Results for “rippling”

Analyzing pre-change impact across vertical (dependency chains, files) and horizontal (pattern consistency, naming) dimensions. Use to estimate blast radius before a refactor. No code.

A relentless interview to sharpen a plan or design.

Use for writing, reviewing, debugging, or testing Python Streamlit apps, especially rerun behavior, widget identity and callbacks, session_state, cache_data/cache_resource, forms, fragments, containers, multipage navigation, uploads/downloads, and Streamlit-hosted chart/table interaction. Do not use for standalone Plotly/Altair figure design, generic backend services, Dash apps, or deployment configuration without app code.

Use when building falling leaves that read as leaves (not confetti): each leaf tumbling on its own axis with sideways slip driven by that tumble. Covers 2D canvas and instanced 3D, recycling, density maths, depth layering, tone-mapped colour, reduced motion, and visibility pausing—for maple, sakura, blossom, ash, or snowfall shapes.

Universal transformation λ(ο,K).τ with recursive self-improvement. USE WHEN routing reasoning, validating knowledge graphs, preparing CICM/ANZCA examinations, or when self-improvement of reasoning/architecture/context is required. Routes queries through R0-R3 complexity pipelines, validates topology (η≥target) and governance (KROG), emits per style (Φ), and compounds learnings into knowledge K. Triggers on complexity assessment, multi-step reasoning, examination mode, or /λ invocation.

Runs a relentless interview that sharpens a plan or design. Use when the user wants to be grilled on an idea, pressure-test a plan, or refine a design through questioning.

Create or analyze settings, scenes, world operations, and image direction in the literary cyberpunk mode of William Gibson's Sprawl fiction: dense, accreted urban systems; uneven high technology; corporate power; mediated culture; and human-scale survival inside global networks. Use for Gibson-informed creative work, setting design, or visual briefs, not for generic neon cyberpunk, faithful continuation of named canon, or imitation of Gibson's prose.

Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments. Triggers Greptile review, fixes all actionable comments, pushes/re-shelves, re-triggers review, and repeats. Use when the user wants to fully optimize a PR/MR/CL against Greptile's code review standards.

Scrape web pages using Scrapling with anti-bot bypass (like Cloudflare Turnstile), stealth headless browsing, spiders framework, adaptive scraping, and JavaScript rendering. Use when asked to scrape, crawl, or extract data from websites; web_fetch fails; the site has anti-bot protections; write Python code to scrape/crawl; or write spiders.

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

Multi-tiered memory management (HOT/WARM/COLD) for context compaction. Invoke ONLY for explicit compaction events: post-`/compact` cleanup, MEMORY.md tier promotion, archive batch, or "trim my context". NOT for general recall (use deep-recall) or routine memory writes (use storage-router). Triggers: "compact memory", "promote to durable", "archive old context", "tier this".

Composition Patterns

Runs a structured interview session to sharpen a plan or design through relentless questioning.

Alert design and on-call practices — severity, runbooks, SLO burn-rate alerting, escalation. Use when designing alerts, writing runbooks, reducing alert fatigue, setting up escalation policies, implementing SLO-based alerting, or improving on-call processes.

Mixup: Beyond Empirical Risk Minimization