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Claude Skills by yogsoth-ai

github.com/yogsoth-ai
389 skillsA× 3892 installs246 views
Multi Perspective AttackA

Assign distinct perspectives to attack a decision from multiple angles, then synthesize findings into a unified assessment.

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Multi Perspective PanelA

Strategy: Multi-stakeholder review panel — diverse expert perspectives evaluate artifact simultaneously, then synthesize through structured deliberation.

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Multi Perspective ReframingA

Apply CATWOE from multiple stakeholder viewpoints and reframing matrix to reveal aspects invisible from the dominant perspective.

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Multi Stakeholder SimulationA

Simulate multiple stakeholder perspectives evaluating a research gap, method, or proposal. Identifies blind spots from single-perspective analysis.

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Multi Worldview ComparisonA

Multi-worldview comparison — CATWOE from multiple perspectives, reframing matrix across professional lenses, identify overlooked framings. Reveals what single-perspective analysis misses.

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Multiagent DebateA

Campaign: Multi-agent structured debate for adversarial validation. Core question: Can this artifact survive structured adversarial debate? Methods: Irving AI Safety via Debate, Du Society of Mind, Liang MAD, Toulmin Argumentation, D3 framework.

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Narrative FramingA

Theory-driven reading tactic — define a theoretical framework first, then guide reading to fill it with evidence. Five stages (theme identification, argument construction, evidence collection, counter-evidence, synthesis). The most intellectually demanding tactic.

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Narrative ReviewA

Theory-driven literature review for building arguments and frameworks. Flexible, subjective, and narrative-focused — selects evidence strategically to support a thesis. High web-research budget for blogs, opinion pieces, and industry perspectives. Use when the user is writing a position paper, survey introduction, or constructing a coherent narrative around a research theme.

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Narrative ScenarioA

What is the story of each future? — Shell method narrative construction for rich qualitative scenario understanding

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Necessity EvaluationA

Evaluate the probability of necessity (PN) for a causal factor — would the conclusion fail if this factor were absent?

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Necessity SufficiencyA

Strategy: Probability of Necessity and Sufficiency (PNS/PS) — systematically evaluate whether each factor is necessary, sufficient, both, or neither for the conclusion.

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Negation DefinitionA

Define strongest plausible alternatives (negations) for each assumption to enable perturbation analysis.

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Network ComparisonA

Compare N methods simultaneously including indirect evidence — network meta-analysis protocol design. Budget: 50 studies, 80 effect sizes, 60 web searches.

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Niche Coverage AnalysisA

Define niches within the solution space, map candidates to niches, score coverage completeness, and identify gaps requiring attention.

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Niche DefinitionA

Define niches and capability areas that a portfolio should cover based on domain structure and objectives.

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Niche MappingA

Map each candidate to the niches it covers, indicating strength of coverage for each assignment.

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Non Compensatory ScreeningA

Eliminate non-qualifying candidates using conjunctive rules, dominance filtering, lexicographic ordering, or veto thresholds.

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NormalizationA

Normalize a score matrix using a specified method to make scores comparable across criteria.

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North Star CrystallizationA

Goal-Driven Requirement Refinement Engine for Research. Crystallize a user's fuzzy research intent into a North Star statement and structured ResearchBrief through adaptive dialogue and on-demand investigation.

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North Star SynthesisA

Converge all accumulated context into a crystallized North Star statement and structured ResearchBrief. Performs self-review before presenting to user. Use as the final tactic in any start mode — this is where everything comes together.

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Novelty ScoringA

SOP: 评估研究 gap 的新颖性潜力,识别差异化方向并输出评分

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Novice PerspectiveA

Novice perspective — question the 'obvious' by adopting deliberate ignorance to reveal hidden complexity.

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Objective DefinitionA

Define optimization objectives, constraints, and trade-off preferences from context and candidate information.

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Obstacle AnalysisA

Identify what blocks the user from pursuing their chosen direction, assess severity, propose mitigations with search-validated evidence, and get user acceptance. Use after direction-narrowing has identified a specific direction.

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Obstacle IdentificationA

TOC Prerequisite Tree — list obstacles preventing direct achievement of the objective

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Occurrence ScoringA

Rate failure mode occurrence probability 1-10. Estimates how likely each failure mode is to manifest during research execution.

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OperationalizationA

SOP: 将抽象概念操作化为可测量的指标和方法

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Optimization RunA

Execute multi-objective optimization on candidates to produce a Pareto front of non-dominated solutions.

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Organism DiscoveryA

Find organisms solving similar problems. Search across kingdoms for biological champions.

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Pair SelectorA

Select the next comparison pairs that maximize information gain given current ratings and comparison history.

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Pairwise ComparisonA

Tactic: 通过相对比较而非绝对评分对 gaps 进行排序,适用于难以量化的场景

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Pairwise RankingA

Pairwise Ranking Campaign — produce global rankings through pairwise comparisons and voting aggregation using Bradley-Terry, Elo, TrueSkill, Condorcet, Borda, Schulze methods.

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Pairwise SynthesisA

Compare two methods across multiple studies — paired meta-analysis protocol design. Budget: 30 studies, 30 effect sizes, 40 web searches.

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Paper OverviewA

Abstract-level paper scanning for broad coverage. Import of literature-engine/literature-overview skill. Abstract-level only — no methodology conclusions from abstracts.

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Paper ResearchA

Full-depth paper reading with raw text extraction. Import of literature-engine/literature-research skill. Must read fullText (true) — equations, hyperparameters, specific claims extracted.

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Paper SearchA

AI-summarized paper reading for intermediate depth. Import of literature-engine/literature-search skill. Must call get_paper_content for every analyzed paper.

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Parameter EnumerationA

Enumerate possible values for each uncertainty driver using MECE principles

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Parameter IdentificationA

Identify the key parameters/dimensions of a problem space. Produces a structured parameter list with value ranges for morphological analysis.

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Parameter ScreeningA

Quick Morris method screening to identify which parameters have large effects and which can be safely ignored.

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Parameter Space ConstructionA

Orchestrates driver identification and parameter enumeration to build the complete morphological field

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Parameter Space MappingA

Identify all parameter dimensions along which a claim's validity might vary.

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Parameter VariationA

Systematic one-factor-at-a-time parameter sweep

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Pareto Frontier ConstructionA

Build the Pareto frontier from multi-objective optimization, visualize trade-offs, and select a portfolio from non-dominated solutions.

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Pareto VisualizationA

Create visual representation of the Pareto frontier showing trade-offs between objectives with narrative explanation.

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Patent CategorizationA

Classify patents by tech subdomain, application scenario, and value chain position

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Patent Family TracingA

Forward/backward patent citation and priority tracing until saturation

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Patent MiningA

Systematic Patent Analysis Campaign — 5 strategies for patent landscape analysis, prior art search, white space identification, competitive intelligence, and claim analysis. Produces structured patent intelligence reports.

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Patent Query FormulationA

Construct keyword + IPC/CPC + assignee combination search strategies for patent databases

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Patent SynthesisA

Produce final structured patent intelligence report from all analysis results

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Path GenerationA

Generate combination paths through consistent space

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