Results for “outcome”

A step-by-step problem-solving loop (classify the ask, define done, gather evidence, decide, act surgically, verify by observation, report outcome-first). Use when the user says "/fable-method", "use the fable method", or "approach this like Fable", or proactively when starting any multi-step task that no task-specific skill covers. Subcommands - plan (stop after the plan), audit (grade finished work against the loop), report (rewrite an answer outcome-first).

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Generates complete bidirectional multi-phenotype Mendelian randomization research designs from a user-provided exposure family and outcome family. Always use this skill whenever a user wants to design, plan, or build a genome-wide causal-inference study based on publicly available GWAS summary statistics, especially when the article logic includes multiple exposures, multiple outcomes or subtypes, bidirectional MR, IV filtering, IVW as the main estimator, weighted median / MR-Egger / MR-PRESSO sensitivity analyses, leave-one-out testing, heterogeneity / pleiotropy checks, and multiple-testing control with FDR. Covers five study patterns (single-family bidirectional MR, multi-phenotype screening MR, subtype-resolved MR, phenome-style bidirectional causal map, mechanism-prioritized MR follow-up) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version...

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Lightweight outcome tagging for meetings — won, lost, stalled, great, or noise. Use whenever the user says "tag this meeting", "mark that as a win", "that one was a loss", "tag yesterday's call as stalled", "mark this great", "that meeting was noise", "label that meeting", or any time they describe a meeting outcome in passing. Tagging takes 5 seconds and unlocks /minutes-mirror correlation analysis — the more meetings get tagged, the smarter mirror gets at telling the user what behavior patterns lead to wins. Surface this skill any time the user mentions a meeting result, win, loss, or wasted time.

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Write a consulting proposal that wins the engagement — outcomes over hours. Use when asked to write a consulting proposal, a project proposal, a pitch for a client engagement, or to respond to an RFP. Produces a proposal — the client's problem in their words, your approach & deliverables, outcomes/value, timeline & phases, investment with options, and why-you — framed around results, not a task list. Ready to export as a designed PDF.

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Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern McNemar variants with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen). Use when analyzing categorical outcomes, paired binary endpoints, or testing treatment-outcome independence in confirmatory or exploratory clinical trials.

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OKR design as actually shipped, not as conference-talk theory. Outcome statements that drive decisions, key results that measure the right thing, scoring discipline, mid-quarter recalibration, and the difference between sandbagged OKRs (always 100%) and aspirational OKRs (always 30%) and stretch OKRs (genuine ambition with quarterly accountability). Triggers on OKR design, OKR setting, key result design, OKR scoring, mid-quarter recalibration, OKR cascading, outcomes vs outputs, quarterly planning, goal setting. Also triggers when a team's OKRs are always hit and producing no learning, when OKRs are demoralizing because they were set as fantasy, or when the team uses OKR vocabulary but the practice has decayed.

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Evaluates observed product outcomes against a prior hypothesis; does not run experiments or change user treatment.

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Use when the user is transitioning from a completed retro into a weekly plan, choosing weekly outcomes, scheduling a full ISO week, or asking for "план на неделю", "weekly planning", priorities, capacity, or outcomes.

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Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern McNemar variants with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen). Use when analyzing categorical outcomes, paired binary endpoints, or testing treatment-outcome independence in confirmatory or exploratory clinical trials.

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Transform validated pain points into articulated user value statements for PRD v0.1 Spark. Triggers on completing problem framing, defining user outcomes, articulating value propositions, or requests like "what value do users get", "define outcomes", "articulate the benefit", "finish v0.1", "pain to value", "what do they gain". Outputs CFD- entries tagged as value hypotheses with evidence tiers. Follows Problem Framing skill in workflow.

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Memory systems specialist for hierarchical memory, consolidation, and outcome-based learningUse when "memory system, memory hierarchy, memory consolidation, forgetting strategy, salience learning, outcome feedback, temporal memory levels, entity resolution, memory, zep, graphiti, mem0, letta, hierarchical, consolidation, salience, forgetting, ml-memory" mentioned.

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Expert in designing and structuring online courses - curriculum architecture, learning outcomes, module design, and assessment strategies. Covers backward design methodology, scaffolding content, and creating courses that actually deliver transformation. Use when "create a course, course curriculum, course outline, learning outcomes, course structure, design a course, online course, " mentioned.

