Results for “fibery-automation”

Deploy serverless browser automation as cloud functions using Browserbase. Run browser automation on a schedule, create webhook endpoints, or run automation in the cloud instead of locally.

Automates repetitive infrastructure and deployment tasks with Terraform, OpenTofu, Ansible, GitHub Actions, and n8n, enforcing safe practices like plan review and confirmation before applying changes.

Designs and implements CI/CD pipelines, infrastructure automation, and workflow optimization to reduce manual tasks.

Build automated AI workflows combining multiple models and services for batch processing, scheduled tasks, event-driven pipelines, and agent loops using the inference.sh CLI.

Manage businesses, projects, time tracking, and budgets in FreshBooks cloud accounting via automated API calls.

Deploys serverless browser automation as cloud functions using Browserbase, including project setup, local testing, and publishing via the bb CLI.

Submits and tracks protein-testing experiments on the Adaptyv Bio Foundry cloud lab (wet-lab validation), and optimizes protein sequences before submission with computational tools (NetSolP, SoluProt, SolubleMPNN, ESM). Use when designing proteins that need wet-lab validation - binding/affinity screening, expression testing, thermostability, or fluorescence assays - or when submitting experiments to the Foundry API, browsing the target catalog, tracking experiment status, retrieving results, or pre-screening sequences for solubility/expression. Triggers on "Adaptyv", "Foundry API", "cloud lab", "biolayer interferometry / BLI", "wet-lab validation". Part of the AlterLab Academic Skills suite.

Run the full autonomous engineering pipeline end-to-end (plan, work, code review, test, commit, push, open PR, watch CI, fix CI failures until green). Use only when the user explicitly requests hands-off execution of a software task and provides a feature description; do not auto-route casual conversation here.

Execute a Fabric Data Pipeline

Optimizes Dify workflows and plugins by restructuring graphs, reducing LLM token usage, tuning worker pools, and improving parallel processing.

Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.

Run autonomous optimization loops that iteratively improve artifacts against evaluators using hypothesis tree refinement, without overfitting.

Identifies operational toil, prioritizes automation by ROI, and provides patterns for self-healing systems and runbook automation.

Run a full pipeline for a task. Orchestrates roles through stages (standalone or HOTL-integrated).