197 skills · sorted by relevance
Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.
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Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.
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Manages GDPR Article 22 rights related to solely automated decision-making and profiling, including identification of automated decisions, meaningful human oversight implementation, logic explanation requirements, and contestation mechanisms. Activate for automated decision, profiling, Art. 22, algorithmic decision, AI decision queries.
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Guides the combined DPIA and AI Act conformity assessment for AI systems processing personal data. Covers EDPB-EDPS Joint Opinion 5/2021, training data lawfulness under Art. 6 and Art. 9, Art. 22 automated decision-making, algorithmic bias detection, and NIST AI RMF MAP function. Keywords: AI privacy, DPIA, AI Act, algorithmic bias, automated decision-making, Art. 22, training data, NIST AI RMF.
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Architecture Decision Framework workflow skill. Use this skill when the user needs Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Architecture Decision Framework workflow skill. Use this skill when the user needs Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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API Patterns workflow skill. Use this skill when the user needs API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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API Patterns workflow skill. Use this skill when the user needs API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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API Patterns workflow skill. Use this skill when the user needs API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Design effective reasoning processes for AI agents and optimize decision-making strategies. Use when designing agent prompts, improving decision quality, implementing specialized reasoning modes, creating reasoning traces, or debugging agent mistakes. Covers prompting, chain-of-thought, reasoning depth, and decision evaluation.
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Decision-making patterns in incident command and emergency management leadership contexts
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Naturalistic decision-making research showing how experts make decisions through recognition-primed processes
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Integration of Kahneman's heuristics research with Klein's expertise studies on intuitive decision-making
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Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.
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Identify and counteract cognitive biases in medical decision-making through systematic error analysis and contextual algorithm application. For diagnostic reasoning, treatment decisions, and clinical judgment improvement. NOT for basic medical knowledge, technical procedures, or non-clinical healthcare domains.
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This skill provides a shared decision-making framework for selecting second-line therapies in patients with ACTH-dependent Cushing's syndrome who have persistent hypercortisolism after transsphenoidal surgery or for whom surgery is not feasible. Clinical triggers include "failed TSS", "non-curative pituitary surgery", "persistent UFC elevation post-op", and "surgery contraindicated".
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Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.
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Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.
The English summary is being prepared. Showing the original description.
Identify and counteract cognitive biases in medical decision-making through systematic error analysis and contextual algorithm application. For diagnostic reasoning, treatment decisions, and clinical judgment improvement. NOT for basic medical knowledge, technical procedures, or non-clinical healthcare domains.
The English summary is being prepared. Showing the original description.
Turn product requirements, roadmaps, architecture reviews, and retrospectives into HTML slides for decision-making. Choose one of eight visual themes to create a consistent, horizontally navigable deck, using source evidence and real numbers to support review.
Create AgentDB learning plugins that use recorded experience to improve agent decisions. Choose a learning method, store states, actions, and rewards, train models, and evaluate suggested actions through CLI and API workflows.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.
Define reusable reasoning and decision patterns for agents, embed them in executable workflows, and review their performance. Share successful approaches, including conditional decision trees, stepwise problem solving, analogies, and evaluation from multiple perspectives.
Build agent memory with ReasoningBank and AgentDB. Record actions and outcomes, retrieve similar experiences, assess results, and consolidate memories into reusable patterns so agents can draw on past work when making decisions.