Pulling skills into your agent

Download a Skill Collection with the PromptLayer SDK or public REST API so Claude Code, Codex, Cursor, or OpenClaw can load it from disk.

After Wrangler (or you) finalizes a Skill Collection in the dashboard, your coding agent loads skills from files on disk. Use client.skills.pull() to fetch the collection, then write the files to your project.

You can generate these exact snippets for your own collection from the dashboard: open a Skill Collection and click Pull via SDK.

Prerequisites

Set your API key in the environment:

export PROMPTLAYER_API_KEY="your_promptlayer_api_key"

Pull as a folder of files

skills.pull() returns a response with a files map (path → text content). For provider-specific collections, those paths already include the provider prefix (.claude/..., .agents/..., or .openclaw/...), so the simplest thing to do is write each file at its returned path from your project root. Everything lands where your agent expects it.

Python

# pip install -U promptlayer
import os
from pathlib import Path

from promptlayer import PromptLayer

client = PromptLayer(api_key=os.environ["PROMPTLAYER_API_KEY"])

result = client.skills.pull("my-collection")
if result is None:
    raise ValueError("No skill collection returned.")

for relative_path, content in result["files"].items():
    output_path = Path(relative_path)
    output_path.parent.mkdir(parents=True, exist_ok=True)
    output_path.write_text(content, encoding="utf-8")

// npm install promptlayer
import { PromptLayer } from "promptlayer";
import { mkdir, writeFile } from "node:fs/promises";
import path from "node:path";

const client = new PromptLayer({ apiKey: process.env.PROMPTLAYER_API_KEY });

const result = await client.skills.pull("my-collection");
if (!result || result instanceof ArrayBuffer) {
  throw new Error("Expected a JSON skill collection response.");
}

for (const [relativePath, content] of Object.entries(result.files)) {
  await mkdir(path.dirname(relativePath), { recursive: true });
  await writeFile(relativePath, content, "utf8");
}

For a Claude Code collection, this produces .claude/CLAUDE.md, .claude/skills/<name>/SKILL.md, etc. For Codex, you get .agents/AGENTS.md, and for OpenClaw you get .openclaw/.... Universal collections have no prefix and land in your project root as-is.

Writing to a custom directory

If you want to rename the output directory (for example, write a Claude Code collection under .agents instead of .claude), strip the known provider prefix from each path and join the remainder to your target directory:

Python

output_dir = Path("custom-dir")
prefix = ".claude/"  # your collection's provider prefix

for relative_path, content in result["files"].items():
    target = relative_path[len(prefix):] if relative_path.startswith(prefix) else relative_path
    output_path = output_dir / target
    output_path.parent.mkdir(parents=True, exist_ok=True)
    output_path.write_text(content, encoding="utf-8")

const outputDir = "custom-dir";
const prefix = ".claude/";

for (const [relativePath, content] of Object.entries(result.files)) {
  const target = relativePath.startsWith(prefix)
    ? relativePath.slice(prefix.length)
    : relativePath;
  const outputPath = path.join(outputDir, target);
  await mkdir(path.dirname(outputPath), { recursive: true });
  await writeFile(outputPath, content, "utf8");
}

Provider	Prefix in response paths
Claude Code	.claude/
OpenAI / Codex	.agents/
OpenClaw	.openclaw/
Universal	(no prefix)

Pin a version or release label

Pass version= or label= to pull an immutable snapshot instead of latest.

Python

client.skills.pull("my-collection", version=12)
client.skills.pull("my-collection", label="production")

await client.skills.pull("my-collection", { version: 12 });
await client.skills.pull("my-collection", { label: "production" });

Pull as a zip archive

Pass format="zip" to get a binary archive instead of a JSON file map. The archive already contains the provider’s on-disk layout, so unzip it at your project root.

Python

import os
from pathlib import Path

from promptlayer import PromptLayer

client = PromptLayer(api_key=os.environ["PROMPTLAYER_API_KEY"])

zip_archive = client.skills.pull("my-collection", format="zip")
if not isinstance(zip_archive, bytes):
    raise ValueError("Expected a zip archive.")

Path("skills.zip").write_bytes(zip_archive)

import { PromptLayer } from "promptlayer";
import { writeFile } from "node:fs/promises";

const client = new PromptLayer({ apiKey: process.env.PROMPTLAYER_API_KEY });

const zipArchive = await client.skills.pull("my-collection", { format: "zip" });
if (!(zipArchive instanceof ArrayBuffer)) {
  throw new Error("Expected a zip archive.");
}

await writeFile("skills.zip", Buffer.from(zipArchive));

Raw REST API

Use GET against the public API when you are not using an SDK:

GET https://api.promptlayer.com/api/public/v2/skill-collections/<identifier>

Optional query parameters:

Parameter	Purpose
format=zip	Return a zip archive instead of JSON
version=<n>	Pin to a specific version number
label=<name>	Pin to a release label

File paths in the JSON response follow the same convention as the SDK: provider-specific collections include the .claude/, .agents/, or .openclaw/ prefix; universal collections are root-relative. Zip exports always include the provider layout.

Skill Collection webhooks

Skill Collections emit a skill_collection_files_changed event when a collection is created, saved, deleted, or restored. To subscribe and verify signatures, see Webhooks.

CI pattern

Run skills.pull in your build or deploy pipeline with a pinned label (for example production) so your agent loads a stable snapshot instead of whatever was latest when the job last ran.

For more on labels and review, see Tune skills for your team.