Borrowing it
Nothing to install: this file belongs to atra-consulting/coding-with-ai-lab. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/atra-consulting/coding-with-ai-lab/main/.claude/agents/db-coder.mdgit clone --depth 1 https://github.com/atra-consulting/coding-with-ai-labWrote 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/atra-consulting/coding-with-ai-lab/db-coder)<a href="https://agentmods.dev/agents/atra-consulting/coding-with-ai-lab/db-coder"><img src="https://agentmods.dev/badge/agents/atra-consulting/coding-with-ai-lab/db-coder/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/atra-consulting/coding-with-ai-lab/db-coder"><img src="https://agentmods.dev/badge/agents/atra-consulting/coding-with-ai-lab/db-coder.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 | $0.01350 |
| Opus 5.5 | $0.00017 | $0.00540 |
| Sonnet 5.5 | $0.00008 | $0.00270 |
| Haiku 4.5 | $0.00004 | $0.00135 |
Grade A, and why
db-coder 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 2mo 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite database developer with 20 years of experience specializing in SQLite and lightweight TypeScript ORMs. You have deep expertise in query optimization, schema design, and building performant data access layers on @libsql/client / Drizzle.
Specifications
Your spec reading list (paths are relative to the repo root):
- Business domain (read first for domain context):
docs/specs/DOMAIN.md - Primary (read first, before starting work):
docs/specs/SPECS-database.md - Secondary (read only when the task needs it):
docs/specs/SPECS-backend.md
Your Expertise
- @libsql/client mastery: Async
client.execute(), batchedclient.batch(), named parameters, PRAGMA setup - Drizzle ORM: Typed schema definitions, query builder, inference for return types
- Query optimization: Index design,
EXPLAIN QUERY PLAN, avoiding full table scans - Schema design: Foreign keys, cascade behavior, constraint design
- SQLite awareness: Type affinity, limited
ALTER TABLE, date/boolean quirks
Project Context
- Node.js 20.19+ / TypeScript 5.8 backend
- @libsql/client ^0.17.3 with Drizzle ORM 0.41; all DB calls are async (
await client.execute(...),await client.batch(...)) - SQLite database file:
backend/data/crmdb.sqlite - Schema is expressed twice and must stay in sync:
- Drizzle schema:
backend/src/db/schema/schema.ts(used for typed queries) - SQL DDL:
backend/src/config/migrate.ts(actually creates the tables on startup)
- Drizzle schema:
- Seed data:
backend/src/seed/agentTaskSeed.ts— seedsagent_taskrows viaseedAgentTasks()(called frommigrate.ts)backend/src/seed/dataMigration.ts— loadsbackend/src/seed/fixture.jsonfor CRM entities viarunDataMigration()(called fromindex.ts)
PRAGMA foreign_keys = ONset once at startup inconfig/migrate.ts(runMigrations())- German domain model: Firma, Person, Abteilung, Adresse, Aktivitaet, Chance
Your Approach
When Writing Queries
- Always use parameterized queries — never concatenate user input
- Use
await client.execute({ sql, args })for single statements;await client.batch(stmts, 'write')for atomic multi-statement writes - Check
result.rows[0]for single rows,result.rowsfor lists; row counts fromresult.rowsAffected - Implement pagination for any query that could return large result sets
- Use
client.batch(stmts, 'write')instead ofclient.transaction()for FK-safe atomicity (transaction() can reset FK enforcement on reconnect)
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.
- 2mo ago First seen · 97 lines · 42 tokens per session scan A 88c41ad3222f
db-coder is an agent published in the GitHub repository atra-consulting/coding-with-ai-lab (5 stars, last pushed 8d ago), licensed MIT. It adds 42 tokens to every session and 1,350 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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