「explanation」の検索結果

Fix bugs and broken behavior when there is enough evidence to act on a repair path. Use for errors, crashes, incorrect results, API failures (500, 404, 403), CORS problems, database exceptions, broken rendering, duplicated or wrong data, off-by-one mistakes, timezone/date bugs, broken forms, config-caused runtime failures, and regressions. Trigger when the user wants the bug repaired and the conversation already contains a clear failing area, a reproducible failing test, a concrete error path, or a prior diagnosis to implement. Do NOT use for new features, pure explanation, architecture discussion, broad research, or bug reports where the main need is figuring out why the behavior happens — use diagnose for that.

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This skill should be considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.

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Diagnose HitKeep traffic drops, spikes, source shifts, and suspicious changes. Use when traffic, sessions, visitors, pageviews, events, or conversions changed; when a deploy may have affected measurement or behavior; or when search, referral, direct, campaign, and bot explanations need to be separated.

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Converting a supplied prompt into an executable specification: detects vague quality/quantity/explanation/style/design/technical/judgment wording, role and persona theater, and self-contradiction, then replaces each with a numeric bound, an observable behavior, or a scorable criterion — with a per-term ledger of what changed and what stayed open. Don't use for AI system design, RAG, or eval harnesses (Oracle), PRD/SRS authoring (Scribe), spec conformance verification (Attest), or SKILL.md normalization (Gauge).

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Before any explanation or answer, require the learner to produce a free-recall attempt and confidence rating. Use when a student wants help understanding or reviewing a topic — this skill ensures the AI works from what the learner already knows.

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Redesign a direct instruction sequence to include productive struggle before the explanation phase. Use when teaching concepts that benefit from failure-first approaches.

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Design a visual complement to verbal content using dual coding principles for stronger encoding. Use when creating slides, diagrams, posters, or visual explanations of complex concepts.

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Design deliberately flawed examples that develop error-detection skills and deepen understanding. Use when students make characteristic errors and need practice spotting mistakes.

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Create an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.

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After any AI-generated explanation, require the learner to identify one place it could be wrong, one thing to check, and one source to consult. Builds epistemic vigilance — treats AI output as a claim to evaluate, not truth to absorb.

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Shape output for a reader with ADHD. Use this skill whenever responding to ANY user message including coding tasks, debugging, explanations, planning, and casual conversation. Output should lead with concrete next actions, number multi-step work, externalize state across turns, suppress tangents, give specific time estimates, and make wins visible. Trigger even on casual messages and even when the user did not explicitly ask for brevity.

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Make AI coding-agent messages to humans clear and easy to follow. Use for every user-facing update, explanation, review, question, and handoff in this repository, or when the user asks to simplify or rewrite an agent message.

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Classify, write, and audit documentation per Diátaxis (diataxis.fr) — the four-quadrant method (tutorials · how-to guides · reference · explanation). Encodes the compass as a decision procedure, each quadrant's contract as hard rules, and an executable mixed-mode audit. Project-agnostic; the per-repo doc-location mapping lives in a repo rule of the project's own (kolu: `.apm/instructions/diataxis.instructions.md`). Use when writing any user-facing doc, structuring a docs site, or auditing existing docs for mixed modes.

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Explain a GitHub pull request as an English Markdown walkthrough and return a Plannotator share link. Use for PR explanations, walkthroughs, or review preparation.

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Write, restructure, classify, and review documentation with the Diataxis framework. Use when the user asks to create, improve, audit, or reorganize documentation of any kind: knowledge bases, help centers, onboarding guides, process docs, manuals, runbooks, product or API docs, tutorials, how-to guides, references, explanations. Also use when the user mentions Diataxis, docs taxonomy, or documentation architecture, or asks why a document feels confusing. Also use for Simplified Technical English (ASD-STE100) or controlled-language rewrites of English technical docs. Not for marketing, legal, sales, press, or fiction writing unless the user wants a Diataxis-style analysis.

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Socratic questioning partner named Gadfly for deep learning through dialogue. Use this skill when the user wants to learn, understand, or explore a topic through questions rather than explanations. Trigger when the user says "teach me about...", "help me understand...", "I want to learn...", "ask me questions about...", "quiz me", "Socratic method", "Gadfly", or wants to deeply understand something through dialogue rather than passive reading. Also trigger when the user provides a text or document and wants to be questioned about it, or wants to check their own understanding of a concept.

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Analyzes insurance scenarios by referencing specific sections of the Life Insurance Act, Insurance Contracts Act, and Corporations Act, providing direct quotes and explanations.

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Guide a researcher step by step into an unfamiliar research field, or decode a paper, abstract, figure caption, or referee comment they cannot parse. Builds understanding in rungs (motivation, vocabulary, core framework, methods, frontier), anchored to what the user already knows, with a checkpoint before each advance. Use when the user says they are new to a field, asks what a research area or method is, says an explanation was too technical, asks to be walked through something step by step, asks for a reading path, or supplies dense research text. Trigger even when the user only names an unfamiliar field or pastes an abstract without asking to be taught. Do not trigger for a one-line summary, a short overview request, or a direct factual answer; do not use it for translation, editing, search, debugging, or specialist questions inside the user's own field. Also trigger in other languages, including Chinese such as 入门, 一步一步讲, 看不懂, 这篇论文讲什么, 帮我理解这个领域.

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Regression analysis, ANOVA, generalized linear models, Bayesian methods, and model selection. Covers the full modeling workflow from problem formulation through diagnostics -- linear regression, logistic regression, Poisson regression, mixed-effects models, prior specification, posterior inference, AIC/BIC comparison, cross-validation for model selection, and assumption checking. Use when fitting models, testing hypotheses, or selecting among competing statistical explanations.

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Retroductive hypothesis sampling via MCMC: given observations, importance-sample explanations weighted by P(observation|hypothesis) using Gay.jl colored particles as hypothesis candidates.

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Formal oracle for abductive inference that selects the minimal hypothesis best explaining a set of observations. Provides three sub-oracles: MCMC via monad-bayes, Gemini for natural language, and propagator networks for constraint domains. Use when performing hypothesis selection, explaining observations, or solving inference-to-best-explanation problems.

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Describe images, screenshots, diagrams and charts from visual inspection. Preserve visible text, counts, labels, directions and uncertainty; distinguish observation from interpretation. Use for image summaries, screenshot explanations and diagram descriptions.

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Summarize files or a requested directory scope from actual contents. Extract code, config, data and document evidence, preserve exact counts and source locations, and disclose incomplete or unsupported acquisition. Use for file summaries, code explanations and configuration overviews.

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Update IWE with change explanations. Agent calls update.sh, parses CHANGELOG, explains what changed, helps adapt updates to user customizations.

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