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Integrate Flowlines Sdk Python

Listed
flowlines-ai·vlatest·backend·MIT

Provides Python guidance and assistance for developing backend services and APIs.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add flowlines-ai/skills --skill integrate-flowlines-sdk-python -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

flowlines-ai

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: api.flowlines.ai.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    api.flowlines.aiundeclared

    What it found

    • skills/integrate-flowlines-sdk-python/SKILL.md:224contacts api.flowlines.ai
      curl -X GET 'http://api.flowlines.ai/v1/get-traces' -H 'x-flowlines-api-key: <FLOWLINES_API_KEY>'

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned flowlines-ai/skills at d795932bf2.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
d795932bf2
Manifest
skills/integrate-flowlines-sdk-python/SKILL.md
Scanned
1 file, 196 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill allows AI agents to interact with Flowlines data pipelines using the Python SDK. It enables programmatic access to pipeline configurations, execution status, and results. Specifically, you can manage pipelines, trigger executions, and retrieve output data directly from within your agent's workflow.

When to use it

  • Automated Data Processing: Trigger and monitor Flowlines pipelines for automated data ingestion or transformation tasks.
  • Dynamic Workflow Orchestration: Adjust pipeline configurations based on real-time conditions detected by the AI agent.
  • Data Retrieval & Analysis: Fetch processed data from completed Flowlines runs to inform decision-making within your agent.
  • Pipeline Management: Create, update, or delete Flowlines pipelines programmatically.

Key capabilities

  • Python SDK integration
  • Pipeline configuration management
  • Execution triggering and monitoring
  • Data retrieval from pipeline results

Example prompts

  • "Run the 'customer_data_pipeline' with these parameters: region=us-west, date=2024-10-27."
  • "Get the status of pipeline 'sales_report_gen'."
  • "Create a new Flowlines pipeline named 'inventory_update' from this YAML configuration..."

Tips & gotchas

  • Requires familiarity with Flowlines and its data pipelines.
  • Ensure the Flowlines Python SDK is installed in your agent’s environment (pip install flowlines-sdk).