Results for “cl-te”

Convert Markdown files to HTML similar to `marked.js`, `pandoc`, `gomarkdown/markdown`, or similar tools; or writing custom script to convert markdown to html and/or working on web template systems like `jekyll/jekyll`, `gohugoio/hugo`, or similar web templating systems that utilize markdown documents, converting them to html. Use when asked to "convert markdown to html", "transform md to html", "render markdown", "generate html from markdown", or when working with .md files and/or web a templating system that converts markdown to HTML output. Supports CLI and Node.js workflows with GFM, CommonMark, and standard Markdown flavors.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `youtube-serp`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Search YouTube SERP results through AISA for video research, channel discovery, trend checking, and competitor tracking. Use when: you need ranked YouTube results for a query, optionally filtered by country or language.

Control a mobile (iOS) emulator / simulator stream from inside Orca using the `orca` CLI. Use for taps, gestures, typing, hardware buttons, camera injection, permissions, accessibility tree, and more — all while seeing the live view in Orca's emulator pane. Prefer this over raw `npx serve-sim` or direct simctl when running agents inside Orca (the orca surface handles device scoping, helper lifecycle, and worktree context). Complements the orca-cli skill for terminals, worktrees, and the built-in browser.

Apply meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "technical debt prevention", "prototype vs tracer bullet", or "code ownership". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.

Comprehensive exploratory data analysis with publication-quality descriptive tables, correlation matrices, distribution plots, and assumption testing. Generates a standalone EDA report with Table 1 (gtsummary/great_tables), correlation heatmap, distribution diagnostics, VIF for multicollinearity, and normality/homoscedasticity tests. All figures are APA-formatted and colorblind-safe. Use when the user says "exploratory analysis," "EDA," "descriptive statistics," "explore the data," "Table 1," "correlations," "distributions," or when /data-clean completes successfully. Triggers on "EDA," "descriptive," "Table 1," "explore," "correlations."

Security controls for RAG. Indirect prompt-injection via retrieved documents, PII detection/redaction (Microsoft Presidio, AWS Comprehend), multi-tenant isolation, ACL-aware retrieval with row-level/metadata filtering, data-leakage prevention, jailbreak hardening on retrieved context, GDPR right-to-be-forgotten in vector DBs. USE WHEN: user mentions "prompt injection RAG", "indirect prompt injection", "PII redaction", "Presidio", "ACL RAG", "row-level security", "multi-tenant RAG isolation", "GDPR vector DB", "right to be forgotten", "jailbreak", "data leakage RAG" DO NOT USE FOR: hallucination detection - use `rag-guardrails`; tenancy scaling patterns - use `rag-production`; audit tracing schema - use `rag-observability`

Turn a work-items.md file (produced by /plan-work-items) into Linear issues, one per slice, in a single target Linear team. Use when you want to publish work items as Linear issues, create implementation tickets to track in Linear, or push a broken-down plan into a Linear team. Requires a configured Linear MCP server and a target team. Reads the team's real workflow states, labels, Projects, and members and resolves every option against them before creating anything; defaults each issue to the team's initial state, unassigned, uncategorized, with no parent or Project unless you ask. Links within-file `Depends on` relationships as native Linear "blocked by" relations and annotates the source file so re-runs resume cleanly. Does not produce the work-items file itself — use plan-work-items first. Does not post to Jira — use work-items-to-jira. Does not post to GitHub — use work-items-to-issues.

Detect process injection techniques (T1055) including classic DLL injection, process hollowing, and APC injection by analyzing Sysmon events for cross-process memory operations, remote thread creation, and anomalous DLL loading patterns.

Integrate Microsoft Graph SDK into any project — .NET, TypeScript/JavaScript, or Python. Covers auth patterns (client credentials, OBO, managed identity), SDK setup, calling Graph APIs, batching, delta queries, change notifications, throttling, and permission scopes. Use when accessing Microsoft 365 data (users, mail, calendar, Teams, files, SharePoint) from any application type.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `market`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Query real-time and historical financial data across equities and crypto—prices, market moves, metrics, and trends for analysis, alerts, and reporting. Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

Police the project's vocabulary — bust vague terms, keep the CONTEXT.md glossary sharp, and lock in decisions worth remembering as ADRs. Use when the user debates naming, says "what should we call this", asks to pin down terminology, wants a decision recorded, or when another skill (hot-seat, whiteboard) surfaces a decision that clears the ADR bar. Just reading the glossary for vocabulary is NOT this skill — trigger only when the words or decisions are being changed.

