Results for “cl-te”

Apply bottom-up and top-down role mining techniques to discover optimal RBAC roles from existing user-permission assignments, reducing role explosion and enforcing least privilege.

Process large ML datasets in parallel across CPU or GPU clusters, with streaming execution, multi-format I/O, and integration with Ray Train, PyTorch, and TensorFlow for batch inference and preprocessing pipelines.

Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.

Vendor-neutral framework for scoring software health, estimating technical debt, assessing cloud readiness and open-source safety, and communicating quality to business stakeholders. Use when you need to quantify code health at the application or portfolio level rather than fix individual findings.

Interact with Atlassian Jira from the terminal: search issues, view details, create issues, add comments, list projects, and transition status. Use when the user mentions Jira, a ticket key (e.g. PROJ-123), or asks about issues, bugs, tasks, projects, or sprint work.

Delegates a coding task to pi (dev/pi), a minimal terminal coding harness. This skill should be used when the user asks to "use pi", "run pi", "delegate to pi", "let pi handle this", "ask pi to", "have pi do", or invokes /pi:delegate. It bridges the current Claude Code context to the pi CLI, passing relevant files, git state, and the task description for execution by the pi-agent.

Analyse experiment results, run validity checks (SRM, exposure parity, data integrity, novelty/primacy), interpret causally, make a ship/iterate/kill decision against the pre-declared rule, and append to cumulative learnings. Forces honest readouts — strips significance claims from underpowered or peek-violating tests; never lets directional results masquerade as causal wins. Load when results exist, or when the user says "read out this experiment", "analyse the test", "did the test win", "interpret the results", "what did we learn", "ship or kill", or when the experimentation orchestrator routes here.

Apply world-class developer documentation principles (Stripe, Snowflake, Databricks, TiDB Cloud) to structure, write, review, or refactor technical documentation. Use this skill whenever the user mentions documentation, docs, sidebar or navigation, information architecture, restructuring a section, writing or editing a guide, reviewing docs, where content belongs, English doc prose, headings, code comments, link text, docs home pages, section landing pages, long-form guides mixing content types, cross-referencing, or making docs readable for AI agents and LLMs. Covers VeloDB Cloud docs work (Monitoring restructure, sidebar, EN/中文 alignment, writing style, landing pages, LLM-friendly docs) and any SaaS or database documentation task. Trigger broadly: if the conversation touches doc organization, page structure, doc quality, doc sentences, landing pages, or AI-readable docs, consult this skill rather than answering from intuition.

Configures pre-created scratch org pools for parallel CI testing, reducing pipeline wait times by claiming pre-warmed orgs instead of provisioning on demand. Covers CumulusCI pool commands, Dev Hub limits, and CI integration.

Determines if PAC/PRA ratio and PAC levels indicate positive or provisionally positive screening for primary aldosteronism. Triggered when a clinician has PAC and PRA results and asks “Is this screening test positive for PA?” or needs to interpret borderline results.

Research the last 30 days across Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, and grounded web search. Returns a ranked, clustered brief with citations. Use when the task needs recent social evidence, competitor comparisons, launch reactions, trend scans, or person/company profiles.

Query your Jellyfin media server from the terminal — recently added movies and episodes, search across your library, browse libraries, and check server info and stats. Use when the user asks about Jellyfin, media server, movies, TV shows, recently added content, or their media library.

Restructure any response for an ADHD brain — TL;DR first, ELI16 clarity, short punchy steps, one clear next action, zero walls of text. Use this skill whenever the user says "elihadhd", "adhd mode", "tldr", "eli16", "eli5", "too long", "overwhelmed", "shorter", "just tell me what to do", "break this down", "snap it", "gauntlet", or shows signs of overwhelm (e.g. "wait what", "I'm lost", "too much"). Also use it when the user asks for the simple version, the quick version, or the punchy version of anything — explanations, plans, debugging help, docs, decisions. When in doubt about whether a response is too heavy, use this skill.

EMC pre-compliance risk analysis for KiCad PCB designs — 18 check categories, 44 rule IDs covering ground planes, decoupling, I/O filtering, switching harmonics, clock routing, differential pair skew, board edge radiation, PDN impedance, return paths, crosstalk, ESD protection, shielding, and magnetic leakage from switching inductors. Produces severity-ranked risk report with pre-compliance test plan. Supports FCC Part 15, CISPR 32, CISPR 25 (automotive), MIL-STD-461G. SPICE-enhanced when available. Use when the user asks about EMC, EMI, radiated/conducted emissions, FCC compliance, CE marking, CISPR, ground plane issues, decoupling strategy, clock routing EMC, switching noise, differential pair skew, or whether their board will pass EMC testing. Also for "will this pass FCC?", "check my EMC", "is my ground plane okay?", "check my decoupling", or "generate an EMC test plan".

