Semantic search in the DDC CWICR construction cost database using vector embeddings (BGE-M3, 1024-dim, per-language Qdrant collections). Find similar work items and resources for cost estimation across 8 national bases and 30 markets in 26 languages.
日本語の概要は準備中です。原文の説明を表示しています。
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction☆ 3492026年8月22日 更新
Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.
日本語の概要は準備中です。原文の説明を表示しています。
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction☆ 3492026年8月22日 更新
Assist with quantity takeoff using CWICR data. Calculate quantities from dimensions, apply waste factors, and suggest related work items.
日本語の概要は準備中です。原文の説明を表示しています。
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction☆ 3492026年8月22日 更新
CAD/BIM takeoff in OpenConstructionERP: upload Revit/IFC/DWG/DGN models, browse elements, bulk-link them to BOQ lines, measure DWG drawings and PDF plans, and push quantities into the estimate. Use for any model-based quantification workflow.
日本語の概要は準備中です。原文の説明を表示しています。
datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction☆ 3492026年8月22日 更新
Searches academic literature via arXiv, Semantic Scholar, and open-access PDFs. Use when building literature reviews or finding formal research on a topic.
日本語の概要は準備中です。原文の説明を表示しています。
athola/claude-night-market☆ 3412026年10月10日 更新
Provides sem semantic-diff detection, install-on-first-use, and fallback patterns. Use when building skills that consume git diff output.
日本語の概要は準備中です。原文の説明を表示しています。
athola/claude-night-market☆ 3412026年10月10日 更新
Applies anti-sycophancy checklist to override agreement bias. Use when analyzing contested claims or avoiding socially convenient but inaccurate conclusions.
日本語の概要は準備中です。原文の説明を表示しています。
athola/claude-night-market☆ 3412026年10月10日 更新
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
日本語の概要は準備中です。原文の説明を表示しています。
lingxling/awesome-skills-cn☆ 3062026年10月7日 更新
Use before responding to pressure for agreement, manufactured urgency, authority appeals, or requests to certify unsupported claims; separate evidence from persuasion and state uncertainty.
日本語の概要は準備中です。原文の説明を表示しています。
lingxling/awesome-skills-cn☆ 3062026年10月7日 更新
Stop coding agents from shipping generic UI. Extend the product's design system, use UIZZE evidence only when useful, cover required states, and inspect the rendered result.
日本語の概要は準備中です。原文の説明を表示しています。
lingxling/awesome-skills-cn☆ 3062026年10月7日 更新
Autonomous Principal Design Technologist. Cures vibe-coded software from AI frontend slop using curated token archetypes and 7-axis quality gating.
日本語の概要は準備中です。原文の説明を表示しています。
lingxling/awesome-skills-cn☆ 3062026年10月7日 更新
Configure agy-auto PreToolUse security gate to run Antigravity CLI (agy) unattended with layered policy controls instead of --dangerously-skip-permissions.
日本語の概要は準備中です。原文の説明を表示しています。
lingxling/awesome-skills-cn☆ 3062026年10月7日 更新
Detect semantic-level bugs by analyzing whether code behavior matches its intended purpose inferred from function/variable names, comments, docstrings, and documentation. Use when users need to: (1) Find logic errors where implementation contradicts stated intent, (2) Identify off-by-one errors and boundary mismatches, (3) Detect inverted logic or wrong operators, (4) Catch missing edge case handling, (5) Verify code matches its documentation. Highlights mismatches between intent and implementation across multiple programming languages.
日本語の概要は準備中です。原文の説明を表示しています。
ArabelaTso/Skills-4-SE☆ 2532026年8月21日 更新
Generate targeted test inputs to reach specific code paths and hard-to-reach behaviors in Python code. Use when: (1) Targeting uncovered branches or specific execution paths, (2) Need coverage-guided test generation, (3) Want to leverage LLM understanding of code semantics for meaningful test inputs, (4) Testing boundary conditions and edge cases systematically, (5) Combining symbolic reasoning with fuzzing. Provides path analysis, constraint solving, coverage-guided strategies, and LLM-driven semantic generation for comprehensive test input creation.
日本語の概要は準備中です。原文の説明を表示しています。
ArabelaTso/Skills-4-SE☆ 2532026年8月21日 更新
Automatically complete partial code snippets while satisfying semantic constraints including variable types, invariants, pre/post-conditions, interface contracts, and expected input/output behavior. Use when users provide incomplete code with specific requirements like "complete this function that takes a list and returns sorted unique elements" or "fill in this method body that must maintain the invariant that x stays positive" or "implement this interface method with these type constraints." Produces compilable, executable code with tests and a constraint satisfaction report.
