「goal」の検索結果

Generate a tailored AGENTS.md for any new project by interviewing the user about their skill gaps, project goals, and tech context. Load when the user asks to set up a project, initialize agents, create an AGENTS.md, bootstrap a repo, onboard agents to a codebase, or says "set up this project for agents". Also triggers on "write an AGENTS.md for this project", "configure agents for my repo", "project bootstrap", "agent onboarding", or when the user starts a new project and needs agent-ready configuration. Re-run when new context arrives (PRD written, stack changes, team changes) to update the AGENTS.md.

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Build the smallest, highest-signal context package for an AI coding task — goal, constraints, repo facts, boundaries, and a verification plan. Load when prompts are underspecified, the agent is missing key files or decisions, the user says "use the right context", "here's the repo", or when work is drifting due to missing constraints. Also triggers on "context engineering", "gather context", "what do you need from me", "before you start". Not for cross-session continuity (use memory-startup/memory-recall).

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Decompose an unknown quantity into 3-5 estimable factors and produce a defensible order-of-magnitude answer without needing precise data. Load when the user needs to size something without data — market size, resource requirements, effort estimates, user numbers, costs — or when a decision is blocked by "we don't know the numbers". Also triggers on "ballpark this", "rough estimate", "how big is this market", "how long would this take", "how many users", or when deep-thinking diagnoses a sizing/estimation frame. The goal is not precision — it is a defensible answer that enables a decision to be made. Based on Enrico Fermi's estimation method.

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Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforcement/curriculum learning, synthetic accessibility scoring, and chemical space exploration vs exploitation. Use when designing new chemical matter against a target, decorating a scaffold, linking fragments, or optimizing a hit for multiple ADMET / activity properties simultaneously.

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Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.

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Align protein structures using Foldseek 3Di, TM-align, US-align, DALI, or Foldmason for structural MSA. Predict, score, and superpose backbone coordinates when sequence identity is below the twilight zone or remote-homology detection is required. Use when sequence MSA fails (<25% identity), when the dark proteome is the target, when AlphaFoldDB / ESM Atlas search is needed, or when structural superposition is the goal.

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[62] VALIDATE. Final self-check before delivery. Verify goal alignment, completeness, correctness, and identify residual risks. Produces quality score (0-100) and delivery status. Use when completing any significant work, before handoff, or when you need confidence that work is ready.

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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability.

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Use this skill when building analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

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Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.

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绩效评估和述职报告生成器。自评、主管评语、KPI总结、晋升述职、SMART目标设定、360反馈撰写。. Use when you need performance review capabilities. Triggers on: performance review. 绩效评估助手。自评、上级评语、OKR复盘、KPI分析、改进计划、SMART目标设定、360反馈撰写。Performance review assistant with self-assessment, manager feedback, OKR review, SMART goals, 360 feedback writing. 绩效考核、年终评估、360评估。Use when writing performance reviews.

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Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

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Gather and persist audience, brand, UX goals, React framework, Tailwind setup, and component defaults for future design work. Use when the user asks to establish or update reusable project design guidance. A request to build UI can proceed with existing context without running setup.

日本語の概要は準備中です。原文の説明を表示しています。

Rigorous visual validation expert specializing in UI testing, design system compliance, and accessibility verification. Masters screenshot analysis, visual regression testing, and component validation. Use PROACTIVELY to verify UI modifications have achieved their intended goals through comprehensive visual analysis.

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Import a single webpage from any URL into canonical EDS block format — structured HTML that authors edit in DA. Scrapes the page, analyzes structure, maps to existing blocks, and generates HTML for immediate local preview. Also triggered by terms like "migrate", "migration", or "migrating". Use this when the goal is canonical EDS authoring; use the snowflake skill instead when the user wants to preserve the original DOM byte-for-byte (static-to-EDS overlay).

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Arithmetic probes ({{7*7}}→49) confirm the injection point but are not proof of impact. The real goal is OS command execution. Arithmetic detection also fails silently when the app echoes the input back (e.g. inside an HTML attribute like <input value='{{7*7}}'>), producing a false negative even when injection exists.

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Expert in CrewAI - the leading role-based multi-agent framework used by 60% of Fortune 500 companies. Covers agent design with roles and goals, task definition, crew orchestration, process types (sequential, hierarchical, parallel), memory systems, and flows for complex workflows. Essential for building collaborative AI agent teams. Use when: crewai, multi-agent team, agent roles, crew of agents, role-based agents.

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Send personalized LinkedIn direct messages to a list of existing 1st-degree connections via browser automation. Use when the user wants to message LinkedIn connections with AI-personalized outreach — e.g. nurturing leads, following up after events, reconnecting with contacts, or announcing something. Takes a data file (CSV/TSV) or plain list with connection names and companies, asks for outreach context/goal, generates a tailored message per person, and sends each one via browser automation. Handles message compose flow, character limits, and incremental status tracking.

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Fast X Intelligence CLI (Rust) — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", (2) user wants real-time monitoring with "watch", (3) user needs AI-powered analysis with Grok ("analyze", "sentiment"), (4) user needs intelligence reports ("report"), (5) user wants to track followers ("diff"), (6) user needs trending topics ("trends"). Also supports: bookmarks, likes, following (OAuth), x-search, collections, CSV/JSON/JSONL export. Non-goals: Not for posting tweets, not for DMs, not for enterprise features.

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X Intelligence CLI — search, analyze, and engage on X/Twitter from the terminal. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "search x", "find tweets about", "monitor x for", "track followers", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic, (4) user needs real-time monitoring ("watch"), (5) user wants AI-powered analysis ("analyze", "sentiment", "report"). Also supports: bookmarks, likes, following (read/write), trending topics, Grok AI analysis, and cost tracking. Export as JSON, JSONL (pipeable), CSV, or Markdown. Non-goals: Not for posting tweets, not for DMs, not for enterprise features. Requires OAuth for user-context operations (bookmarks, likes, following, diff).

日本語の概要は準備中です。原文の説明を表示しています。

Monitors a specified object against explicit stopping criteria and distinguishes replica convergence, iterative progress, and workflow terminal state. NOT for execution or setting goals.

日本語の概要は準備中です。原文の説明を表示しています。

Model an organization with BDI-inspired perceptions, expressed goals, accommodations, and levels of agency. Use for socio-technical diagnosis where actors interpret the same situation differently and agreement is partial. NOT for individual AgentSpeak execution, normative conflict algorithms, or ordinary workflow diagrams.

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Design an individual agent's belief, goal, intention, and reconsideration model. Use when specifying autonomous decision state, commitment policy, or recovery from failed plans. NOT for AgentSpeak interpreter mechanics, organization modeling, normative conflicts, or multi-agent execution waves.

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Design an agent's handling of obligations, prohibitions, permissions, and conflicts among norms and goals. Use when an autonomous agent must decide which norms apply and what to do when they conflict. NOT for simple fixed policy checks, ordinary BDI commitment design, or organizational metaphor.

日本語の概要は準備中です。原文の説明を表示しています。