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Found 1,886 Skills
Spatial data processing for geological modelling with GemPy. Use when Claude needs to: (1) Prepare spatial data for GemPy models, (2) Extract interface points from geological maps, (3) Process orientations/dip measurements, (4) Sample DEMs along profiles or cross-sections, (5) Convert between GIS formats and GemPy inputs, (6) Clip/transform vector/raster data for modeling, (7) Create model extents from geospatial bounds.
Generate academic presentation-style HTML slide decks and browser reports from PDFs, structured text, Markdown, paper summaries, outlines, or research notes. Use whenever the user wants to convert a scientific paper PDF directly into an interactive HTML report, clickable web presentation, shareable browser deck, or PPT-like HTML output with figures, structured insights, section pages, and offline deck-directory output. In the Aut_Sci_Write suite, choose this skill when the user wants HTML/web output; choose sci-ppt when they explicitly need a .pptx file.
Adversarial robustness engineering for ML/AI—evasion, poisoning, extraction, membership-inference threat models; robust training, sanitization, detectors; ASR/certified evals; lab model attacks; data-pipeline integrity; production I/O guardrails (classical ML and LLM/multimodal). Use for adversarial examples, robustness suites, poison audits, deploy guardrails—not LLM app red team (ai-redteam), governance (ai-risk-governance), safety classifier R&D (ml-research-engineer-safeguards), safeguard serving (ml-infrastructure-engineer-safeguards), privacy research (privacy-research-engineer-safeguards), AppSec pentest (penetration-tester).
A meta-skill for creating/writing custom Skills for the Aike Smart Parking Open Platform CLI (openydt), benchmarked against Feishu's lark-skill-maker. It is used when users want to encapsulate a specific openydt interface or a business process into a reusable Skill, create a new openydt domain Skill, standardize the directory structure and frontmatter of SKILL.md, extract the catalog command list, add --yes to write operations, or learn how to write an openydt Skill. Trigger words: create openydt skill, write an openydt skill, encapsulate openydt interface, create a parking domain skill, openydt skill maker, skill template, SKILL.md specification, how to write frontmatter, how to list command list, turn this interface into a skill, benchmark against lark-skill-maker, parking open platform skill, skill scaffolding, skill directory structure.
Luban - Skill Polishing Workshop. Transform a "usable Skill" into a public Skill asset that is "understandable, installable, shareable, verifiable, and continuously evolvable". The methodology consists of five craftsman-like steps: 1. Material Inspection: First challenge whether the premise of this Skill is valid; directly state if the "material" is not worth polishing. 2. Peer Research: Search for similar Skills online to clarify its position in the ecosystem. 3. Dimension Measurement: Evaluate using three metrics - structure, actual testing, and live verification (live verification means reconciling with real running outputs; a green CI can be deceptive). 4. Iterative Refinement: Freeze the original version as a baseline; only retain changes that pass the verification gate, otherwise revert. Try to institutionalize verification methods as tools and rules in the repository. 5. Post-Release Iteration: Release is not the end; maintain a benchmark observation list, and start the next iteration based on real feedback. This tool is used when users want to upgrade, optimize, polish, productize, or release their self-developed Skills. The final deliverables include a structured Skill Polishing Report, directly replaceable rewritten segments, and a shareable "Graduation Certificate" result card that can be screenshot. Trigger phrases include but are not limited to: "Let Luban take a look at this skill", "Polish at Luban's Workshop", "Polish my skill", "Upgrade my skill", "Optimize this skill", "Skill check-up", "Skill audit", "Productize my skill", "How to release this skill", "Benchmark against similar skills", "Why no one installs my skill", "Help me publish my skill to GitHub/ClawHub", "Improve SKILL.md". Even if users only provide a Skill directory, GitHub repository link, or a segment of SKILL.md saying "Help me figure out how to modify it", it should be triggered as long as the context is about making the Skill more usable and shareable. Do NOT use this for creating a new Skill from scratch (use skill-creator), regular code review (use code-review), or rewriting ordinary prompts unrelated to Skill assets.
Auto-activate for pytest_databases, Docker DB fixtures, PostgreSQL/pgvector/AlloyDB Omni/MySQL/Oracle/MSSQL/CockroachDB/Yugabyte/MongoDB/GizmoSQL/Redis/Spanner/BigQuery/Azurite/MinIO tests. Not for mocked DBs.
Professional code review skill for Claude Code. Automatically collects file changes and task status. Triggers when working directory has uncommitted changes, or reviews latest commit when clean. Triggers: code review, review, 代码审核, 代码审查, 检查代码
Interactive Intent approval. Review sections and mark status (locked/reviewed/draft). Use /intent-review <path> to review a specific file, or /intent-review to review Intent in current directory.
Provides comprehensive guidance for Redux state management including stores, actions, reducers, middleware, selectors, and Redux Toolkit. Use when the user asks about Redux, needs to manage global state, implement Redux patterns, or work with Redux middleware.
Guidance for filtering JavaScript and XSS attack vectors from HTML while preserving original formatting. This skill should be used when tasks involve removing script content, sanitizing HTML, filtering XSS payloads, or creating security filters that must preserve the original document structure unchanged.
Complete RAG and search engineering skill. Covers chunking strategies, hybrid retrieval (BM25 + vector), cross-encoder reranking, query rewriting, ranking pipelines, nDCG/MRR evaluation, and production search systems. Modern patterns for retrieval-augmented generation and semantic search.
Guide AI agents to generate complete PageObject pattern web scraper projects using Playwright and TypeScript with Docker deployment. Supports agent-browser site analysis for automated selector discovery. Keywords: scraper, playwright, pageobject, web scraping, docker, typescript, data extraction, automation.