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 skills add BauplanLabs/bauplan-skills --skill bauplan-debug-and-fix-pipelinegit clone --depth 1 https://github.com/BauplanLabs/bauplan-skillsWrote 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/skills/bauplanlabs/bauplan-skills/bauplan-debug-and-fix-pipeline)<a href="https://agentmods.dev/skills/bauplanlabs/bauplan-skills/bauplan-debug-and-fix-pipeline"><img src="https://agentmods.dev/badge/skills/bauplanlabs/bauplan-skills/bauplan-debug-and-fix-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/skills/bauplanlabs/bauplan-skills/bauplan-debug-and-fix-pipeline"><img src="https://agentmods.dev/badge/skills/bauplanlabs/bauplan-skills/bauplan-debug-and-fix-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Memory Poisoning · line 136 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
- medium Excessive Agency · line 181 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00041 | $0.04672 |
| Opus 5 | $0.00020 | $0.02336 |
| Sonnet 5 | $0.00008 | $0.00934 |
| Haiku 4.5 | $0.00004 | $0.00467 |
Grade A, and why
bauplan-debug-and-fix-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 today.
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 — 418 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug and Fix Pipeline
What This Skill Does
A Bauplan pipeline job has failed. This skill walks through a structured diagnosis and repair: pin the exact state that caused the failure, collect evidence, find the root cause, apply a minimal fix, and confirm the fix works.
The core principle is evidence first, changes second — never guess at a fix before understanding what broke and why.
When to Use This Skill
Use this when:
- A
bauplan runhas failed and you need to understand why - You have a failed job ID, a branch name with a broken run, or a time window to search for failures
- You want to fix the pipeline and verify the fix against the exact data state that caused the failure
What You'll Need
At least one of:
- A Bauplan job ID (preferred)
- A Bauplan branch name where the failure happened
- A time window to search for failed jobs
- A local path to the pipeline project directory
If none are provided, the skill will try to infer from context. If ambiguous, it will ask.
Workflow at a Glance
Step 0 Setup
Confirm Bauplan connectivity, check for Git, create output directories.
Step 1 Pin the failing state
Extract the branch, commit hash, and error message from the failed job.
→ Write job report
Step 2 Create a debug branch
Branch from the exact failing ref so you see the same data the job saw.
Step 3 Collect evidence and find root cause
Inspect schemas, sample data, and trace upstream until you find
the model whose inputs are clean but whose output is broken.
→ Write data snapshot reports as you go
Step 4 Apply a minimal fix
Create a Git debug branch, make the smallest change that addresses
the root cause. One logical change per commit.
Step 5 Rerun and verify
Re-execute the pipeline on the debug branch and confirm the fix works.
→ Write summary report
The skill produces three types of reports in debug/: a job report, data snapshots, and a final summary. These are the deliverables — they document what happened, what was found, and what was changed.
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.
- today Changed b9c556cf82cc
- yesterday Changed · +20 lines f63ba977cd6a
- 11d ago First seen · 398 lines · 41 tokens per session scan A 80fe3bab4045
bauplan-debug-and-fix-pipeline is a skill published in the GitHub repository BauplanLabs/bauplan-skills (16 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 4,672 once invoked, about $0.0002 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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