「exa」の検索結果

Use this skill when working with Telnyx communication APIs for SMS/MMS messaging, voice calls, phone number management, messaging profiles, webhook integration, two-way SMS conversations, bulk sending, message scheduling, or production deployment of telephony features. v2.0 includes official Telnyx documentation, production patterns from Twilio-Aldea (Ed25519 signature validation, provider-agnostic webhooks, idempotency), and TypeScript code examples.

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Systematically gather comprehensive travel itinerary requirements through structured discovery questions, MCP-powered research (Perplexity, Exa), and expert detail gathering. Use when users request travel planning, itinerary creation, or trip assistance requiring deep research and personalized requirements gathering. Outputs detailed requirements specification with day-by-day itineraries.

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Unified web and social media search across 5 providers (Brave, Tavily, Xpoz, Exa, Firecrawl). Auto-routes queries to the best API, supports parallel multi-provider search with deduplication, AI-generated answers, and social media search. Triggers on web search, find news, search Twitter, search Reddit, social media search, multi-provider search, omnisearch, research news, OSINT, search for, look up, find information about.

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Research UI component patterns across the component.gallery corpus — 60 canonical component types, ~95 production design systems, 2,600+ examples — plus an AI-era overlay (prompt inputs, tool-call cards, streaming status, citations) and composite patterns (command palette, app shell, agent console). Compare implementations, find alternative component names, ground frontend decisions in real-world precedent. Pairs with minoan-frontend-design for research-then-build workflows. Triggers on component patterns, how do others implement X, design system research, component comparison, AI chat components, agent UI patterns.

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Use when an output artifact, template, schema, example, or handoff field must stay aligned across commands, skills, docs, and validators.

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Produces structured markdown session continuation documents for multi-session workflows. Captures active work streams, decisions with rationale, knowledge-file deltas learned during the session, the exact files to load next conversation, ingested content, artifacts, and open items into an ingestion-optimized handoff. Carries pending KF updates and unresolved items forward across handoff chains so context never drops. Generates a closeout checklist and echoes the starter prompt to chat. Use when approaching context limits, wrapping up a session, or managing work across conversations. Trigger on: "create a handoff," "session closeout," "wrap up this session," "build session handoff," "BSH," "continue next session," "we're running out of context," "context is getting long." Do NOT use for Memory optimization, context budget analysis, project audits, deciding whether work is ready for autonomous/Claude Code execution (use rootnode-handoff-trigger-check), or summaries with no continuation intent.

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Backend conventions and patterns. Use when working on API routes, dependency injection, or hexagonal architecture in the backend.

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Design polychromatic ornamental patterns grounded in Alexander Speltz's classical ornament taxonomy. Builds on monochrome structural analysis by adding period-authentic color palettes, color-to-motif mapping, and rendering styles suited to painted, illuminated, and glazed ornament. Use when creating decorative designs where color is integral to the tradition (Islamic tilework, illuminated manuscripts, Art Nouveau), exploring how historical periods used color in ornament, or producing colored reference imagery for design, illustration, or educational materials.

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Design monochrome ornamental patterns grounded in Alexander Speltz's classical ornament taxonomy. Covers historical period selection, motif structural analysis, prompt construction for line art and silhouette rendering, and AI-assisted image generation via Z-Image. Use when creating decorative borders, medallions, or friezes in a single color, exploring historical ornament styles through generative AI, producing line art or pen-and-ink renderings of classical motifs, or generating reference imagery for design or educational materials.

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Generate jigsaw puzzles via generate_puzzle() or geom_puzzle_*() with parameter validation against inst/config.yml. Supports rectangular, hexagonal, concentric, voronoi, and snic puzzle types with configurable grid, size, seed, offset, and layout parameters. Use when creating puzzle SVG files for a specific type and configuration, testing generation with different parameters, generating sample output for documentation or demos, or creating ggplot2 puzzle visualizations.

