Results for “pre-pr”

Generates pixel art SVG illustrations for READMEs, docs, or slides, with character templates, chat bubbles, and scene composition guidance.

Sarbanes-Oxley Act compliance reference — SOX sections, internal controls, audit requirements, and IT governance. Use when evaluating SOX compliance, designing internal controls, or preparing for financial audits.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.

A playful, arcade-inspired interface for games — built on the VT323 pixel typeface, hard-edged 0px corners, chunky pill buttons that physically press into solid offset blocks

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

This skill should be used when building prediction market integrations, implementing betting functionality, or querying Polymarket odds. Covers market search, odds checking, and position management.

Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data preprocessing.

Create coins on pump.fun — standard create with initial buy. Prefer runnable Node scripts in this skill folder; use @pump-fun/pump-sdk for custom integrations.

Handle errors as values using fp-ts Either and TaskEither for cleaner, more predictable TypeScript code. Use when implementing error handling patterns with fp-ts.

Prepare PRINCE2 Managing a Stage Boundary material: end stage report, next stage plan, updated business case, updated project plan, lessons, risks, issues, and exception plan if needed.

Structure spoken product-sense interview answers with assumptions, segmentation, pain-point prioritization, and MVP tradeoffs.

Use this skill when the user asks specifically about preparing for the New Entrant Safety Audit (NESA) under 49 CFR 385 Subpart D — different from a Compliance Review. Covers what auditors look at, the 18-month window, automatic failure conditions, the 60-day fix window, what to NOT do, and how to convert from "new entrant" to permanent authority. Cite 49 CFR 385.301-321.

Audit, write, or revise .vale.ini, or work through vale findings on a repo. Use when adding Vale, troubleshooting silent passes or noisy findings, evolving config, or applying the suggestion → warning → error cleanup cascade after a vale run (interactive or pre-commit failure). Applies the two-hook pre-commit pattern (sync + lint), explicit Packages and per-format BasedOnStyles, scoping/ignores for false positives, and a shared accept.txt vocabulary.

Build cinematic, scroll-driven 2.5D websites with parallax depth, text animations, and premium effects using CSS and JavaScript.

Detect and prevent public-over-private name resolution in npm, PyPI, and Maven dependency manifests.

Explains machine learning model predictions using SHAP values, covering feature importance, visualizations, debugging, bias analysis, and production deployment.

Genera reportes profesionales en HTML, PDF y Markdown, con tablas, gráficos y conclusiones, para presentar análisis de forma clara y reproducible.

Delivers measurement-driven performance optimization for latency, throughput, memory, and tail behavior, with correctness preservation and regression guards.

Guides a blameless post-mortem process for incidents, covering templates, root-cause analysis, action items, and prevention.

Persistent cross-session memory management. Enables agents to remember user preferences, project conventions, and past decisions across different sessions using a structured MEMORY.md index and topic files.

Use when planning an AAAI project timeline from topic selection through abstract, OpenReview submission, two-phase review, rebuttal, decision, camera-ready, registration, presentation, and public artifact release.

Read-only query methods for PumpFun claims — unclaimed token rewards, creator vault balances, volume accumulators, distributable fees, and current-day token previews across Pump and PumpAMM programs.

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.

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.

Design a lesson opening that activates prior knowledge and connects previous learning to today's content. Use when planning lesson starters, retrieval openers, or advance organisers.

Modify a classroom task with language scaffolds that preserve cognitive demand for EAL learners. Use when adapting existing tasks for students at different English proficiency levels.

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.

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.

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.

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.