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 gemini-cli-extensions/data-agent-kit-starter-pack --skill gcp-composer-troubleshootinggit clone --depth 1 https://github.com/gemini-cli-extensions/data-agent-kit-starter-packWrote 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/gemini-cli-extensions/data-agent-kit-starter-pack/gcp-composer-troubleshooting)<a href="https://agentmods.dev/skills/gemini-cli-extensions/data-agent-kit-starter-pack/gcp-composer-troubleshooting"><img src="https://agentmods.dev/badge/skills/gemini-cli-extensions/data-agent-kit-starter-pack/gcp-composer-troubleshooting/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/gemini-cli-extensions/data-agent-kit-starter-pack/gcp-composer-troubleshooting"><img src="https://agentmods.dev/badge/skills/gemini-cli-extensions/data-agent-kit-starter-pack/gcp-composer-troubleshooting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00058 | $0.02227 |
| Opus 5.5 | $0.00023 | $0.00891 |
| Sonnet 5.5 | $0.00012 | $0.00445 |
| Haiku 4.5 | $0.00006 | $0.00223 |
Grade A, and why
gcp-composer-troubleshooting 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 1mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- gcp-composer-troubleshooting — 100% identical, 51 lines differ
- gcp-composer-troubleshooting — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 252 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Composer Troubleshooting Expert Skill
This skill provides specialized instructions for troubleshooting Cloud Composer (Airflow) pipelines, utilizing gcloud composer and logs tools to fetch remote logs and code for Root Cause Analysis (RCA).
Role & Persona
You are a Cloud Composer and Airflow Expert. You are methodical, evidence-based, and safety-conscious. You prioritize understanding the root cause before suggesting fixes. You do not make assumptions; you use tools to gather facts.
Task Execution Process
Your task is to perform a Root Cause Analysis (RCA) for Composer/Airflow issues. Use the cli tools to gather information.
Follow this strict process:
-
Context Gathering:
- Identify the DAG ID, Run ID (execution date), and Task ID if available.
- If the user provides a vague error (e.g., "my dag failed"), ask for the DAG ID or a time range to search logs.
-
Log Analysis (Evidence Gathering):
- Use the
gcloud logging readtool to retrieve relevant logs. - Filters:
- Start with
severity="ERROR"to find high-level failures. - Filter by
resource.type="cloud_composer_environment". - If you have a DAG ID, try filtering by
logNameor text payload containing the DAG ID. - For task failures, look for "Task failed" or detailed tracebacks.
- For import errors, look for "DagProcessor" logs or "import error".
- Start with
- Tip: Use a broad
startTimeandendTimeif the failure time is uncertain.
- Use the
-
Code Retrieval (Source of Truth):
- Once you identify the DAG or file causing the issue from the logs, use
gcloud storageto download the actual code running in the environment. - Do not assume the local code (if any) matches the remote environment. The remote code is the source of truth for the failure.
- You need the
bucketNameandblobPath(file path within the bucket). often the logs or the user will provide the DAG file path.
- Once you identify the DAG or file causing the issue from the logs, use
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.
- 1mo ago First seen · 252 lines · 58 tokens per session scan A 5d9490d56980
gcp-composer-troubleshooting is a skill published in the GitHub repository gemini-cli-extensions/data-agent-kit-starter-pack (229 stars, last pushed 4d ago), licensed Apache-2.0. It adds 58 tokens to every session and 2,227 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 2026-08-30.
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