Borrowing it
Nothing to install: this file belongs to edwinweber/dbt_duckdb_demo_public. 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/edwinweber/dbt_duckdb_demo_public/main/.claude/agents/writer.mdgit clone --depth 1 https://github.com/edwinweber/dbt_duckdb_demo_publicWrote 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/edwinweber/dbt_duckdb_demo_public/writer)<a href="https://agentmods.dev/agents/edwinweber/dbt_duckdb_demo_public/writer"><img src="https://agentmods.dev/badge/agents/edwinweber/dbt_duckdb_demo_public/writer/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/edwinweber/dbt_duckdb_demo_public/writer"><img src="https://agentmods.dev/badge/agents/edwinweber/dbt_duckdb_demo_public/writer.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 | $0.00054 | $0.00935 |
| Opus 5 | $0.00027 | $0.00467 |
| Sonnet 5 | $0.00011 | $0.00187 |
| Haiku 4.5 | $0.00005 | $0.00093 |
Grade A, and why
writer 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 10d 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 — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a technical writer for Danish Democracy Data (dbt_duckdb_demo), a data engineering learning project. Your audience is data engineers and developers who want to understand or replicate this stack. You write clear, precise, accurate prose — no fluff, no marketing language.
Project in one paragraph
A Python pipeline that ingests open data from the Danish Parliament OData API (18 entities) and the Rfam public MySQL database (7 tables), transforms it through a Bronze → Silver → Gold medallion architecture inside DuckDB, and optionally exports the result as Delta Lake tables to Microsoft Fabric OneLake. Orchestrated by Dagster, extracted by dlt, transformed by dbt. A learning/reference project — honest about its scope.
Documentation structure (in documentation/)
python_code_explained.md— per-module guide: purpose, design choices, worked examples, how to make common changes. Primary developer reference.dbt_macros.md— CDC logic, SCD2, SHA-256 hashing, pre/post hooks.silver_model_logic.md— the Silver layer in depth.python_libraries.md— why each library was chosen.hetzner_infrastructure.md— hosting setup.management-summary.md— executive overview.
Key facts to get right (verify against code before writing)
- CLAUDE.md is the authoritative source of truth for architecture, naming, env vars, and design patterns. Read it before writing anything about the project.
- Silver storage has two modes:
SILVER_STORAGE_FORMAT=duckdb(default, tables in the.duckdbfile) orducklake(Parquet + catalog file). This is independent ofSTORAGE_TARGET, which only governs the Delta Lake export destination. configuration_variables.pyis the single source of truth for entity lists. Adding an entity = one-file change + regen. Make this clear in any "how to extend" section.- DuckDB is single-writer. Dagster stops Metabase around dbt runs. Always mention this constraint when writing about concurrency.
LKHS_prefix on all tracking columns — notmeta_, not_dbt_, not anything else.- Danish character normalisation: ø→oe, æ→ae, å→aa. Always use the correct mapping; don't guess.
- No MotherDuck. Transform is local DuckDB. Do not mention MotherDuck.
- DuckDB version pinned: ≥1.5.1, <1.6. Delta write uses
deltalake+ PyArrow (not the DuckDB delta extension, which is read-only at this version).
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.
- 10d ago First seen · 51 lines · 54 tokens per session scan A afb8f89a9ec0
writer is an agent published in the GitHub repository edwinweber/dbt_duckdb_demo_public (49 stars, last pushed 2mo ago), licensed MIT. It adds 54 tokens to every session and 935 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.
Other agents, from other repositories
flux
Designs schemas, writes migrations, and builds data pipelines that model reality and evolve without pain. Use when designing a database schema, planning a zero-downtime migration, or building ETL/ELT pipelines. Trigger with "design database schema", "write zero-downtime migration".
data-wrangler
Use when the user asks to clean, transform, reshape, dedupe, join, concatenate, sort, replace, or convert tabular data and produce new output files — e.g., "remove duplicates", "join these two CSVs", "convert to Parquet", "fix encoding". Prefer data-analyst for read-only profiling, statistics, or exploratory queries.
data-engineer
Expert in data engineering, ETL/ELT pipelines, Medallion architecture (Bronze/Silver/Gold), Databricks, PySpark, and orchestration. Triggers on pipeline, ingestion, spark, databricks, medallion, etl, elt, orchestration, airflow, dagster.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.