Run three agents as a newsroom — a Writer, an Editor, and a Fact-checker — that draft, critique, and verify in parallel and argue until the writing survives with zero flags. This is the level above a single self-review loop, for the pieces that matter most. Best run in Claude Cowork against the user's files. Use for high-stakes writing the user wants bulletproof: a newsletter, a launch post, a client email, a public announcement. Trigger whenever the user says 'run the team', 'use the swarm', 'writer editor fact-checker', 'spawn agents to work on this', or wants the strongest possible version of a piece. For a lighter single-agent loop, use red-pen instead.

Use when the user requests diagrams, flowcharts, architecture diagrams, ER diagrams, UML / sequence / class diagrams, SysML / MBSE diagrams (block definition, internal block, requirement, parametric), BPMN business process diagrams, swimlane / cross-functional flowcharts, network topology, cloud architecture from Terraform or Kubernetes manifests, ML/DL model figures (Transformer/CNN/LSTM), mind maps, or any visualization. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Best suited when the diagram needs custom styling, rich shape vocabulary, swimlanes, or exportable images (PNG/SVG/PDF/JPG). Generates .drawio XML and exports locally via the native draw.io desktop CLI.

Run a Codex prompt repeatedly on a fixed interval. Use for "/loop", "run this every N minutes/hours", "poll X every 5 minutes", "repeat this Codex prompt", or any recurring interval-based Codex job. This is the interval-repeat companion to the separate `schedule` skill (cron / specific-time). For a durable, always-on alternative that survives reboots and terminal exits, prefer Codex app Automations; this local CLI is a terminal fallback that only fires while its daemon process is running.

Plans and coordinates the deployment of a model to Amazon SageMaker AI, selecting the appropriate pathway (real-time, serverless, async, batch, or Bedrock CMI) based on model type, traffic, latency, and cost constraints.

Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs. Produces clickable URLs for sharing Arize resources with team members. Use when the user wants to link to or open a trace, span, session, dataset, evaluator, or annotation config in the Arize UI.

Conventions and helpers for lightweight relationships between entities expressed as frontmatter references (not first-class Binding entities). Use when linking two entities with a simple, unscoped, untemporal relationship — 'this work item blocks that one', 'this decision relates to that work item'. For scoped/temporal relationships, use binding-management instead.

Run a pre-mortem risk analysis on a PRD or launch plan. Categorizes risks as Tigers (real problems), Paper Tigers (overblown concerns), and Elephants (unspoken worries), then classifies as launch-blocking, fast-follow, or track. Use when preparing for launch, stress-testing a product plan, or identifying what could go wrong.

Federal acquisition compliance auditor for the active Theseus workspace, backed by live FAR/DFARS text via the vendored `ecfr` MCP. USE WHEN the user asks to audit FAR/DFARS clause coverage, validate that cited clauses actually exist in eCFR (catch fabricated or typo'd numbers), check whether a cited clause has been amended since the solicitation issued, validate regulatory references (NIST SP, DAFI, MIL-STD), check that every "shall" requirement has a deliverable, find missing compliance artifacts, audit proposal_instruction ↔ evaluation_factor coverage (UCF Section L↔M or non-UCF equivalent — FAR 16 task orders, FOPRs, BPA calls, OTAs), or "are we compliant with the proposal instructions?". Cross-references the workspace's clause / regulatory_reference / requirement / deliverable / compliance_artifact entities against live eCFR and flags gaps with severity. Format-agnostic. DO NOT USE FOR drafting compliant prose (use proposal-generator) or extracting clauses (Theseus pipeline does that automatically).

Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `cn-llm`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. China LLM Gateway - Unified interface for Chinese LLMs including Qwen, DeepSeek, GLM, Baichuan. OpenAI compatible, one API Key for all models. Use when: the user needs model routing, provider setup, or Chinese LLM access guidance.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `smart-search`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. Intelligent hybrid search combining web and academic sources via AIsa Smart Search endpoint. Best when you need both web and scholarly results. Use when: the user needs web search, research, source discovery, or content extraction.

Bun JavaScript runtime. Fast all-in-one toolkit with bundler, test runner, package manager. Use when working with Bun projects or considering Node.js alternatives. USE WHEN: user mentions "bun", "bun test", "bun build", asks about "Bun.serve", "bun install", "SQLite in Bun", "bunx", "performance comparison" DO NOT USE FOR: Node.js runtime - use `nodejs` skill instead DO NOT USE FOR: Hono/Elysia frameworks - use framework-specific skills DO NOT USE FOR: Language syntax - use `typescript` or `javascript` skills

