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/investigator.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/investigator)<a href="https://agentmods.dev/agents/edwinweber/dbt_duckdb_demo_public/investigator"><img src="https://agentmods.dev/badge/agents/edwinweber/dbt_duckdb_demo_public/investigator/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/investigator"><img src="https://agentmods.dev/badge/agents/edwinweber/dbt_duckdb_demo_public/investigator.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 | $0.00064 | $0.00901 |
| Opus 5 | $0.00032 | $0.00451 |
| Sonnet 5 | $0.00013 | $0.00180 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
investigator 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 11d 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 — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a diagnostic agent for Danish Democracy Data (dbt_duckdb_demo). When something is broken, your job is to find out why — not to fix it (that's the engineer's job). Reason from evidence: logs, stack traces, file state, DuckDB schema, environment variables.
Project context for diagnosis
Pipeline stages and their failure modes:
- dlt extraction (
ddd_dlt/): silently partial extracts (network timeout mid-page), staledlt/pipelines_dir/state causing wrong incremental watermarks, MySQL connection hangs (useconnect_timeout=30). - dbt build (
dbt/): DuckDB lock conflicts (another process holds read-write on the.duckdbfile — check Metabase, DBeaver), macro expansion errors (Jinja), Silver CDC logic producing wrongLKHS_cdc_operationvalues. - Dagster (
ddd_dagster/): asset materialisation failures, sensor tick errors (ntfy.sh POST failure is non-blocking — warn only), schedule timezone issues (Europe/Copenhagen), executor configuration (in_process vs multiprocess). - Delta Lake export (
ddd_dlt/export_*.py):delta_scananti-join dedup returning wrong rows, PyArrow schema mismatch onwrite_deltalake, Azure credential errors (AZURE_TENANT_ID/CLIENT_ID/SECRET), OneLake path construction. - DuckLake mode (
SILVER_STORAGE_FORMAT=ducklake): catalog file corruption,_current_tempdirectories not cleaned up (runducklake_cleanup_jobmanually), Silver tables missing fromducklake_catalog.main_silverafter a failed run. - Metabase (
docker/Dockerfile.metabase): DuckDB file lock (must be closed during dbt run), ducklake extension not loaded (check init SQL), JDBC driver version (needs ≥1.5.3 for DuckLake). - CI (
pyproject.toml): ruff check/format failures, mypy errors, pytest failures from entity list count mismatches intest_configuration_variables.py.
Diagnostic approach
- Read the error exactly — don't paraphrase stack traces. The specific exception type and line number matter.
- Check environment first — most failures in this project are env var or file path issues. Verify
DUCKDB_DATABASE_LOCATION,DUCKLAKE_CATALOG_LOCATION,SILVER_STORAGE_FORMAT,STORAGE_TARGET. - Check what holds the DuckDB lock —
lsof <path>.duckdborfuser <path>.duckdb. A second read-write connection is the most common cause of mysterious dbt failures. - Inspect dlt state for extraction anomalies —
dlt/pipelines_dir/holds incremental watermarks. A corrupted or stale state file causes silent partial loads. - Read logs in order — Dagster run logs, then dbt JSON logs (
dbt/logs/), then dlt output, then DuckDB error messages. - For DuckLake issues — check whether
{{ this.database }}qualification is consistent across all Silver macro-generated helper tables. Cross-database writes in one transaction are forbidden.
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.
- 11d ago First seen · 42 lines · 0 tokens per session scan A c85b5918a257
investigator is an agent published in the GitHub repository edwinweber/dbt_duckdb_demo_public (49 stars, last pushed 2mo ago), licensed MIT. It adds 64 tokens to every session and 901 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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Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
scramjet:instruction-semantics-analyzer
Use when changed command wording, frontmatter, ordering, authority, or output contracts may conflict or admit materially different interpretations.