irrelevant ==========
Q3 responder handles two responsibilities: (1) assigning HTTP status codes to unhandled exceptions and (2) throwing custom errors in the stack. Within client projects, the first is irrelevant as Q3 registers the functionality via global express middleware
fs read and write streams based on minipass
Preprocess gherkin files by filtering out irrelevant steps
fs read and write streams based on minipass
Sanitizes pasted logs before sending them to AI by redacting long quoted strings, JWT tokens, bcrypt hashes, and base64 blobs to reduce token usage and remove irrelevant noise.
ugly, very ugly parser. irrelevant for production use.
A pretty-printer for [io-ts](https://github.com/gcanti/io-ts/issues/350) errors that filters out irrelevant unions by the identifying tag literal in input data - it chooses the union option with the most fields covered.
Converts input value to a string with separator decimal passed as paramater, locale is irrelevant. Using one-separator-decimal.
DOMinus.js is a reactive data binding library that turn HTML irrelevant.
the irrelevant piece in the trilogy (sidenote: i think i'm jumping the shark by now)
Material Design Icons DX
Converts input value to a floating-point number with separator decimal passed as paramater, locale is irrelevant. Only the last non-numeric character is considered for the conversion.
Lint files staged by git
Stylelint plugin for stylehacks linting.
This Python code implements a genetic algorithm (GA) for feature selection. Feature selection is an important step in machine learning where irrelevant or redundant features are identified and removed from the dataset, improving model performance and redu
🌐 Turn any <input> into an address autocomplete.
Lightweight, deterministic backend guard for RAG pipelines. Detects irrelevant context, ungrounded answers, and generic responses without LLM calls.
a really stupid setImmediate polyfill
decaffeinate fork of the CoffeeScript implementation
Resolve and fetch package metadata and tarballs
decaffeinate fork of the CoffeeScript implementation
Aids humans and automation in managing npm audit results
This Python code implements a genetic algorithm (GA) for feature selection. Feature selection is an important step in machine learning where irrelevant or redundant features are identified and removed from the dataset, improving model performance and redu
A Rust crate for ignoring variables in a more explicit fashion, and checking assumptions about those variables.
Metadata-driven Parquet pruning for Rust: Skip irrelevant data before reading
Bayesian Linear Regression with Automatic Relevance Determination for interpretable, sparse modeling in embedded and WASM environments
finr recursively searches files and directories with a pattern while ignoring irrelevant directories. Built with the phrase "Work smarter not harder" in mind.
Reconstructive memory retrieval engine using ACT-R spreading activation
Archaic attempt at autonomous non-sandboxed distributed artificial life of assembler automaton type.
FUSE filesystem that hides files matching .agentignore rules from processes - control what agents can see while building apps
A quiet place for your project docs. MCP server that gives AI agents scoped access to private documentation.
A library for Avatar Graphs
Converting BIP39 entropy to valid Bizinikiwi (sr25519) SecretKeys
A flexible binary format for storing and streaming structured data as packets with CRC protection and recoverability from corruption. Built for extensibility and robustness.
An AI coding agent hook that blocks destructive commands before they execute
Rails helper. Finds the irrelevent styles in your stylesheet and generates a html report to keep you informed.
A wrapper around strace(1) that allows you to perform targetted tracing of a block. strace_me allows you to track down problems without wading through gobs of ruby startup or other irrelevant noise.
Sending messages with the Slack API is not that difficult, but I've had to solve the same problems a lot of times at different companies. This gem attempts to make those solutions irrelevant by providing a simple interface and scripts to send and update messages, and build/extend threads.
SentinelRb provides automated analysis of AI prompts to identify and flag common antipatterns like irrelevant information, misinformation, bias, and dangerous instructions. Uses LLM-based scoring combined with heuristic pattern matching for comprehensive prompt quality assessment.
Evaluates cognitive inputs by relevance (effect/effort ratio). High-effect low-effort inputs get attention; irrelevant inputs filtered. Based on Sperber & Wilson (1986) Relevance Theory.
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