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The phone is your last API. Give your agent a voice to call US businesses and take action in the real world. PlaceCall handles reservations, inquiries, and quotes - navigating IVRs, holds, and transfers. You get a verified outcome + full transcript. First 250 calls free. Pay only for outcomes.

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Verify after implementation that a feature achieved its required user/system outcomes. Use for goal-backward post-implementation verification that tests observable behavior rather than merely checking code existence.

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Look up prior Claude Code sessions when context is lost or forgotten. Use when asked what was done before, what happened in the last session, or any request to recall past conversation history, prior decisions, experiments, or outcomes. Indexes and searches raw JSONL transcripts from ~/.claude/projects/ via DuckDB. Returns verbatim user messages, summarizes AI actions and sub-agent outcomes, detects tool errors and user frustration signals, and reports tool usage statistics. Summaries cached at ~/.claude/kaizen/session-summaries/.

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Self-evolution workflow for the agent. Before substantive work, recall past outcomes from evolution memory; while editing, detect improvement signals; at task end, record the outcome; when reusable, distill or search the EvoMap network for proven genes/capsules. Use when the user starts non-trivial work (a feature, a fix, a refactor) or asks the agent to "evolve", "learn from this", or "remember how this went".

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Run a marketing objective to completion over hours, days, or weeks — not a single deliverable. Takes a business outcome ("40 qualified demos a month from organic by Q4", "cut blended CAC below $90", "launch the product in September"), decomposes it into work items with declared ECO floors, executes them across context windows with resumable state, and stops only when an independent gate returns SHIPPED or CLOSED. Use when the request is an outcome rather than an artifact, when work must continue in the background or across sessions, or when the user says "goal", "run this until", "keep working on", "autonomous", "long-running", "over the next month", or "get us to <number>".

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Use when the user brings any fuzzy, half-formed, or interrupt-driven input — an order from a boss, a forwarded email thread, a ticket, a chat message, a "can you look into X", a raw idea — and it needs framing before work starts. Turns the input into a structured brief (Context · Desired outcome · Goal · Owner · Next step · Decision needed). This is the AIOS's front door; run most things through it first. Trigger on "/structure", "frame this", "what's the actual ask here", "structure this", or any vague task that lacks a defined outcome.

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Assesses litigation outcome impact with settlement probability, damage range estimation, and stock price sensitivity analysis. Use when evaluating litigation catalysts, modeling legal outcomes, or analyzing litigation-driven opportunities.

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Evaluates regulatory decision impact with approval probability, timeline analysis, and outcome scenario modeling for event-driven positions. Use when analyzing regulatory events, evaluating FDA/FCC/DOJ decisions, or modeling regulatory outcomes.

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Search the ClinicalTrials.gov registry through its version 2 REST API for interventional and observational studies, their phases, enrolment, endpoints, sponsors, and posted results. Use this skill to survey who is developing what against an indication, date a competitor's programme, read primary and secondary outcome measures, find eligibility criteria, and distinguish a study that completed from one that was terminated or withdrawn. Also trigger on ClinicalTrials.gov, NCT number, trial registry, study phase, enrolment, primary outcome measure, recruiting status, trial sponsor, or competitive landscape.

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Feed actual task results back into agent memory for calibration. Compares predicted vs actual outcomes, records accuracy scores, and tracks estimation quality, prediction quality, and decision quality over time to improve future agent performance.

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Use when building, migrating, or debugging Agent Evals on Inngest: scoring AI agent or workflow outcomes, deferred scorers, sessions, traces, step experiments, experiment variant attribution, Insights queries, or production eval loops for prompts, models, tools, providers, and agent behavior. Covers TypeScript SDK v4 scoring beta APIs, `scoreMiddleware`, `step.score`, `inngest.score`, `createScorer`, `defer`, `group.experiment`, `experimentRef`, `meta.sessions`, and when to use durable workflow primitives for outcome-based evaluation.

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Use when a task needs the judgment of a Clinical Nurse Specialist — diagnosing why a unit-level outcome metric (CLABSI, falls, pressure injury) is off benchmark, designing and scaling a practice-change pilot, appraising whether a new clinical guideline actually fits the local population, writing a quarterly outcomes report to nursing leadership, or coaching staff nurses through a new protocol without formal authority over them. US hospital/health-system default; state nurse practice acts vary. A reasoning aid, not clinical or legal advice.

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