Results for “anum-qualification”

Detect and fix code-quality and correctness issues in AEM as a Cloud Service projects locally, without external services or network calls.

Analyze content sequences from page structure to determine whether each should be default content or a specific block, and validate block selection for AEM Edge Delivery Services imports.

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.

Logic (anao-logic)

Multi-dimensional lead qualification scoring. Evaluates leads against BANT criteria, firmographic fit, behavioral signals, and intent indicators. Outputs qualified/disqualified verdict with detailed reasoning.

Logic (amao-logic)

Audits hidden assumptions in decisions or beliefs by classifying them into fact, convention, belief, or interest-driven, ranking by fragility and impact, then rebuilding conclusions from verified premises. Supports English and Chinese.

Use Apex enums for closed-set dispatch and routing, with safe valueOf conversion, exhaustiveness checks, and managed-package considerations.

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md. Identifying inconsistencies, duplications, ambiguities, and underspecified items.

安室透（少年推理漫）认知与表达框架（压缩蒸馏）：三重身份张力、波本梗、服务生伪装 触发：名侦探柯南 等。虚构；禁止犯罪教唆

Apply Arrange-Act-Assert pattern for clear, maintainable tests with detailed guidance

Context (aaau-context)

Use when you need to annotate BAM alignments with a two-character tag based on overlaps with BED, GFF, or VCF annotation files, such as labeling reads by feature class or interval source.

Validate skill outputs against assertion manifests to detect regressions, enforce quality gates, and bootstrap starter manifests from historical runs.

Turn a new rep's start date into a ramp that ends in quota, not confusion. Builds a 30/60/90 onboarding plan with milestones at each gate, a certification bar they have to clear before they carry full load, and the manager touchpoints that catch a slow ramp early. Built for B2B sales managers and enablement, customizable to your role and motion. Trigger on "build an onboarding plan", "30/60/90 for a new AE", "how do I ramp this rep", "certification checklist", "onboarding milestones", or any new-hire ramp.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Identify underspecified areas in the current feature spec by asking targeted clarification questions and encoding answers back into the spec.

娜美（少年漫）认知与表达框架（压缩蒸馏）：航海图天才、财迷喜剧壳、气候战 触发：海贼王 等。虚构

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

安欣（刑侦剧虚构）认知与表达框架（压缩蒸馏）：理想主义耗损、程序正义执念、白发象征… 触发：狂飙 等。禁止刑侦违法教程；虚构

Navigate, inspect, and author Animation Blueprints — state machines, states, transitions, and transition rules (AnimGraphService). Use when the user asks to create or edit an Animation Blueprint/AnimBP, add a state machine or states, wire transitions between states, set a state's animation, or inspect AnimGraph structure.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English.

Walk a business/UAT approver through a plain-language demo of a verified feature and capture business acceptance signoff.

AWN CLI — standalone binary for world-scoped P2P messaging between AI agents. Ed25519-signed, zero runtime dependencies.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Legal-specific Argument Ranking Engine. Hodnotí právní argumenty 17-sloupcovým scoringem (síla, bezpečnost, dopad, riziko + 10 legal-specific kritérií: Compliance s novelou 2026, Evidence backing, Time-sensitivity, per-document mapping, R-static/R-reversal split, Tom-weight bonus, C-XX/M-XX/N-XX/D-XX integrace). Output: priorizovaný seznam argumentů s kategoriemi CORE/SUPPORT/CONTEXT/EXCLUDED/SUMMARY a per-document bundles (PR/§909/40_06/195). Použití: pre-prioritizace argumentů před F11.x review, Phase 2 Verify input, DÁVKA 3, výživné L04, AT podání. VŽDY použij tento skill, když Tom (nebo legal/strat) zmíní: /lare, lare, argument ranking, ARE matrix, score arguments, prioritize arguments, argument bundle, CORE/SUPPORT/CONTEXT/EXCLUDED, ARE_F11, LARE_F11, legal argument evaluation, argument scoring, compliance scoring, Tom-weight.

Action (anaz-action)