Development

iii-worker-manager: host: 127.0.0.1 port: 49134 iii-worker-manager#browser: host: 127.0.0.1 port: 3110 rbac: auth_function_id: auth::browser expose_functions: - match("link::create") - match("link::request_delete") - match("stream::*") ``` Restart the project so Compose can materialize the changed engine configuration: ```bash iii compose --up --namespace linkly --file worker-compose.yaml ``` `expose_functions` is an allowlist of which functions a browser session can call. `auth_function_id` ...

engine: workers: {} containers: http: worker: package://api.workers.iii.dev/http version: "0.21.3" config_name: http state: worker: package://api.workers.iii.dev/state version: "0.22.2" config_name: state config_override: adapter: name: kv config: store_method: in_memory ``` The `engine:` section makes this Compose invocation own the engine. Project workers belong only under `containers:`. `state` uses an in-memory store by default, so every restart starts clean. That's what we want for this ...

value: queue_configs: clicks: type: standard max_retries: 5 concurrency: 5 adapter: name: builtin ``` <Note> Queue names are references to the queue and do not place any restrictions on what can be put into a given queue. </Note> You already wrote `link::record_click` in Chapter 3, where `http::redirect` triggers it directly. Nothing about that function needs to change to make it queuable. You only change how it's triggered with a `TriggerAction`. **First import `TriggerAction`** into `link/s...

Where a stream is for a live trickle of events, a **channel** is for **moving a large amount of data at once**: a direct streaming pipe between two endpoints, rather than one request and response. Channels are bidirectional (each end has both a reader and a writer), but here you'll stream in one direction, uploading a CSV of links. You'll give this its own `bulk-importer` worker so the `link` worker stays focused on single links.

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{/* AUTO-GENERATED FILE, DO NOT EDIT. Generated from the clap CLI definitions by the hidden `gen-cli-docs` subcommand. Regenerate with `scripts/generate-cli-docs.sh`. */} Reference for the `iii` binary and the `iii console` runtime it dispatches to. Running `iii` with no subcommand starts the engine. The same information is available from the binaries themselves via `iii --help` and `iii <subcommand> --help`. For a guided overview, see [CLI](../using-iii/cli).

Interview-driven consulting for custom voice command sets. Discover workflows, translate to noun-verb commands (or verb-first for developers), iterate, and emit JSON config.

Regenerate the neovim keybinding cheat sheet from the home-manager/modules/neovim config so it stays accurate. Use when the neovim config changed or the cheat sheet is stale.

Manage, build, test, package, install, and debug the Ivy Tendril extension in Antigravity IDE and VS Code. Use when the user asks to install, link, update, build, test, or package the Ivy Tendril extension for Antigravity IDE.

Build an app with Remotion

Use when adding, adopting, debugging or updating Morphir CLI examples and morphir itest scenarios, including nbformat notebooks, scenarios.md, scenario metadata, Rego assertions and integration coverage.

Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.

This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics, and other single-cell modalities. Use this skill for probabilistic modeling, batch correction, dimensionality reduction, differential expression, cell type annotation, multimodal integration, and spatial analysis tasks.

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced met...

Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for programmatic ELN workflows.

CLI/Python toolkit for rapid bioinformatics queries. Preferred for quick BLAST searches. Access to 20+ databases: gene info (Ensembl/UniProt), AlphaFold, ARCHS4, Enrichr, OpenTargets, COSMIC, genome downloads. For advanced BLAST/batch processing, use biopython. For multi-database integration, use bioservices.