Borrowing it
Nothing to install: this file belongs to colossus-lab/openarg_backend. 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/colossus-lab/openarg_backend/main/.claude/commands/debug-pipeline.mdgit clone --depth 1 https://github.com/colossus-lab/openarg_backendWrote 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/commands/colossus-lab/openarg_backend/debug-pipeline)<a href="https://agentmods.dev/commands/colossus-lab/openarg_backend/debug-pipeline"><img src="https://agentmods.dev/badge/commands/colossus-lab/openarg_backend/debug-pipeline/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/commands/colossus-lab/openarg_backend/debug-pipeline"><img src="https://agentmods.dev/badge/commands/colossus-lab/openarg_backend/debug-pipeline.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 | $0.00000 | $0.01001 |
| Opus 5.5 | $0.00000 | $0.00400 |
| Sonnet 5.5 | $0.00000 | $0.00200 |
| Haiku 4.5 | $0.00000 | $0.00100 |
Grade A, and why
debug-pipeline 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug backend pipeline: $ARGUMENTS
Diagnose the described problem in the scraper → embedding → collector → analyst pipeline. Follow this checklist:
Base infrastructure
- PostgreSQL running:
make db.upor check docker (docker ps | grep postgres) - Redis running: verify connectivity on port 6381
- Migrations applied:
make db.migrate - Environment variables:
OPENAI_API_KEY,DATABASE_URL,CELERY_BROKER_URL - Workers active: check in Flower (
make flower→ http://localhost:5556)
Scraper (src/app/infrastructure/celery/tasks/scraper_tasks.py)
-
scrape_catalog(portal)receives a valid portal (datos_gob_ar, caba, etc.) - The corresponding
IDataSourceadapter is registered in Dishka -
fetch_catalog()returnsCatalogEntry[]— is the CKAN portal responding? - Upsert to
datasetsworks (check UNIQUE constraint on source_id + portal) - Dispatches
index_dataset_embeddingfor each dataset - If failing: check worker-scraper logs, verify HTTPX timeout
Embedding (src/app/infrastructure/celery/tasks/embedding_tasks.py + scraper_tasks.py)
-
index_dataset_embedding(dataset_id)receives a valid UUID - The dataset exists in the
datasetstable - 3 chunks are generated: main, columns, contextual
- OpenAI embedding API responds (verify
OPENAI_API_KEY) - Chunks are saved in
dataset_chunkswith 1536-dim embedding - HNSW index works:
SELECT * FROM dataset_chunks ORDER BY embedding <=> $1 LIMIT 5 - If failing: check retries (max 3), review worker-embedding logs
Collector (src/app/infrastructure/celery/tasks/collector_tasks.py)
-
collect_dataset(dataset_id)downloads the file fromdownload_url - Format is supported (CSV, JSON, XLSX, XLS)
- Pandas parses correctly (check encoding, separators)
- Cache table
cache_{id}is created in PostgreSQL -
cached_datasetsis updated: status downloading → ready -
datasets.is_cached = trueandrow_countupdated - Row limit: 500k max
- If failing: check download URL, file format, worker-collector logs
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 · 83 lines · 0 tokens per session scan A f7e738043678
debug-pipeline is a command published in the GitHub repository colossus-lab/openarg_backend (150 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,001 tokens. 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.
debug-pipeline compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| debug-pipelinecolossus-lab/openarg_backend | Command | 150 | 3d ago | MIT | A | 0 | Claude Code |
| qa-changesOpenHands/extensions | Command | 176 | yesterday | MIT | A | 63 | Claude Code |
| react-nativegetsentry/toolkit | Command | 957 | yesterday | none | A | 0 | Claude Code |
| auditar-cascadingluanpdd/kit-mcp | Command | 5 | 4d ago | MIT | A | 54 | Claude Code |
| http-serviceMadAppGang/magus | Command | 14 | yesterday | MIT | A | 27 | Claude Code |
| doctordoncheli/don-cheli-sdd | Command | 59 | 2mo ago | Apache-2.0 | A | 76 | Claude Code |
| doctorfatihkan/badi | Command | 7 | 1mo ago | MIT | A | 0 | Claude Code |