Results for “grammar”

Regex/parser/DSL design specialist for grammar authoring and ReDoS-safe regex. Not for REST APIs (Gateway) or DB schemas (Schema).

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework

Explains MariaDB-specific REVOKE syntax and behavior, including the five grammar forms, privilege requirements, error semantics, and role/proxy revocation nuances.

Expert copy editor for Quarto (.qmd) files. Checks grammar, spelling, punctuation, and academic writing quality. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to proofread, check grammar, fix typos, or review prose in a .qmd document. For APSA style rules (numbers, citations, capitalization, abbreviations, neutral language), use the apsa-style skill instead. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

Polish English academic papers for SSCI journal submission. This skill checks grammar, improves readability, and enhances academic tone. Use when the user asks to polish, proofread, edit, or improve their English academic paper, manuscript, or article — especially when targeting SSCI, SCI, or other international journals. Also use when the user asks to "润色", "修改语法", "提升学术性", "polish my paper", or mentions their paper needs language improvement for journal submission. Always trigger on any request involving academic English polishing, even if the user doesn't explicitly say "SSCI."

Proofread and correct text for grammar, spelling, punctuation, style, clarity, and consistency, with support for multiple style guides and readability analysis. Use when the user requests proofreading or provides relevant inputs for this workflow.

Scores generated text for morphosyntactic well-formedness by measuring how closely it adheres to language-specific dependency rules extracted from treebanks.

GLIP: Grounded Language-Image Pre-training

Forces a second, harder escalation pass using the original glazer prompt words verbatim, pushing for a sharper replacement thesis rather than more polish.

lemmaly — Algorithm-First Proof

Algorithm-first discipline: state Big-O, data structure, and algorithm family BEFORE writing loops, queries, or recursion. Catches O(n^2), N+1, and brute-force defaults.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion to catch O(n²), N+1, and brute-force defaults.

Write clear, plain prose and strip register-jargon from text, using a costume-or-term-of-art test to preserve genuine technical terms.

Generate cinematic videos with Seedance 2.0 using director-level prompts, camera grammar, and multi-mode generation across Chinese, Global, and VIP tiers.

Algorithm-first discipline: state Big-O, data structure, and algorithm family BEFORE writing loops, queries, or recursion. Catches O(n^2), N+1, and brute-force defaults.

韩寒（作家车手）认知与表达框架（压缩蒸馏）：反套路叙事、冷幽默、公共发言锋利… 触发：三重门赛车 等。不伪造赛事实；尊重他人

Analyse the language demands of a classroom task to identify barriers for EAL and multilingual learners. Use when adapting tasks, planning support, or assessing linguistic accessibility.

Build students' capacity to read historical documents closely — attending to word choice, tone, and rhetoric as evidence of perspective. Use when students summarise sources without analysing language.

润色中文学术论文，识别并替换模板化、机械化的AI表达，使文本更自然、更符合人类学者的写作习惯。

Algorithm-first discipline: state Big-O, data structure, and algorithm family BEFORE writing loops, queries, or recursion. Catches O(n^2), N+1, and brute-force defaults.

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

Extracts and formalizes domain terminology from a conversation into a consistent glossary saved to a local file.

Enforces an algorithm-first discipline: state Big-O, data structure, and algorithm family before writing loops, queries, or recursion, catching O(n^2), N+1, and brute-force defaults.

Build students' capacity to compare accounts across multiple historical sources — identifying agreements, contradictions, and gaps. Use when students treat individual documents as complete answers rather than partial perspectives.

Remove AI writing patterns from prose. Use when drafting, editing, or reviewing text to eliminate predictable AI tells.

Build and sharpen a project's domain model — a CONTEXT.md glossary and ubiquitous language. Use when pinning down terminology, or the agent "uses the wrong words". Repo decision-memory system (INDEX.md, rejected alternatives) → docs-adr.

Language Tutor