153건 · 관련도순
Full-spectrum product research pipeline. Runs competitive analysis, technology trend scouting, user feedback analysis, and feature ideation. Triggers: on: research, competitive research, market research, feature discovery, what should we build next.
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Produces a DRAFT product requirements document from the discovery notes, interview summaries, support themes, analytics notes and stakeholder messages the user provides: problem statement, target users, goals with measures as stated, numbered requirements each with a testable acceptance criterion, non-goals, constraints, dependencies and open questions, with every statement tagged evidenced, assumed or UNKNOWN so each assumption is visible for the product owner to confirm. Use when the user asks to "write a PRD", "draft the product requirements", "turn these discovery notes into requirements", "document what this feature needs to do" or "build the requirements doc for this epic". Do not use for supplier-facing requirements in a tender, use rfp-requirements-pack instead; for a technical design decision, use architecture-decision-record; for the change ticket that ships the work, use change-request-pack. Drafts for human review; never approves, authorises or signs off.
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web アプリの機能を構造化して書き下すワークフロー。新規/既存の 2 モード、5 フェーズで構造化（先行事例調査は並列3エージェント、Reader Test 付き）。「機能を考えたい」「機能定義したい」「web アプリ作りたい」「機能から設計したい」「新しい機能」で発動。※ 曖昧な状態の掘り下げは deep-interview、要件統合は discovery-council、設計は design を使う。
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Implement, review, or improve in-app tips and onboarding using Apple's TipKit framework. Use when adding feature discovery tooltips, onboarding flows, contextual tips, first-run experiences, coach marks, or working with Tip protocol, TipView, popoverTip, tip rules, tip events, or feature education UI.
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Selects biomarker features from high-dimensional omics data using Boruta all-relevant selection, mRMR, LASSO/elastic-net, and stability selection, while controlling the leakage, irreproducibility, and correlated-feature traps that make most published signatures fail to replicate. Use when identifying candidate biomarkers, deciding between an all-relevant and a minimal-optimal selector, or judging whether a selected gene set is reproducible. For unbiased performance estimation of the resulting model see machine-learning/model-validation; for interpreting a trained model see machine-learning/prediction-explanation.
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Builds diagnostic and prognostic classifiers on omics feature matrices with regularized logistic regression, random forest, and gradient-boosted trees, handling the p>>n regime, batch shortcut learning, class imbalance, and probability calibration. Use when building a classifier from expression, methylation, or variant data, choosing an algorithm for high-dimensional small-n data, or diagnosing a suspiciously perfect AUC. For unbiased evaluation see machine-learning/model-validation; for feature selection see machine-learning/biomarker-discovery; for time-to-event outcomes see machine-learning/survival-analysis.
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Explains ML predictions on omics data with SHAP, LIME, and permutation importance, handling the correlated-feature trap, the conditional-vs-interventional Shapley choice, and the attribution-is-not-causation boundary. Use when interpreting an omics classifier, debugging shortcut/batch learning, or deciding whether an attribution ranking can be trusted as biology. For validated feature selection see machine-learning/biomarker-discovery; explanations are not a selection method.
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Audit or design server-side indexes, directories, reputations, or aggregates that are DERIVED from traffic a platform witnesses (chain heads, run verdicts, heartbeats, publish activity) so that consent gates the derivation, not merely the read: no shadow index over non-consenting principals, post-consent-only evidence windows, retention bounds and delete-propagation into derived rows, activity-oracle threat modeling, and audit-logged ranking discretion. Use when building a capability directory / whois from witnessed activity, a reputation ledger from settled outcomes, vitals aggregation across tenants, or any "the yellow pages can't lie because they index signatures" feature. Keywords: shadow index, derived index, consent gates derivation, activity oracle, phone book not a log, delist propagation, ranking weight audit, k-anonymous aggregate, subpoena surface. NOT for the consent-screen UX and scope-ladder mechanics themselves (use local-first-tenancy-boundary), reputation scoring math and Sybil economics (use agent-identity-continuity-reputation), or discovery-layer architecture L1/L2/L3 (use agent-discovery-directories-guilds).
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Pipeline that turns a big system idea into briefs for an agent fleet. Use when Arman says 'let's plan out X', 'build or overhaul the X system', 'create the vision and plan for X', 'do the full discovery process', 'get this ready for a fleet', or 'do what we did for education', or when carrying forward a VISION, COMPETITIVE_INSIGHTS, roadmap, or briefs doc. NOT for one feature in a live system (use build-sub-feature).
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Index-based file discovery using ABOUTME headers. Use INSTEAD of grep or Explore agent when searching for files by purpose or feature. Faster and more accurate than scanning code. Invoke this skill when user asks "which files handle X", "where is Y implemented", or when you need to find files related to a feature or task.
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Find Laravel packages for specific features through LaraPlugins.io MCP, a connection to its package search tools. Check maintenance indicators, release history, and Laravel/PHP compatibility to compare candidates before adding a package to a project.
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Grok Bot의 claude-mem에서 완료한 작업을 검색 가능한 XML 기록으로 정리합니다. 대기나 초기화처럼 기록이 필요 없는 상태는 별도 표시로 구분합니다.
Map an existing codebase into seven documents covering its technology, structure, architecture, conventions, integrations, tests, and concerns. Link findings to file evidence, mark unknowns, and highlight differences between stated plans and the actual implementation.
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Manage Jira issues, build JQL searches, and design project workflows and reports. Use bundled scripts to generate search queries and check workflow designs, with guidance on which operations require Jira’s interface or API.
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Manage a Kortix project from the terminal: start and monitor agent sessions, store secrets, open change requests for review, and call connected services. The skill points agents to the current command reference for detailed operations.
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Assess WPS, a router feature for easy Wi-Fi setup, for weaknesses in PIN authentication. The skill covers device discovery, offline and online testing, lockout behavior, and how a recovered PIN can expose the network password.
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Turn user research and complaints into a clear problem statement. Identify who is struggling, their desired outcome, barriers, root causes, constraints, and emotional impact, then summarize the problem in one sentence for team discussions or product planning.
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Structure customer research around what people want to accomplish, the difficulties they face, and the benefits they seek. Explore practical tasks, social perceptions, and emotions to clarify unmet needs and guide product positioning or priorities.
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Create a technical design document before implementation by answering questions about the problem, scope, architecture, risks, and delivery plan. The skill adjusts sections to project size and covers security, testing, monitoring, and recovery where relevant.
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Coordinate work across independent Squad installations by discovering their capabilities and delegating tasks across repositories. It guides context sharing, acceptance criteria, and progress tracking, while distinguishing persistent Squad teams from temporary groups of agents.
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Investigate GraphQL APIs for unauthorized data access, unsafe updates, and permission inconsistencies with REST APIs. The skill covers schema discovery, checks across users and organizations, and validation steps that turn suspected weaknesses into reproducible findings with concrete impact.
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Guide site integration work from capability discovery and authentication choices through implementation and validation. Cover account features, administrative resources, check-ins, or native editor usability, while documenting evidence, supported behavior, and paths that remain unverified.
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Process mass spectrometry data in Python with PyOpenMS. Read common file formats, smooth and normalize signals, detect peaks, align samples, and process peptide identification results for protein and metabolite quantification workflows.
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Turn requirements into a reviewed technical design. Examine existing code and relevant technologies, define component responsibilities and interfaces, plan files and tests, and record research findings and the reasons behind design decisions.
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