21-rule prose review workflow for technical and academic Markdown/LaTeX excerpts. Use when the user asks for muxing-style-review, wants a complete agent-style check combining check-human.md with agent-style audit-only evidence, wants a compact-rule check, wants a DeepSeek/Codex manuscript draft checked for clarity, evidence, citation discipline, terminology, AI-tell prose, or wants an A/B draft comparison. Prefer a dedicated review subagent when available for non-trivial reviews. Use the sibling style-review skill for the upstream post-hoc audit/polish workflow.

Triages security incidents by classifying type, assigning severity based on business impact, enriching with threat intelligence, and routing to appropriate response teams using NIST SP 800-61r3 and SANS PICERL frameworks.

Runs a headless-Chromium sweep at phone/tablet widths to catch off-screen overflow, tiny touch targets, clipped text, and oversized modals, then reports each offender with a screenshot and a concrete fix.

Implementation guide for GDPR Article 7(3) consent withdrawal mechanisms. Covers the equal ease requirement ensuring withdrawal is as easy as giving consent, one-click withdrawal implementation, cascading effects on downstream processing, third-party notification workflows, and technical architecture for real-time consent revocation.

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.

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.

Use this skill whenever the user wants to work with the Loops CLI from the terminal. This includes installing or updating the CLI, authenticating, storing and selecting API keys, validating credentials, and running commands for contacts, contact properties, lists, events, transactional email, campaigns, email messages, themes, components, and uploads. Trigger on phrases like "Loops CLI", "loops auth login", "loops campaigns create", "loops uploads create", "loops email-messages update", "loops themes list", "loops components get", "loops contacts create", "loops events send", "loops transactional send", "loops api-key", "loops agent-context", "brew install loops-so/tap/loops", or any time the user wants to use Loops from the shell instead of application code.

Guides AI agents to apply advanced mathematical and probabilistic techniques (Bloom filters, HyperLogLog, FFT, etc.) for large-scale data problems where classical algorithms are optimal but math offers better asymptotic bounds.

Enforce organizational security policies across Kubernetes clusters and CI/CD pipelines using Open Policy Agent (OPA) and Gatekeeper, including writing Rego policies, deploying admission controllers, and testing policies locally.

Builds React 18+ components, implements custom hooks, debugs rendering issues, migrates class components to functional, and manages state with Context, Redux, or Zustand. Covers React 19 Server Components, Suspense boundaries, useActionState forms, and performance optimization.

Captures a spatial hierarchy of rendered DOM elements from any webpage via Playwright CLI, returning an LLM-friendly text tree, structured JSON tree, and a node map with CSS selectors and overlay metadata.

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

Search YouTube videos, channels, and trends through the AIsa YouTube SERP client. Use when the user asks for content research, competitor tracking, or trend discovery without managing Google credentials. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

Deep web exploitation beyond initial scanning. Covers SQLi (blind, OOB, second-order), NoSQL injection (MongoDB, operator bypass), GraphQL injection (introspection, batching, mutation abuse), XSS (reflected/stored/DOM with full source-sink analysis), SSTI (Jinja2/Twig/Freemarker/ERB engine identification and RCE), SSRF chains, file upload bypass (polyglot creation), XXE (blind, DOCX/SVG injection, Content-Type switching), deserialization (Java/PHP/Python/.NET), command injection, path traversal (LFI wrapper bypasses), race conditions, CSRF, JWT attacks (none/key confusion/kid injection), HTTP request smuggling (CL.TE/TE.CL/H2), CRLF injection, open redirect bypass chains, CORS exploitation, web cache deception/poisoning, OAuth misconfiguration, prototype pollution, session management, and business logic flaws. Uses sqlmap (advanced modes), commix, xsser, wapiti, davtest, and manual http(action="request", ...) payloads. Every technique includes actual payloads, commands, and code snippets for immediate use. Ch

Restructure existing code without changing its behavior, through a test-gated refactoring loop: a named target, a green suite over that target before any edit, a planned sequence of small named refactorings, and the full suite re-run after every step. Use when the user wants to refactor, restructure, clean up, simplify, or improve the design of existing code, or to apply refactoring recommendations from a code-review or architectural-analysis report. This skill changes code; it does not review code (use code-review), assess architecture (use architectural-analysis), or build new behavior test-first (use tdd). Do not use it on code inside an active tdd loop; the refactor step of tdd owns that cleanup. Runs its planned sequence to completion without pausing for review; to review each named refactoring as it lands, use pairing.

Deno runtime for TypeScript/JavaScript. Covers permissions, standard library, testing, and Deploy. Use for secure, TypeScript-native backend development. USE WHEN: user mentions "deno", "permissions", "Deno.serve", asks about "deno test", "deno deploy", "standard library", "top-level await", "npm compatibility" DO NOT USE FOR: Node.js runtime - use `nodejs` skill instead DO NOT USE FOR: Fresh/Oak frameworks - use framework-specific skills DO NOT USE FOR: Language syntax - use `typescript` skill