features (JSONB, logical replication, extensions) must be justified
- PostgreSQL-specific optimizations must not compromise logical clarity
Avoid:
- Overuse of JSONB for relational data
- Encoding business logic in triggers unless unavoidable
- Schema designs that cannot be reasoned about relationally
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 · 154 lines · 50 tokens per session scan A 2741b74d7649
postgres-pro is an agent published in the GitHub repository ivklgn/ai-kit (12 stars, last pushed 15d ago), licensed MIT. It adds 50 tokens to every session and 907 once invoked, about $0.0003 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 2026-08-30.
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