「systematic」の検索結果

Debugs crashes, regressions, flakes, and production bugs systematically. Use when diagnosing stack traces, logs, or profiling data; not perf tuning or incident command.

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Investigate data incidents and find root causes using Monte Carlo's observability data. Guides the agent through systematic investigation: alert lookup, lineage tracing, ETL checks, query analysis, and data profiling. Activates when a user asks about data issues, incidents, alerts, or why data looks wrong.

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Guide users from coverage analysis to monitor creation. USE WHEN user asks what should I monitor, where are my gaps, improve coverage, or wants a systematic approach to monitoring across their data estate.

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Systematic code review skill covering both requesting a review (pre-commit checklist) and receiving and responding to review feedback. Checks code quality, security, test coverage, architectural alignment, and documentation before any code is committed.

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Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write code.

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Use when users request Android competitor research, systematic feature or interface mapping, evidence screenshots, interaction coverage, comparison-ready product dossiers, or Android system-boundary verification without APK decompilation.

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Systematic debugging with persistent state across context resets

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Systematic debugging with root cause investigation. (gstack)

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Design a mastery experience sequence that systematically builds student confidence in a skill they avoid. Use when students say 'I can't do this', avoid tasks, or show learned helplessness.

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Design a checking-for-understanding protocol with specific techniques for each lesson stage. Use when planning systematic comprehension checks during explicit or direct instruction.

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When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.

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4 阶段根因调试：在修复之前理解 bug。

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4-phase root cause debugging: understand bugs before fixing.

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Systematic backlink building for indie founders. Covers 5 channel types ranked by GEO + SEO ROI: Wikipedia (entities), authoritative media (PR), industry reviews (G2/Capterra/Product Hunt), Reddit/Quora discussions, and HARO/Featured.com expert quotes. Designed for 0→1 sites where domain authority is the bottleneck. Aligns with 2026 Google/Bing GEO guidance: backlinks are the strongest brand-authority signal AI search engines use to decide citations. Defaults to dev/B2B link sources; for 2C products (education, consumer apps) authority links differ — see gingiris-seo-geo/references/2c-adaptation.md.

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Systematic debugging method: 5-step root-cause analysis (capture, isolate, hypothesize, investigate, fix & verify) plus common bug-pattern reference. Use when errors, exceptions, test failures, or unexpected behavior appear. Loaded automatically by the debugger agent.

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Methodological guide for the AI Agent to safely and systematically translate, refactor, and modernize giant legacy codebases (PHP, Python 2, old React) into modern stacks.

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Conducts a systematic related-work / literature-survey / state-of-the-art review for a research question by defining survey dimensions, searching each axis, building a taxonomy of prior work, identifying the gap, and producing a positioning narrative for a paper's Related Work section. Goes beyond a flat paper list to deliver structured analysis. Use when the user is starting a new research project and needs to map the landscape, asks "what's been done on X?" or "how does my idea compare to existing work?", needs to write or revise a Related Work / Background / Prior Art section, wants to identify a research gap or position their contribution, or asks to build a taxonomy of approaches in a research area.

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Systematic materials selection for engineering design using performance indices, Ashby charts, multi-constraint optimization, and case-based reasoning. Covers the five-step Ashby method — function, objective, constraint, free variable, index — with worked examples for stiffness-limited beams, strength-limited ties, thermally shocked vessels, and minimum-cost components. Use when choosing among metals, polymers, ceramics, and composites under competing objectives.

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Systematic departures from rational choice theory and their implications for economic analysis and policy. Covers cognitive heuristics (anchoring, availability, representativeness), biases (loss aversion, status quo, overconfidence), prospect theory (reference dependence, probability weighting, diminishing sensitivity), nudge theory and choice architecture, and the integration of psychological findings into economic models. Use when analyzing decision-making under uncertainty, evaluating policy interventions that exploit behavioral patterns, or assessing where standard rational-agent models break down.

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Systematic analysis of DC and AC linear circuits using Ohm's law, Kirchhoff's laws, node and mesh methods, Thevenin and Norton equivalents, phasor analysis, and Bode plots. Covers series and parallel reduction, superposition, source transformation, impedance in the frequency domain, first and second order transient response, and the conversion between time domain and phasor representations. Use when quantitatively predicting voltages, currents, power, gain, phase, or time response of any lumped-element linear circuit.

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Systematic evaluation of arguments for structure, validity, soundness, and charitable interpretation. Covers premise identification, conclusion extraction, argument mapping, steel-manning, and the distinction between validity (form) and soundness (form plus true premises). Use when assessing an argument, reconstructing an opponent's position fairly, or preparing a rebuttal.

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OpenStack backup operations skill for protecting cloud infrastructure through systematic backup strategies and disaster recovery procedures. Covers database backups (MariaDB full and incremental with mariabackup), configuration backups (globals.yml, inventory, Fernet keys), volume snapshots (Cinder LVM snapshots), image exports (Glance), instance snapshots (Nova), backup encryption (GPG/OpenSSL), retention policies (daily/weekly/monthly rotation), restore procedures (database point-in-time recovery, service rebuild), RPO/RTO planning, and disaster recovery drills. Use when planning backup strategy, scheduling automated backups, testing restore procedures, or executing disaster recovery.

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Systematic debugging approach for identifying and fixing issues

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Systematic code maturity assessment using Trail of Bits' 9-category framework. Analyzes codebase for arithmetic safety, auditing practices, access controls, complexity, decentralization, documentation, MEV risks, low-level code, and testing. Produces professional scorecard with evidence-based ratings and actionable recommendations. (project, gitignored)

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。