「ara」の検索結果

Requires OFOX_API_KEY — create one at https://app.ofox.ai. Shared execution layer for the Ofox video generation API (api.ofox.ai) — creates a video job, polls it to completion, downloads the finished mp4 from a persistent CDN URL, and reports the real cost. This is a library skill, not a standalone user-facing one — it is invoked by scenario skills such as seedance-short-drama, seedance-ad-creative, and seedance-product-video, which build model/prompt/resolution choices for a specific use case and then call into this skill's script rather than re-implementing the API calls. Load this skill directly only when a user explicitly names the Ofox video API, asks to call it with specific low-level parameters, or asks to debug/resume a stuck or failed Ofox video job by job id — for a plain scenario request ("make me a short drama scene", "generate a cinematic ad clip"), use the relevant scenario skill instead, which itself depends on this one.

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Pre-meeting research and talking points generator. Researches the person and company, pulls CRM history, and generates a structured briefing with agenda, talking points, objection handlers, and recommended asks.

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Full daily team standup across all 6 verticals: Sales, Social Media, Content, SEO, Creative, and Strategy. Spawns all vertical agents in parallel, collects reports, and presents a unified standup summary. Run at 9 AM daily.

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An innate exploratory drive that guarantees no graph node remains permanently invisible to an agent population. After a warm-up period (step > 3), each agent fires a coverage scan with probability |unseen_nodes| / |all_nodes|. When triggered, the agent teleports directly to the globally unseen node with the highest belief uncertainty, works it, and returns control to the normal action-selection loop. Probability is self-annealing: it starts near 1.0 when almost everything is unseen and decays toward 0.0 as coverage saturates, requiring no manual schedule. The mechanism is "innate" (hard-coded into the agent step loop) as distinct from the "adaptive" EFE path, which requires local neighbors and learned precision weights. Together they form a two-layer exploration architecture: adaptive for locally-guided foraging, innate for topological completeness.

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Interpret and design bounded FIPA communicative-act exchanges using XC00037H semantics while keeping delivery, authority, and external effects separate. NOT for proving delivery, task authorization, or external effect completion.

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Foundational impossibility result proving consensus cannot be guaranteed in asynchronous systems with even one faulty process

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Use when introducing a feature flag system, choosing between release flags / experiment flags / operational flags / kill switches / permission flags, designing percentage rollouts, building kill-switch + circuit-breaker patterns, structuring evaluation contexts (user IDs, plan tier, region), or building flag-cleanup discipline. Triggers: LaunchDarkly / GrowthBook / Unleash / Flagsmith / OpenFeature, percentage ramp, sticky bucketing, kill switch wired to alerting, "we still have flags from 2 years ago", flag debt, OpenFeature provider, evaluation context, default value on provider failure. NOT for A/B test statistical analysis (separate skill), traffic-split routing at the edge, build-time bundler defines, or environment-based config.

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Use when optimizing Docker builds with BuildKit, designing multi-stage Dockerfiles, leveraging cache mounts, building multi-arch images, choosing distroless vs alpine, or signing images with cosign. Triggers: docker build slow, layer cache not hitting, npm install / pip install reruns, multi-stage final image bloat, glibc vs musl issues, RUN --mount=type=cache, BUILDKIT_INLINE_CACHE, registry cache exporters, qemu emulation for arm64, COPY ordering for cache. NOT for Docker daemon admin, Kubernetes-specific image policies, container security scanning workflows, or Buildpacks (different paradigm).

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Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).

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Parses complex problems into candidate DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies and identifies candidate parallelization opportunities. Activate on 'build dag', 'create workflow graph', 'decompose task', 'execution graph', 'task graph'. NOT for simple linear tasks or when an existing DAG structure is provided.

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Professional CV and resume builder transforming career narratives into ATS-optimized, multi-format resumes. Integrates with career-biographer for data and competitive-cartographer for positioning. Generates PDF, DOCX, LaTeX, JSON Resume, HTML, and Markdown. Activate on 'resume', 'CV', 'ATS optimization', 'job application'. NOT for cover letters, portfolio websites (use web-design-expert), LinkedIn optimization, or interview preparation.

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Validates typed DAG dependency declarations, returns Kahn linear extensions or generations and residual cycle witnesses, and identifies changed consumers for revalidation. NOT for constructing graphs, scheduling resource capacity, granting effects, or executing nodes.

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Analyze hierarchical DAG-like systems by separating undirected substrate from ordering metadata, then classifying diamonds, mixers, shortcuts, and hidden cycle structure. Use for workflow architecture, citation or genealogy DAG comparison, and information-flow diagnosis. NOT for ordinary cycle detection in arbitrary graphs, one-node runtime debugging, or systems with no real ordering constraint.

