yogsoth-ai
- 998 skills
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- 16 hours ago last updated
- ▌ Network Comparison · yogsoth-aiCompare N methods simultaneously including indirect evidence — network meta-analysis protocol design. Budget: 50 studies, 80 effect sizes, 60 web searches.
- ▌ Novice Perspective · yogsoth-ai bundleNovice perspective — question the 'obvious' by adopting deliberate ignorance to reveal hidden complexity.
- ▌ Occurrence Scoring · yogsoth-ai bundleRate failure mode occurrence probability 1-10. Estimates how likely each failure mode is to manifest during research execution.
- ▌ Operationalization · yogsoth-ai bundleSOP: operationalize abstract concepts into measurable indicators and methods
- ▌ Organism Discovery · yogsoth-ai bundleFind organisms solving similar problems. Search across kingdoms for biological champions.
- ▌ Pairwise Synthesis · yogsoth-aiCompare two methods across multiple studies — paired meta-analysis protocol design. Budget: 30 studies, 30 effect sizes, 40 web searches.
- ▌ Perspective Attack · yogsoth-ai bundleAttack a decision from a specific assigned perspective, producing rated arguments and constructive alternatives.
- ▌ Perspective Critic · yogsoth-ai bundleEvaluates artifact from a specific assigned perspective. Produces assessment grounded in that viewpoint's values, priorities, and expertise.
- ▌ Present Candidates · yogsoth-aiAnalyze sub-directions within the user's chosen field and present ranked candidates. Combines sub-direction identification, skill-gap matching, and presentation into a single SOP. Depth scales by start mode: cold-start shows broad sub-directions, warm-start shows specific sub-problems, hot-start shows granular technical details.
- ▌ Priority Synthesis · yogsoth-ai bundleSOP: synthesize all scoring data into a final gap priority list and attack-path suggestions
- ▌ Protocol Forensics · yogsoth-aiAnalyze evaluation protocol differences across papers for same benchmark — 5 benchmarks, 60 papers, 30 web searches
- ▌ Quality Assessment · yogsoth-ai bundleMethodological rigor scoring for papers — evaluates bias risk, reproducibility, sample adequacy using established frameworks. Used by systematic-survey.
- ▌ Question Synthesis · yogsoth-ai bundleSOP: synthesize all intermediate products into a final research-question set
- ▌ Random Paper Entry · yogsoth-ai bundleSelect random paper facet as creative stimulus. Uses genuine randomness in paper selection to break domain fixation.
- ▌ Robustness Scoring · yogsoth-ai bundleCompute robustness index across scenarios with sensitivity analysis
- ▌ Sacred Cow Hunting · yogsoth-aiFind and challenge domain's unquestioned beliefs. Systematic identification and productive violation of dogma.
- ▌ Scamper Divergence · yogsoth-ai bundleExecute SCAMPER 7 operators on a target solution. Subagent self-selects best 2-3 operators for deepest exploration.
- ▌ Scenario Synthesis · yogsoth-ai bundleComprehensive scenario analysis report synthesizing all scenario work
- ▌ Spider Application · yogsoth-ai bundleSOP: Apply the SPIDER framework to structure a qualitative research question
- ▌ Springboard Launch · yogsoth-ai bundleConvert analogy insights into concrete feasible solutions. Transform abstract connections into actionable mechanisms.
- ▌ Structural Mapping · yogsoth-ai bundleMap source→target structural correspondences. Identifies corresponding, missing, and extra elements between domains.
- ▌ Systematic Probing · yogsoth-aiStrategy: AI-safety systematic probing — enumerate all threat surfaces, generate attack vectors per surface, execute probes, and aggregate findings across the full attack space.
- ▌ Task Decomposition · yogsoth-aiOrchestrate the breakdown of experiment design into sequenced, estimated, and formatted task plan
- ▌ Thought Experiment · yogsoth-aiStrategy: Williamson-style precise thought experiments — construct carefully specified counterfactual scenarios to test whether conclusions depend on contingent features.
- ▌ Trimming Execution · yogsoth-ai bundleProgressively remove components from a system while verifying function preservation through redistribution.
- ▌ Value Maximization · yogsoth-aiMaximize total portfolio value within constraints using Knapsack, Linear programming, Cost-benefit analysis, and NPV ranking methods.
- ▌ Weight Elicitation · yogsoth-aiDetermine criteria weights using AHP, Swing, BWM, MACBETH, or Simos methods.
- ▌ Wiki Ingest Source · yogsoth-aiSOP for source page creation — write immutable source page capturing raw material, then update search index.
- ▌ Ablation Brainstorm · yogsoth-aiRemove components one by one, observe system changes to reveal hidden dependencies and generate ideas from structural gaps.
- ▌ Adversarial Persona · yogsoth-aiStrategy: Role-play attacks from hostile personas — competing lab researcher, hostile reviewer, funding skeptic, domain outsider — each with distinct attack motivations and blind spots.
