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- Resciencelab
- Opc Skills
- Template
template_skill
- Python
472
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill resciencelab/opc-skills --skill template- SKILL.md2.5 KB
Overview
This skill provides a compact, command-driven toolkit for solopreneurs to run and integrate Python-based agent utilities. Use when you want quick CLI automation, local script orchestration, or to prototype API-backed agent behaviors using trigger keywords like "run", "deploy", "script", and "integrate." It bundles scripts, usage examples, and troubleshooting steps to speed setup and iteration.
How this skill works
The skill exposes small Python scripts in a scripts/ directory that you run from the skill folder to perform tasks or call APIs. It inspects environment variables and required API keys, reads command-line arguments, and prints structured output for easy piping into other tools. Built-in help flags and example commands make it simple to test basic and advanced flows locally before integrating into an agent.
When to use it
- Use when you want to run a quick automation or prototype with Python CLI scripts (trigger: "run script", "execute").
- Use when you need to wire an external API into an agent workflow and want a local script wrapper (trigger: "integrate API", "call endpoint").
- Use when debugging environment or auth issues for a solo agent deployment (trigger: "troubleshoot", "auth error").
- Use when preparing reproducible examples or command snippets for documentation or demos (trigger: "example", "demo").
Best practices
- Set required environment variables (API keys, endpoints) before running scripts; follow the example export commands.
- Start with provided quick-start commands to validate the environment and dependencies.
- Use the built-in --help flags on each script to discover options and flags before running advanced flows.
- Keep sensitive keys out of version control; use .env files or CI secrets where appropriate.
- Run examples from the skill directory so relative paths and imports resolve cleanly.
Example use cases
- Quickly call a third-party API via a local wrapper script to test rate limits and auth steps.
- Run a demo workflow from examples/ to show an agent capability during a client presentation.
- Wrap complex agent logic behind a simple CLI for repeatable testing and CI integration.
- Troubleshoot auth or environment variable issues using guided troubleshooting steps.
FAQ
Install Python dependencies, set required environment variables (API keys, endpoints), and run scripts from the skill directory.
How do I see available commands?
Run any script with --help to list options and usage examples.
Can I integrate these scripts into CI or an agent?
Yes. The scripts are designed to be called from CI pipelines or agent workflows; ensure secrets and environment variables are provided securely.