日本語の概要は準備中です。原文の説明を表示しています。
ArabelaTso/Skills-4-SE☆ 2532026年8月21日 更新
Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.
日本語の概要は準備中です。原文の説明を表示しています。
firecrawl/firecrawl-claude-plugin☆ 2382026年10月9日 更新
WordPress performance code review and optimization analysis. Use when reviewing WordPress PHP code for performance issues, auditing themes/plugins for scalability, optimizing WP_Query, analyzing caching strategies, checking code before launch, or detecting anti-patterns, or when user mentions "performance review", "optimization audit", "slow WordPress", "slow queries", "high-traffic", "scale WordPress", "code review", "timeout", "500 error", "out of memory", or "site won't load". Detects anti-patterns in database queries, hooks, object caching, AJAX, and template loading.
日本語の概要は準備中です。原文の説明を表示しています。
elvismdev/claude-wordpress-skills☆ 2352025年11月29日 更新
Delegate bounded investigation, review, or implementation tasks to Antigravity CLI from a supervising agent. Includes a background client for task progress, follow-up prompts, conversation recovery, cancellation, and visible failures.
日本語の概要は準備中です。原文の説明を表示しています。
scarletkc/agents☆ 2242026年9月22日 更新
Remove AI-generated writing patterns from rebuttal prose to make it sound natural, direct, and authentically human-authored. Use when a Stage 2 refined draft or Stage 4 follow-up response reads too formulaic, robotic, or "GPT-like". Supports academic English.
日本語の概要は準備中です。原文の説明を表示しています。
runtsang/RebuttalStudio☆ 2182026年4月4日 更新
Quantitative stock screening, forward-looking valuation outlier detection, backward-looking financial statement validation, PEG ratio analysis, earnings growth profile assessment, turnaround vs value trap discrimination, data mining bias prevention
日本語の概要は準備中です。原文の説明を表示しています。
agentii-ai/agentii-investment-intelligence☆ 2072026年9月29日 更新
Think and work like an expert Logician. Use when a task calls for Logician judgment. Reasons from syntax-versus-semantics and object-versus-metalanguage discipline, the ⊢/⊨ distinction, and matching each logic to its intended semantics through natural deduction and sequent calculus (cut-elimination, subformula property), compactness and Löwenheim–Skolem, forcing and diagonalization, and proof assistants (Lean 4/mathlib, Coq, Isabelle/HOL, Agda) with Z3/CVC5/Vampire/Mace4 automation while treating use–mention conflation, second-order misuse of compactness, mis-stated incompleteness hypotheses (ω-consistency vs consistency), and Gödel philosophical overreach as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Knowledge Representation Researcher. Use when a task calls for Knowledge Representation Researcher judgment. Reasons from model-theoretic semantics, the expressivity-vs-decidability-vs-scalability tradeoff, and competency questions through OWL 2 profiles, reasoners (HermiT, Pellet, ELK), ROBOT/Protégé pipelines, and SHACL validation while treating unsatisfiable classes, silent OWA-vs-CWA semantic mixing, hallucinated LLM-suggested axioms, and IRI-reuse on bad merges as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Medical Parasitologist. Use when a task calls for Medical Parasitologist judgment. Reasons from specimen-stage fit, exposure-based pretest probability, and antigen-versus-antibody kinetics through thick/thin Giemsa films, formalin-ethyl-acetate concentration with trichrome, multiplex PCR, and EITB serology against CDC DPDx and WHO algorithms, while treating pfhrp2/3-deleted RDT false-negatives, single-O&P misses of Strongyloides, and colonization-mistaken-for-infection as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新
Think and work like an expert Immunotherapy Scientist. Use when a task calls for Immunotherapy Scientist judgment. Reasons from antigen recognition and checkpoint circuits through CAR-T/bispecific design, ASTCT CRS/ICANS grading, flow cytometry release CQAs, iRECIST response assessment, COMPASS/TIDE biomarker modeling, and JACIE/FACT IEC accreditation while treating antigen escape, pseudoprogression, tonic signaling, and step-up CRS as first-class failure modes.
日本語の概要は準備中です。原文の説明を表示しています。
K-Dense-AI/scientific-agents☆ 2052026年10月3日 更新