「recognition」の検索結果

Being a constructive participant in networked communities. Covers digital footprint management, online etiquette and professional communication, collaborative tools, attribution and copyright, cyberbullying recognition and response, and the responsibilities that come with amplification. Use when helping learners think about how to behave online -- not what is technically allowed, but what is actually healthy for themselves and their communities.

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。

Distributional analysis of environmental benefits and burdens across communities. Covers the historical origins of environmental justice in the U.S. civil rights tradition, siting and exposure disparities, indigenous rights and land stewardship, climate justice at global and intergenerational scales, procedural vs. distributional vs. recognition justice, and the environmental justice screening tools used by regulators. Use when analyzing who bears environmental harm and who receives environmental benefit, or when designing interventions whose distributional consequences matter.

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。

Entrepreneurship, innovation, and disruption for starting, scaling, and defending new ventures. Covers opportunity recognition, jobs-to-be-done, the disruptive innovation framework, sustaining vs disruptive innovation, platform businesses, network effects, minimum viable product, customer development, and the startup lifecycle from idea to exit. Use when evaluating a venture idea, positioning a new product, interpreting a competitive threat, or designing a platform.

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。

Computational thinking as a problem-solving discipline independent of programming languages. Covers the four pillars (decomposition, pattern recognition, abstraction, algorithm design), computational problem-solving methodology (understand, decompose, generalize, formalize, verify), abstraction levels (from hardware through user interface), modeling and simulation, automata and formal languages (DFA, NFA, regular expressions, context-free grammars, Turing machines), computational complexity classes (P, NP, NP-complete, undecidable), and constructionist pedagogy (learning by building, Logo, Scratch, physical computing). Use when approaching unfamiliar problems, teaching problem-solving strategies, analyzing problem complexity, or bridging between domain knowledge and computational solutions.

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。

Recognition and mitigation of systematic reasoning errors documented in the heuristics and biases tradition. Covers confirmation bias, availability, anchoring, representativeness, framing effects, hindsight bias, overconfidence, and motivated reasoning. Each bias is presented with its mechanism, diagnostic signal, and structured mitigation. Use when you suspect your own or another reasoner's conclusions may be shaped by systematic cognitive distortion rather than evidence.

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。

Practical naked-eye and binocular sky observing. Covers dark adaptation, limiting magnitude, constellation recognition, star hopping, the messier and Caldwell catalogs accessible without a telescope, the Moon, planets, meteor showers, aurorae, and the ethics and habits of observing under light-polluted and dark skies. Use when teaching someone to find their way around the sky, planning a naked-eye session, or choosing a first binocular tour.

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。

Run a custom computer-vision prompt against an image with a local vision LLM. Wraps kuzco's tool_llm_image_custom() ellmer tool. Use when none of the specialized kuzco image skills (classification, OCR, recognition, sentiment, alt text) fit the task.

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。

Binary visualization for human pattern recognition - Ghidra plugin by Chris Domas (xoreaxeaxeax)

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。

Apply systematic problem-solving techniques for marketing challenges including campaign complexity (simplification cascades), creative blocks (collision-zone thinking), recurring campaign patterns (meta-pattern recognition), assumption constraints (inversion exercise), audience scale uncertainty (scale game), and dispatch when stuck. Techniques derived from proven problem-solving frameworks adapted for marketing execution.

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。

Codified expertise for returns authorization, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management. Informed by returns operations managers with 15+ years experience. Includes grading frameworks, disposition economics, fraud pattern recognition, and vendor recovery processes. Use when handling product returns, reverse logistics, refund decisions, return fraud detection, or warranty claims.

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。

Identifies audio content using Chromaprint/AcoustID fingerprinting, Shazam API recognition, and ACRCloud monitoring. Matches music, speech, and ambient audio against fingerprint databases.

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。

Reference for advanced data structure patterns used in competitive programming and technical interviews. Covers heaps, monotonic stacks, tries, segment trees, Fenwick trees, stack-based parsing, and ordered sets with Python templates, recognition signals, and edge case guidance.

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。

Reference for dynamic programming patterns — recognition signals, constraint mapping, Python templates, edge cases, and common mistakes for 8 core DP techniques

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。

Reference patterns for graph algorithm problems including BFS, DFS, Dijkstra, topological sort, union-find, MST, Bellman-Ford, and bipartite checking. Provides recognition signals, Python templates, edge cases, and common mistakes for each technique. Use when solving problems involving graphs, trees, shortest paths, connectivity, or dependency ordering.

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。

Reference for string algorithm patterns — KMP, Z-function, Rabin-Karp, Manacher's, string hashing, suffix arrays, and Aho-Corasick. Covers recognition signals, core ideas, Python templates, edge cases, and common mistakes for each technique.

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。

Evaluates multi-jurisdictional restructuring with Chapter 15 recognition, COMI analysis, and parallel proceeding coordination. Use when analyzing cross-border insolvency, assessing jurisdiction selection, or coordinating multi-country restructurings.

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。

Automated brownfield codebase analysis with weighted keyword scoring, three-stream analysis, and design pattern recognition. Detects project type, frameworks, dependencies, architecture patterns, and generates comprehensive project profile.

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。

Master binary analysis patterns including disassembly, decompilation, control flow analysis, and code pattern recognition. Use when analyzing executables, understanding compiled code, or performing static analysis on binaries.

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。

AI intentional non-action — deliberate stopping without clearing, assessment, or rebalancing. Recognition that sometimes the most productive response is no response. Every other self-care skill produces output; rest produces silence. Use when all tending skills feel like more activity rather than less, when the system is functioning well but at high utilization, after sustained intensive work, or when the impulse to optimize is itself the problem.

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。

Observe and assess a garden using a structured sensory protocol adapted from Coordinate Remote Viewing. Covers pre-entry clearing (meditate checkpoint), Stage I gestalt impression, Stage II sensory layer (leaf, stem, root, soil), Stage III pattern recognition with AOL management, and garden health triage matrix (heal checkpoint). Use before any intervention, when plants show stress symptoms, at seasonal transitions, when evaluating a new garden site, during regular health monitoring, or after extreme weather events such as frost or heat waves.

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。

Identify and safely gather edible and useful wild plants. Covers safety rules and deadly plant recognition, habitat reading, multi-feature identification methodology, the universal edibility test, sustainable harvesting practices, preparation methods, reaction monitoring, and building knowledge with beginner-friendly universal species. Use when supplementing food supply in a wilderness or survival setting, needing medicinal or utility plants, identifying plants around camp for safety, or in long-term scenarios where foraging extends available rations.

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。

AI strength recognition — scanning for what is functioning well and understanding why. The complement to heal, which scans for drift and problems. Gratitude builds structural knowledge from working patterns: what you appreciate, you understand; what you understand, you can build on. Use after completing a task successfully, during heal when everything reads as healthy, when confidence is low and needs grounding in evidence, or periodically to counterbalance the natural bias toward problem detection.

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。

Spot patterns appearing in 3+ domains to find universal principles

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。

Use this skill when the user needs to set up bookkeeping, track revenue and expenses, prepare for taxes, choose accounting software, understand SaaS revenue recognition, or manage the financial operations of their bootstrapped business. Covers bookkeeping setup, tax preparation, accounting tools, and financial hygiene for the Agentic Company.

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。