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Produce feasible non-preemptive DAG schedules from declared predecessors, durations, gates, capacities, and calendars. NOT for authorizing task execution or hiding resource and calendar infeasibility.

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Collage as a web design aesthetic — overlapping elements, mixed media, cut-out shapes, scrapbook layouts, and editorial magazine spreads adapted for the web. CSS techniques for layered compositions using z-index stacking, clip-path, mix-blend-mode, parallax layering, and grid-breaking layouts. Activate on 'collage web', 'editorial layout', 'magazine layout', 'overlapping elements', 'scrapbook', 'cut-out aesthetic', 'mixed media web', 'layered composition', 'grid-breaking', 'editorial web design', 'fashion website layout', 'David Carson'. NOT for photo collage/gallery grids (use collage-layout-expert), maximalist density (use maximalist-web-design), neobrutalism (use neobrutalist-web-designer).

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Expert in cluttering -- the lesser-known fluency disorder characterized by rapid/irregular speech rate, excessive disfluencies, and frequent ADHD comorbidity. Covers differential diagnosis from stuttering, assessment protocols, therapy approaches (rate control, self-monitoring, pragmatic awareness), technology-assisted intervention, and AI tools for people who clutter. Activate on 'cluttering', 'rapid speech disorder', 'speech rate too fast', 'speech disfluency not stuttering', 'disorganized speech', 'ADHD speech problems', 'cluttering vs stuttering', 'speech intelligibility', 'mazed speech', 'telescoping words'. NOT for stuttering-only treatment (overlap is common but they are distinct), hearing disorders, or voice disorders (pitch, resonance).

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Audit whether an enforced-coordination MCP has actually shrunk its ~19 legacy etiquette verbs into the 5 enforced tools — work/act/ask/recall/status — each carrying one denial shape and one transcript event, migrated through a real retirement path (intake-metadata, alias, or doc-history — never a parallel runtime), with zero legacy-verb calls once a body reaches compliance mode C4+. Use when reviewing a broker-collapse migration plan, gating a body's move from advisory (C0-C3) to enforced (C4+) coordination, or verifying IT-018 Broker Collapse compliance. NOT for the inbound trigger→spawn boundary that decides whether an event may spawn an agent at all (use fleet-event-spawn-trust), the capability-token cryptographic mechanism behind a denial (use agentic-zero-trust-security), designing how a swarm of agents invokes and shards work (use swarm-invocation-designer), or auditing an individual PR's mergeability (use agent-pr-authoring).

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Produces a narrow-interval quality signal for a WinDAGs skill that a third party can verify without inspecting model weights or method internals. The mechanism is attribution-kNN over a tamper-evident outcome log (task→skills→accept/reject store), combined with a conformal-prediction calibration certificate that provides a formal coverage guarantee. Thompson/Beta sampling is explicitly rejected as a category error: it produces a selection signal for stationary i.i.d. rewards, not an attestation signal for context-dependent LLM output quality. The resulting bundle — outcome-log Merkle root + conformal threshold + optional TEE guardrail signature — constitutes a "narrow-interval trust" credential: verifiable, bounded, and internals-opaque.

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Design AgentSpeak-style BDI plan libraries with explicit event, context, failure, and authority boundaries. NOT for treating BDI plans as safety approval or guaranteed execution.

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Safety-case design for always-on agents with episodic memory. Covers data hygiene, privacy and security risk surfaces, cost controls, scope, user dependency concerns, retention, incident containment, and responsible deployment evidence. It identifies hazards and asks for named controls, tests, owners, and residual uncertainty; it does not provide legal, clinical, youth-safety, or jurisdictional determinations. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).

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Design and audit a pricing function for variable-cost agent labor. Choose among per-seat, metered, credits, hybrid, and outcome pricing; name buyer value and cost metrics separately; calculate a reproducible cost floor; require pre-commitment guardrails; and stress-test declared personas. Use for offline pricing-design evidence, not billing implementation or runtime control. NOT for production billing, payment collection, or runtime spend enforcement.

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Design or review a declared control-command profile and its verb/backend lifecycle matrix. Distinguish policy denial, unsupported capability, delivery acknowledgement, independently observed effect, and unknown outcome; bind authorization to principal, target, scope, current policy, expiry, and fencing epoch. NOT for claiming runtime correctness, proving an adapter from declarations, or approving a control-panel button without independent runtime evidence.

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Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.

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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

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