ComposablePipelines: Skill for Claude Code

.claude/skills/composable-pipelines/SKILL.md

composable-pipelines is a skill for Claude Code from MacPaw/ComposablePipelines. It costs 0 tokens per session (1,586 once invoked), scanned A, original, Apache-2.0.

A Swift package for defining AI workflows as pipelines, compiling them into execution graphs, and running them through an executor you provide. A pipeline is a sequence or graph of tasks, such as model calls, loops, and checks.

In plain words
What is it for?
Use it to write or debug Swift pipelines containing models, guardrails, loops, repeated tasks, client tasks, and shared state, then compile and run them.
Why use it?
It helps organize data flow between AI steps and makes the workflow structure observable and encodable.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: positional $N argument.

This is MacPaw/ComposablePipelines's own configuration. It tells Claude Code how to work on ComposablePipelines itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ComposablePipelines configures →

Reuse

Borrowing it

Nothing to install: this file belongs to MacPaw/ComposablePipelines. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/MacPaw/ComposablePipelines/main/.claude/skills/composable-pipelines/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/MacPaw/ComposablePipelines

Made for: Claude Code.

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README.md
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Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,586 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.01586
Opus 5.5 $0.00000 $0.00634
Sonnet 5.5 $0.00000 $0.00317
Haiku 4.5 $0.00000 $0.00159

Measured 2mo ago against content hash 1192937d6fbe, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

composable-pipelines 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.

.claude/skills/composable-pipelines/SKILL.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Composable Pipelines

A runtime-agnostic stack for AI pipelines in Swift: a declarative DSL lowers to a Codable AST, a compiler emits an execution graph, and an observable walker runs it — while an Executor you supply decides what "run a model" means.

Quick start

import ComposablePipelines

struct Summary: Pipeline {
    typealias Output = String
    let document: String

    @State var keyPoints = ""
    @State var summary = ""

    var body: some Pipeline {
        $keyPoints.set {                                    // step 1 → slot
            Model<String>().systemPrompt("Extract the 5 key points.").message(document)
        }
        $summary.set {                                      // step 2 reads step 1
            Model<String>().systemPrompt("Summarize from these points.").input { $keyPoints.get() }
        }
        $summary.get()                                      // pipeline output
    }
}

// Run it (linear flow): compile → walk.
let graph  = PipelineCompiler().compile(pipeline.loweredGraph())
let result = try await PipelineWalker(executor: MyExecutor()).run(graph: graph) { event in print(event) }
let text   = try JSONDecoder().decode(String.self, from: result)   // ExecutionValue == Data (JSON)

Authoring cheatsheet

  • Pipeline: struct X: Pipeline { typealias Output = T; @State var … ; var body: some Pipeline { … } }. The graph is inferred from the @State slots each step reads/writes — never wired by hand.
  • State: @State var s = "" → write with $s.set { <pipeline> } or $s.set(value); read with $s.get(). End body with the output slot's .get().
  • Model (output-only generic): Model<Output>() then chain .systemPrompt(_), .input { $slot.get() } or .message(staticValue), and optionally .tools([…]), .temperature(_), .maxTokens(_), .requirements(ModelSelectionRequirements(traits: […])).
  • Primitives: Guardrail(input, rules:allowed:blocked:), While(condition:) { … }, Group { … }, ForEach(in: xs) { x in … }, Summarize(text: $slot, maxTokens:), ClientTask(input: $slot) { value in … }, From(provider, query: $slot), Self.return(value).
  • Control flow: use native if / switch on produced state (e.g. if verdict == "trivial").

Read the full file on GitHub · 127 lines

Changes

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.

  1. 2mo ago First seen · 127 lines · 0 tokens per session scan A 1192937d6fbe

Subscribe to this mod's changes

composable-pipelines is a skill published in the GitHub repository MacPaw/ComposablePipelines (26 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,586 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.

Related

composable-pipelines compared with skills from other repositories

composable-pipelines next to 6 skills from other repositories
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autoragMarker-Inc-Korea/AutoRAGSkill5.3kyesterdayApache-2.0A68Claude Code, Codex
autorag-lite-setupMarker-Inc-Korea/AutoRAGSkill5.3kyesterdayApache-2.0A65Claude Code, Codex