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Formulate a quantum mechanics or quantum chemistry problem with proper mathematical framework including Hilbert space, operators, boundary conditions, and approximation method selection. Use when setting up a quantum mechanics problem for analytic or numerical solution, formulating a quantum chemistry calculation, translating a physical scenario into the Schrodinger or Dirac formalism, or choosing between perturbation theory, variational methods, DFT, and exact diagonalization.

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Identify insects using body plan analysis, dichotomous keys to order, wing venation, mouthpart type, antennae form, leg and tarsal structure, and confidence levels. Covers the fundamental hexapod body plan verification, a simplified dichotomous key to major orders, wing venation and type analysis, mouthpart classification, antennae morphology, leg specialization and tarsal formula, and a structured confidence assessment framework. Use when you need to identify an unknown insect beyond preliminary order placement, are working through a specimen for taxonomic study, want to distinguish between similar orders or families, or need to assign a confidence level to a field identification.

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Epistemic transparency — acknowledging uncertainty, flagging limitations, avoiding overconfidence, and communicating what is known, unknown, and uncertain with proportional confidence. Maps the HEXACO personality dimension to AI reasoning: truthful calibration of confidence, proactive disclosure of gaps, and resistance to the temptation to appear more certain than warranted. Use before presenting a conclusion, when answering questions where knowledge is partial or inferred, after noticing a temptation to state uncertain information as certain, or when a user is making decisions based on provided information.

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Apply the fail-early (fail-fast) pattern to detect and report errors at the earliest possible point. Covers input validation with guard clauses, meaningful error messages, assertion functions, and anti-patterns that silently swallow failures. Primary examples in R with general/polyglot guidance. Use when writing functions that accept external input, adding input validation before CRAN submission, refactoring code that silently produces wrong results, reviewing PRs for error-handling quality, or hardening internal APIs against invalid arguments.

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Scaffold a new R package with complete structure including DESCRIPTION, NAMESPACE, testthat, roxygen2, renv, Git, GitHub Actions CI, and development configuration files (.Rprofile, .Renviron.example, CLAUDE.md). Follows usethis conventions and tidyverse style. Use when starting a new R package from scratch, converting loose R scripts into a structured package, or setting up a package skeleton for collaborative development.

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Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.

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Use when examining ELF binaries with readelf, objdump, nm, or ldd: dependencies, symbols, sections, relocations, build IDs, or hardening, or when enabling RELRO, PIE, stack canaries, FORTIFY_SOURCE, CET, CFI, or seccomp filters, or checking a binary with checksec. Not for modifying binaries: use binutils. Not for runtime sanitizer builds: use sanitizers.

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Use when skill or knowledge activation is unreliable, or setup reaches activation reliability. Not for remote, credential, publish, deploy, or irreversible changes.

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Use when the user asks for a council, second opinions, or parallel investigation. Not for cross-examination of existing proposals: use cross-critique.

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Use when an exact symbol, path, entrypoint, or line range can bound a focused code question or patch proposal under a fixed source budget. Not for source changes or broad repository exploration.

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Release one current Proto UI work-item claim when it expired, became invalid, or the contributor stopped. Use only for the contributor's own recorded claim and only when the exact reversible GitHub mutation is authorized. Do not select replacement work, change readiness, or release another contributor's claim.

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Post one already selected Proto UI work-item claim as a reversible GitHub metadata mutation. Use after pui-select produced a current proposal and the exact claim has authorization, live permission, current readiness, and an idempotent write boundary. Do not select work, decide readiness, release claims, or widen the authorized wording.

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Publish one prepared Agent evidence packet as an additive Issue comment, including historical or closed Issues, under exact current authorization. Use after read-only Issue inspection and separately authorized evidence preparation. Do not reproduce, select work, upload assets, edit human text, claim, review, close, or change Issue metadata.

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Integrate one exact-head Proto UI pull request through either the ordinary independent-review path or a separately explicit current-user connected-operation decision. Preserve source, DCO, live platform enforcement and all deferred criteria; never manufacture approval or acceptance.

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