Modern C++ (C++17/20/23) language and standard library. Covers RAII, move semantics, smart pointers, templates, concepts, ranges, coroutines, modules, std::expected, std::format, std::span, std::string_view. USE WHEN: user mentions "C++", "modern C++", "C++17/20/23", "RAII", "smart pointers", "templates", "concepts", "ranges", "move semantics", "std::expected", "std::span", "coroutines", "modules", "STL" DO NOT USE FOR: C (use a C-specific skill), C# (use `csharp`), Objective-C++, Carbon, kernel/no-exception subset (use `cpp-systems`)

Narzędzia deweloperskie wiersza poleceń (CLI) platformy Soneta (enova365, Triva). Używaj gdy użytkownik: (1) zarządza bazami danych przez `dbmgr` — tworzy, rejestruje, konwertuje, backup/restore, licencje, rozszerzenia (extensions), analiza, kompilacja; (2) przygotowuje bazę testową/demo z wiersza poleceń albo automatyzuje operacje na bazach w skrypcie/CI; (3) testuje działającą aplikację przez `buscall` — zdalnie steruje programem (nawigacja, formularze, gridy, edycja) i robi zrzuty ekranu; (4) uruchamia aplikację ramki `SonetaFrame` (`SonetaFrameNew`), konfiguruje źródła baz danych (`demo:`, `http`, `docker:`, `process:`, `orchestrator:`) albo pyta o plik ustawień `Settings_Product.json`; (5) pyta o składnię, komendy lub opcje `dbmgr`, `buscall`, `callmcp`, `SonetaFrame`; (6) wspomina „zarządzanie bazą enova", „baza demo", „konwersja bazy", „testowanie na żywej aplikacji", „ramka Soneta". Sięgnij też, gdy inny skill potrzebuje operacji na bazie lub weryfikacji zmian na uruchomionej aplikacji.

Run a co-sell with a partner on a named account and actually close together, not just trade a lead. It maps the account across both companies, sets who owns what so nothing falls between you, builds the joint value story neither of you tells alone, and plans the path to close so the partner is a force in the deal, not a spectator. Built for B2B partnerships and sales teams, customizable to your CRM and your co-sell motion. Trigger on "run a co-sell", "co-sell on this account", "map the account with our partner", "who owns what in this joint deal", "joint value story", or any partner co-sell request on a named account.

Configure rsyslog for centralized log collection with TLS encryption, custom templates, and log rotation. Generates server and client configuration files with GnuTLS stream drivers, x509 certificate authentication, per-host log segregation, and reliable queue settings for high-availability syslog infrastructure.

Summarizes, condenses, or extracts text, transcripts, and key points from URLs, articles, web pages, PDFs, podcasts, YouTube videos, and local files. Acts as a fallback transcription tool when the user asks to transcribe, digest, recap, or get the gist of a link, video, or document.

DashScope (Alibaba Cloud Bailian / 阿里云百炼) integration — image generation (qwen-image-2.0-pro), text-to-speech (qwen3-tts-flash), and ASR with word-level timestamps (qwen3-asr-flash-filetrans). Use when generating images via Qwen-Image, narrating via Qwen-TTS, or transcribing with word-level timestamps via Qwen-ASR.

Audit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a detection-only mode that flags patterns without rewriting.

Specjalistyczna wiedza o WŁASNOŚCIOWYM formacie plików form.xml platformy Soneta (enova365) — bez tego skilla Claude generuje błędne XML z nieistniejącymi elementami. ZAWSZE używaj tego skilla gdy użytkownik: (1) prosi o utworzenie lub modyfikację pliku pageform.xml, viewform.xml, form.xml, lookupform.xml lub gridform.xml dla platformy Soneta (enova365); (2) pyta o elementy DataForm, Page, Group, Grid, Field, Row, Stack, Flow, Command, Include, Appearance, GroupBy w Soneta; (3) pyta o składnię EditValue, DataContext, Visibility, RowCondition, Renderable, CaptionHtml, Footer, Class lub układ UI formularzy Soneta; (4) pokazuje istniejący plik form.xml/pageform.xml/viewform.xml i pyta o jego strukturę lub chce go rozszerzyć; (5) pyta o warunkową widoczność, formatowanie warunkowe (Appearance), bindowanie danych lub wzorce UI w Soneta/enova365.

The two model-touching halves of Worklink, shipped as one opt-in skill. (1) Planner: decompose a parent Chainlink issue into testable worklink:ready leaf subissues (mutates Chainlink only, never executes). (2) Ready-queue poller: discovers worklink:ready leaves and dispatches them by invoking `mimir worklink run` as a detached subprocess, up to the concurrent-claim cap — it never reimplements claim/evidence/transition. Opt-in (mimirbot yes, muninn no): `mimir skills install chainlink-orchestrator`, then set the env below to enable autonomous dispatch.

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.

See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio, video), and create real time alerts for events from live streams or desktop capture.