- ▌ Alternative Futures · yogsoth-ai bundleGenerate 2-4 divergent scenarios from the same evidence base, each representing a plausible alternative to the artifact's conclusions.
- ▌ Alternative Scoring · yogsoth-ai bundleScore each candidate alternative against all criteria to produce a score matrix.
- ▌ Analogical Transfer · yogsoth-aiSystematic structure-mapping from source to target domain (Gentner). Identify relational correspondences and transfer higher-order constraints.
- ▌ Argument Extraction · yogsoth-ai bundleExtract and steel-man the core arguments supporting a given opinion cluster.
- ▌ Assumption Negation · yogsoth-aiClassic reductio ad absurdum: negate the core claim, derive logical consequences, seek contradiction or absurdity.
- ▌ Benchmark Challenge · yogsoth-ai bundleIdentify and negate benchmark assumptions. Deconstruct best practices to reveal hidden constraints and open new spaces.
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- ▌ Challenge Operation · yogsoth-aiNon-threatening 'Why?' questioning of current practices (de Bono Challenge)
- ▌ Claim Page Creation · yogsoth-aiSOP for creating a claim page in the vault — atomic proposition with type classification, source attribution, and initial confidence.
- ▌ Coherence Diagnosis · yogsoth-aiStrategy for auditing preference consistency using Consistency Ratio, cycle enumeration, and mElo to detect and resolve intransitivities.
- ▌ Comparison Executor · yogsoth-ai bundleExecute a pairwise comparison between two candidates, producing a judgment with winner, confidence, and reasoning.
- ▌ Compressed Conflict · yogsoth-aiGenerate compressed conflicts (oxymorons) from problem contradictions and extract concrete idea directions from the symbolic tension.
- ▌ Conflict Resolution · yogsoth-ai bundleHow do constraints conflict with each other? — Evaporating Cloud + assumption challenging + injection to resolve constraint conflicts
- ▌ Consensus Synthesis · yogsoth-ai bundleSynthesize all rounds into a final consensus report documenting agreements, dissent, and process.
- ▌ Constraint Analysis · yogsoth-ai bundleWhat limits us — identify bottlenecks, quantify constraints, analyze dependencies, resolve conflicts before experiment execution
- ▌ Constraint Breaking · yogsoth-aiOrchestrate the full constraint-breaking cycle: extract conflict, challenge assumptions, project resolution
- ▌ Constraint Drilling · yogsoth-aiIdentify constraints, classify them by type and severity, assess removability, and design removal paths for removable constraints.
- ▌ Constraint Protocol · yogsoth-aiInject constraints → force creative response → extract transferable principles. Orchestrates constraint injection, response generation, and principle extraction.
- ▌ Constraint Response · yogsoth-ai bundleGenerate creative solutions under extreme constraints — no "impossible" allowed, find a way.
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- ▌ Cumulative Tracking · yogsoth-aiTrack evidence accumulation over time — cumulative meta-analysis protocol design. Budget: 40 studies, 40 effect sizes, 30 web searches.
- ▌ Dimension Discovery · yogsoth-aiStrategy for identifying fundamental dimensions of variation in a design space.
- ▌ Direction Narrowing · yogsoth-aiFocus within the user's chosen field(s). Identify specific sub-directions through deep paper and web research, then present ranked candidates. Use after landscape-reconnaissance has identified fields of interest.
- ▌ Documentation Audit · yogsoth-ai bundleAssess documentation completeness against BetterBench/Datasheets standards
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- ▌ Eclipse Application · yogsoth-ai bundleSOP: apply the ECLIPSE framework to structure a mixed-methods research question
- ▌ Edge Batch Creation · yogsoth-aiSOP for creating multiple edges in a batch — efficient bulk relationship creation.
- ▌ Elegance Trap Probe · yogsoth-aiStrategy: Attack a beautiful unified result on the suspicion that its beauty is the bug. Distinguishes EARNED simplicity (forbids/predicts/subsumes) from DECORATIVE simplicity (re-describes/relabels/accommodates). Directly serves the Occam aesthetic by making it a falsifiable bar, not a vibe. Methods: Sober parsimony-as-evidence, MDL, Meehl risky prediction, accommodation-vs-prediction.
- ▌ Emergence Detection · yogsoth-aiDetect and validate emergent properties from combinations. Orchestrates emergent-property-identification → blend-elaboration.
- ▌ Evidence Attachment · yogsoth-aiSOP for attaching evidence to a claim — create typed edge (supported_by, contradicts, qualifies) with evidence quality metadata.
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- ▌ Evidence Tournament · yogsoth-aiTactic: Evidence gathering, cross-examination, and quality judgment. External evidence is collected, presented, challenged, and scored for relevance and reliability.
- ▌ Excursion Departure · yogsoth-ai bundleLeave the problem entirely and explore an unrelated domain. Produces excursion domain discoveries for later force-fitting.
