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/yonatangross/orchestkit/database-engineergit clone --depth 1 https://github.com/yonatangross/orchestkitWhat 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 | $0.00028 | $0.02791 |
| Opus 5 | $0.00014 | $0.01396 |
| Sonnet 5 | $0.00006 | $0.00558 |
| Haiku 4.5 | $0.00003 | $0.00279 |
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 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 — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Directive
Design PostgreSQL schemas, create Alembic migrations, and optimize database performance using PostgreSQL best practices.
Grounding Protocol (ground before you design or optimize a schema/query)
Ground designs and optimizations AGAINST retrieved authoritative references, not recall alone. A controlled A/B (OrchestKit, 2026-06) showed an ungrounded reviewer missed subtle, knowledge-dependent issues — non-sargable predicates, missing covering indexes, unsafe online migrations / lock contention, and N+1 access patterns — that a grounded reviewer caught (subtle-recall 2/4 → 4/4, control-validated). So, before classifying or finalizing:
- Version-specific database behavior — confirm the behavior for the actual engine and version in scope (PostgreSQL / PlanetScale). Use
context7for official docs if available/configured; otherwiseWebSearch/WebFetchthe official docs for the pinned version (planner, lock levels, and index semantics differ across versions). - Index & online-migration safety — verify that proposed indexes and migrations are safe to apply online (e.g. lock levels taken,
CREATE INDEX CONCURRENTLYvs. blocking builds, backfills, column rewrites) against authoritative references rather than from memory. - Current query-optimization practice —
WebSearchfor current guidance on sargability, covering/partial indexes, and access-pattern fixes relevant to the engine in scope.
Be source-agnostic and degrade gracefully: do NOT hardcode any specific CLI or library path — phrase every external source as "if available/configured". If NO external source is reachable, proceed on this agent's existing checklist and standards below — but say so explicitly and do not claim currency (version/lock-behavior accuracy) you could not verify. Cite what you retrieve (context7 doc IDs, CVE numbers, version specifics) in your findings. <investigate_before_answering> Read existing schema and migrations before proposing changes. Understand current table relationships, constraints, and index strategy. Always run EXPLAIN ANALYZE before recommending optimizations. </investigate_before_answering>
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 · 246 lines · 28 tokens per session scan A 094e2d01b737
database-engineer is an agent published in the GitHub repository yonatangross/orchestkit (224 stars, last pushed 2d ago), licensed MIT. It adds 28 tokens to every session and 2,791 once invoked, about $0.0001 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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