Results for “rounding”

Runs a relentless interview that asks every frontier question at once, round by round. Use when the user wants to be grilled on a design or map a design tree.

Configures personalized status briefings by learning your communication style, audiences, and data sources through an interactive conversation.

Generate personalized status briefings by pulling from configured data sources like GitHub, email, Teams, and Slack, then synthesizing updates in your own communication style.

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.

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.

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.

Track weekly funding rounds across configurable verticals with primary-source verification, per-round analysis, and risk assessment.

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.

Iteratively improves a compiled LaTeX paper through two rounds of external LLM review, fix implementation, and recompilation.

Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop...

Generate personalized status briefings on demand. Pulls from your configured data sources (GitHub, email, Teams, Slack, and more), synthesizes across them, and drafts updates in your own communication style for any audience you define.

Run a structured, multi-source deep-research loop on a question until the answer stops changing.

Designs and reviews feedback loops for AI agents to ensure goals are machine-decidable, loops are damped, and human judgment is preserved.

Designs new software features and multi-component changes for the current repo into implementation-ready BDD specs via autonomous codebase research, then commits the design for review (runs to completion without mid-design questions). Scope covers new features, greenfield design, and multi-component changes. Not for hardware/physical-system design, out-of-repo questions, single-file refactors, or known-root-cause bugs (those go to direct edits or systematic-debugging).

PRISMA Scoping Review Pipeline

Short clarifying interview before starting non-trivial engineering work — surfaces the actual requirement, what's explicitly out of scope, and what proves it's done. Use before writing code when the task's requirement, scope, or definition of done isn't already unambiguous. Not for trivial or fully-specified changes — that's ceremony, not clarity.

Grilling

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

通用多轮迭代改进：对任意研究制品反复调用 /review → 解析反馈 → 修复 → 更新 wiki，直到达标

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

Generates award-level UI with GSAP motion, bento grids, and Python-driven randomization for layout variety.

Create and optimize popups, modals, overlays, slide-ins, and banners to increase conversions without harming user experience or brand trust.

Group interface elements using containers, backgrounds, and boundaries based on the Gestalt Law of Common Region.

Design and optimize popups, modals, and overlays to capture leads and increase conversions without damaging user experience.

Designs and governs recursive self-improvement loops where an agent mines its own failures and proposes edits to its own harness, prompts, or workflow, covering acceptance gates, diversity preservation, and the optimization ladder.

When the user wants to optimize any form that is NOT signup/registration — including lead capture forms, contact forms, demo request forms, application forms, survey forms, or checkout forms. Also use when the user mentions "form optimization," "lead form conversions," "form friction," "form fields," "form completion rate," or "contact form." For signup/registration forms, see signup-flow-cro. For popups containing forms, see popup-cro.

Design and improve revenue operations, lead lifecycle rules, scoring, routing, handoffs, and CRM process automation. Use when marketing, sales, and customer success workflows need clearer operational structure.

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Applies dialogue MA, portrait reframing, and loudness/sync QA to an interview or talking-head rough cut using canonical timeline metadata and a shared renderer.

Discover, audit, repair, adapt, and design bounded, verifiable AI-agent loops with explicit triggers, actions, stopping conditions, and guardrails.

Discover, find, compare, audit, repair, adapt, craft, run, debrief, and prepare repeatable AI-agent loops for publication. Use when a user asks to analyze code or coding threads for recurring work, find a published loop, interview them to turn a goal into a bounded loop, review a loop...

Design a lead routing and SLA model someone can actually implement. The assignment rules, the round-robin or account-based logic, the SLA timers, and the fallbacks when a rep is out or a lead has no owner. Built for B2B RevOps teams, customizable to your CRM and your team shape. Trigger on "design lead routing", "who should get this lead", "build our SLA", "round robin rules", "leads are falling through", or any routing diagnostic.

Design and optimize revenue operations, including lead lifecycle rules, scoring, routing, handoffs, and CRM process automation for marketing, sales, and customer success alignment.

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".

Discovers, finds, audits, repairs, adapts, crafts, runs, debriefs, saves, and prepares repeatable AI-agent loops for publication, treating loops as bounded feedback systems.