Results for “fr”

Imported skill faq_database from openai

Imported skill github_utils from openai

Imported skill spec_parsing from openai

Imported skill ui_component from openai

Imported skill 3p_updates from anthropic

Imported skill dmmono_ofl from anthropic

Imported skill gloock_ofl from anthropic

Imported skill outfit_ofl from anthropic

Imported skill tektur_ofl from anthropic

Imported skill chat_input from langchain

Friendly onboarding when users ask about capabilities

Generate favicons from a source image

Generate favicons from a source image

Pull data from a web page. (gstack)

Extract an Allium specification from an existing codebase. Use when the user has existing code and wants to distil behaviour into a spec, reverse engineer a specification from implementation, generate a spec from code, turn implementation into a behavioural specification, or document what a codebase does in Allium terms.

Strip a problem to its irreducible fundamental truths and rebuild the solution from the ground up — free from analogy, convention, and inherited assumptions. Load when the user feels constrained by how something has always been done, when existing solutions feel expensive or inefficient for no good reason, when the user asks to think from first principles, challenge the fundamentals, or rebuild this from scratch. Also triggers on "why does it have to work this way", "what are the actual constraints here", "ignore what everyone else does", or when deep-thinking diagnoses a convention-break frame. Based on Aristotle's first principles method, popularised by Musk and Feynman. Produces genuinely novel solutions by eliminating convention.

Detects the test platform (VSTest vs Microsoft.Testing.Platform) and test framework (MSTest, xUnit, NUnit, TUnit) from .NET project files.

Migrates .NET Framework code using Thread.Abort to cooperative cancellation with CancellationToken in modern .NET 6+.

Generate a complete, production-ready application from an OpenAPI specification using the active framework's conventions and best practices.

Creates a GitHub issue from a specification file using a feature request template, checking for existing issues first.

Creates Cursor rules in .cursor/rules/ with YAML frontmatter for persistent AI guidance, including scope and file pattern configuration.

Coordinate a full Galyarder Framework release across engineering verification, npm, GitHub, smoke testing, and announcement follow-up.

Renders text or images as ASCII art for terminal-friendly output, including banners, frames, QR codes, and weather.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.

Play Pokemon games autonomously via headless emulation. Starts a game server, reads structured game state from RAM, makes strategic decisions, and sends button inputs — all from the terminal.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Use when you need to apply aggregation functions (sum, mean, count, etc.) to values from overlapping intervals in one file and map them onto intervals from another file.

Use when evaluating the free energy (kcal/mol) of an RNA secondary structure, calculating co-folding energies for two RNA strands, or analyzing consensus structures from multiple sequence alignments.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.