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 saski/arnesto --skill gcp-pipeline-orchestrationgit clone --depth 1 https://github.com/saski/arnestoWrote 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/saski/arnesto/gcp-pipeline-orchestration)<a href="https://agentmods.dev/skills/saski/arnesto/gcp-pipeline-orchestration"><img src="https://agentmods.dev/badge/skills/saski/arnesto/gcp-pipeline-orchestration/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/saski/arnesto/gcp-pipeline-orchestration"><img src="https://agentmods.dev/badge/skills/saski/arnesto/gcp-pipeline-orchestration.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 | $0.00076 | $0.04048 |
| Opus 5 | $0.00038 | $0.02024 |
| Sonnet 5 | $0.00015 | $0.00810 |
| Haiku 4.5 | $0.00008 | $0.00405 |
Grade A, and why
gcp-pipeline-orchestration 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.
This is a copy
95% identical to gcp-pipeline-orchestration — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 416 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mandatory Reference Routing
If relevant, call the associated reference file(s) before you take actions. Refer to the table below to determine which reference file to retrieve in different scenarios involving specific functions. [!IMPORTANT]: DO NOT GUESS filenames. You MUST only use the exact paths provided below.
| Function/Use Case | Required Reference File | Capabilities & Intent Keywords |
|---|---|---|
| orchestration-pipelines schema | references/orchestration-pipelines-schema.md |
orchestrate, generate, create, update |
How to use this skill
Orchestration pipelines require creating two files to ensure a complete and deployable pipeline:
Orchestration File(e.g.,orchestration-pipeline.yaml,test-pipeline.yaml): Defines the pipeline's logic, tasks, and schedule. IMPORTANT: Check if adeployment.yamlfile exists and references an existing orchestration file. If it does, you must update the existing orchestration file (e.g.,test_pipeline.yaml) instead of creating a new one. The filename can be customized but must be referenced in thedeployment.yamlfile.deployment.yaml: Defines the environment-specific configurations.(e.g.,dev,prod).deployment.yamlshould only exists in the repository root and must be nameddeployment.yaml
-
All files should always be maintained together. And all files should be placed on the root of the workspace folder.
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This skill is helpful to create or update configuration files to orchestrate data pipelines.
How to use this skill
Step 1: Assess Orchestration Pipeline Status and Initialize if Necessary
Examine the repository's root directory for a deployment.yaml file.
- Check for existing setup: The absence of
deployment.yamlindicates that orchestration has not been set up. - Determine if initialization is required: Initialization is required if
deployment.yamlis missing. you MUST run theinitcommand in Step 3 to scaffold the project ifdeployment.yamlis missing. Do NOT create the files manually. - Pipeline Name: If initialization is needed, ask the user for the pipeline name. If user hasn't provided the orchestration pipeline name, name should be "orchestration_pipeline"
- Environment Name: If initialization is needed, you MUST ask the user for the environment name. If the user does not provide it, use dev as the default.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 416 lines · 76 tokens per session scan A 496fb43d4b5f
gcp-pipeline-orchestration is a skill published in the GitHub repository saski/arnesto (5 stars, last pushed today), licensed Unlicense. It adds 76 tokens to every session and 4,048 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to gcp-pipeline-orchestration, differing in 3 lines, and is treated as a copy.
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