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 peteromallet/Arnold --skill pipeline-templategit clone --depth 1 https://github.com/peteromallet/ArnoldWrote 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/peteromallet/arnold/pipeline-template)<a href="https://agentmods.dev/skills/peteromallet/arnold/pipeline-template"><img src="https://agentmods.dev/badge/skills/peteromallet/arnold/pipeline-template/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/peteromallet/arnold/pipeline-template"><img src="https://agentmods.dev/badge/skills/peteromallet/arnold/pipeline-template.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 | $0.00016 | $0.00488 |
| Opus 5.5 | $0.00006 | $0.00195 |
| Sonnet 5.5 | $0.00003 | $0.00098 |
| Haiku 4.5 | $0.00002 | $0.00049 |
Grade A, and why
pipeline-template-reference 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.
How it starts
The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Pipeline Template Reference
The canonical scaffold is arnold_pipelines/_template/. It shows the minimum
required contract for a native-first pipeline:
build_pipeline()returnsarnold.pipeline.Pipelinewith a non-nullnative_program.- Module-level metadata with
driver=("native", "<kind>")andsupported_modescontaining"native". - Native declarations in
pipelines.pyusing@pipeline,@phase,@decision,parallel,compile_pipeline, andproject_graph.
Native-First Authoring Shape
For native-first authoring, organise components as package-local exports:
pipelines.py owns the native declaration topology. Supporting modules
(steps.py, prompts.py, policies.py, schemas.py, subflows.py)
may be imported by the native declaration, but the declaration itself
is the single source of topology truth.
The build_pipeline() entrypoint compiles the native program and projects
it into a Pipeline shell. The shell exists for discovery and validation.
The runtime executes the native program directly.
Dispatch Substrate Boundary
The native_program field is a dispatch substrate, not a final
compositional surface. It proves the package is executable by the native
runtime, but it does not lock in panel synthesis, join delegation,
parallel merge strategy, subpipeline ownership, or Capsule projection.
Those concerns belong to later Megaplan layers above the dispatch
boundary.
What NOT to Use
Do not use these patterns in new packages built from the template:
- Graph-first authoring with
arnold.workflow.Pipeline,Step,Route. - Native-as-opt-in or dual-mode (graph + native) packages — the template is native-first and single-mode.
_legacy.py, graph fallback builders, compatibility namespaces, shim packages, or temporary wrapper modules.--driver graphscaffolding or manual graph construction.- Hand-authored
WorkflowManifest,NativeProgrambuilder objects, or_forward_m2_m3graph objects inbuild_pipeline().
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 · 54 lines · 16 tokens per session scan A d74bbf4c349d
pipeline-template-reference is a skill published in the GitHub repository peteromallet/Arnold (98 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 488 once invoked, about $0.0001 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 2026-09-04.
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