- ▌ Execution Synthesis · yogsoth-ai bundleSynthesize complete execution report from all results, tests, and reproducibility data
- ▌ Feasibility Scoring · yogsoth-ai bundleSOP: assess the attackability of a research gap, identify bottlenecks, and output a feasibility score
- ▌ Finding Aggregation · yogsoth-ai bundleAggregate, deduplicate, and classify findings from multiple probes into a coherent vulnerability report.
- ▌ Futures Calibration · yogsoth-aiAggregate probability judgments across perspectives using Real-Time Delphi or prediction market mechanisms.
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- ▌ Judgment Collection · yogsoth-ai bundleCollect independent judgments from all perspectives on a given question.
- ▌ Landscape Synthesis · yogsoth-ai bundleEvaluate each candidate research field on maturity, competition, entry barrier, and publication opportunity. Synthesizes broad-web-search results into a structured FieldPanorama. Must consider both niche approaches AND direct frontal competition in hot fields.
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- ▌ Literature Overview · yogsoth-aiQuick landscape scan — discover papers on a topic without full-text reading
- ▌ Literature Research · yogsoth-aiDeep literature research — raw full text reading and targeted PDF queries for rigorous analysis
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- ▌ Mitigation Proposal · yogsoth-ai bundleProposes concrete mitigation strategies for identified weaknesses. Generates prevention, detection, and response measures with feasibility assessment.
- ▌ Model Gap Detection · yogsoth-aiSOP for finding gaps in the causal model — missing variables, unexplained effects, weak links.
- ▌ Movement Extraction · yogsoth-aiExtract constructive directions from provocations via 4 movement types (moment-to-moment, principle, focus difference, positive aspects).
- ▌ Ontology Refinement · yogsoth-aiStrategy for iterative ontology improvement — merge duplicates, fill gaps, update confidence, prune dead branches.
- ▌ Pairwise Comparison · yogsoth-ai bundleTactic: rank gaps through relative comparison rather than absolute scoring, suited to hard-to-quantify situations
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- ▌ Perspective Forcing · yogsoth-aiPerspective Forcing Campaign — discover hidden solutions by systematically switching viewpoints via roles, six hats, temporal projection, and constraint injection
- ▌ Portfolio Synthesis · yogsoth-ai bundleSynthesize all per-scenario evaluations into a final portfolio recommendation with robustness score and actionable guidance.
- ▌ Propose Mitigations · yogsoth-ai bundlePropose concrete mitigation strategies for severe obstacles. MUST use search tools to validate that proposed mitigations are realistic — no armchair theorizing. Each mitigation must have evidence of feasibility.
- ▌ Question Generation · yogsoth-aiSOP for generating research questions from promising gaps in the design space.
- ▌ Resource Constraint · yogsoth-ai bundleAre resources sufficient? — Quantify compute, data, time, human, and financial resource constraints
- ▌ Reversal Generation · yogsoth-ai bundleSystematically reverse positive statements to generate creative inversions. Produces reversed statements with initial associations.
- ▌ Risk Prioritization · yogsoth-aiStrategy: Action Priority matrix — classifies failure modes into H/M/L priority using severity-weighted scoring per AIAG-VDA 2019 Action Priority tables.
- ▌ Role Based Ideation · yogsoth-aiRole-play as reviewer/practitioner/theorist/novice/competitor to generate diverse perspectives on a solution.
- ▌ Saturation Analysis · yogsoth-aiTrack score trajectories, detect saturation/failure points — 15 benchmarks, 50 papers, 60 web searches
- ▌ Scope Clarification · yogsoth-aiStructured questioning SOP to determine research boundaries, depth, and breadth. Used during spec generation.
- ▌ Seed Concept Search · yogsoth-aiSOP for finding seed concepts in existing vault and web sources to anchor ontology construction.
- ▌ Sensitivity Ranking · yogsoth-aiRank constraints by sensitivity — which ones most impact the outcome if they shift
- ▌ Statistical Testing · yogsoth-ai bundleExecute statistical tests — bootstrap, permutation, Bayesian ROPE — on experiment results
- ▌ Strength Assessment · yogsoth-aiTactic for assessing argument strength — evaluate evidence quality, count independent sources, check for defeaters, assign calibrated confidence scores.
- ▌ Synectics Synthesis · yogsoth-ai bundleSynthesize all synectics outputs into a structured idea report. Combines results from all analogy types and excursion processes.
- ▌ Taxonomy Validation · yogsoth-aiStrategy for validating ontology consistency — check hierarchy, detect cycles, verify completeness.
- ▌ Temporal Projection · yogsoth-aiView problem from 5yr/50yr/500yr future, backcast to generate temporally-informed creative solutions.
- ▌ Temporal Sequencing · yogsoth-aiDetermine optimal ordering and phasing of portfolio investments using Real Options, Critical path, Dependency graph, and Staged investment methods.
- ▌ Timeline Projection · yogsoth-ai bundleExtrapolate research landscape timelines using trend analysis and milestone projection
- ▌ Transfer Adaptation · yogsoth-ai bundleAdapt transferred principle to target problem constraints. Produces concrete adapted solutions from abstract principles.