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Manipulate row selection (`df.selection`) on a Datagrok DataFrame via the datagrok_exec tool — set, clear, invert, add to, remove from, intersect, and read the selection mask. Also covers current row (`df.currentRowIdx`), the cross-skill bridges to/from the filter, and how to materialize the selected rows as a new DataFrame. Use whenever the user says "select rows", "deselect", "invert selection", "highlight rows", "selected rows", "clear selection", "current row", "currentRowIdx", "count selected", "list selected indexes", "selection from filter", "filter from selection", or asks for selected rows as a new table. Does NOT cover row filtering (separate skill `datagrok-filtering`) or generic DataFrame cloning (`datagrok-df-and-columns`).

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The logical structure of mathematical proof -- how first-order logic, natural deduction, and semantic reasoning combine to produce rigorous mathematical arguments. Covers the logical skeleton of direct proof, contraposition, contradiction, cases, and induction; the role of definitions, lemmas, and theorems; how informal mathematical prose maps to formal deductive structure; and the difference between proof-as-object and proof-as-activity. Use when the question is "why is this a valid proof?" rather than "what proof technique applies?"

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Practical argument analysis and construction -- how to identify, evaluate, reconstruct, and build real arguments in natural language. Covers argument identification (premises, conclusions, intermediate steps), charity and steel-manning, argument mapping, the distinction between deductive validity and inductive strength, burden of proof, and the rhetorical context in which arguments operate. Use when the goal is to engage with real-world argument rather than to formalize it.

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Analyzing patterns of continuity and change over time in historical contexts. Covers periodization (how and why we divide history into eras), identifying turning points, measuring rates of change, and recognizing long-term patterns and trends. Use when analyzing temporal structure in history, debating period boundaries, or assessing whether a moment represents genuine transformation or surface-level disruption.

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Networking fundamentals as they apply to cloud infrastructure — virtual networks, subnets, routers, NAT, floating IPs, security groups, VLAN/VXLAN segmentation, load balancing, SDN concepts, and how Neutron-style cloud networks sit on top of physical topology. Covers TCP behavior at scale, congestion control, tail latency, overlay networks, and the operational gotchas that come from network layering. Use when designing cloud network topology, debugging cross-AZ latency, or reviewing a proposed VPC/SG design.

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Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.

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Runs several language models as independent coders on one labeling or discovery task and treats disagreement as data. Covers diverse panel assembly, independent voting, consensus rules, Cohen’s and Fleiss kappa, Krippendorff’s alpha, correlated-error limits on validity claims, human validation, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, how to combine model labels, or what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.

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Scan Claude Code session transcripts to find the strongest user reactions to assistant instruction-following failures, reconstruct the triggering assistant output, and render a shareable terminal-style PNG artifact. Use when you want to surface and share a moment where the assistant completely missed what was asked — captures what they were doing, what Claude said, and how the user reacted. Triggers on: "rtfp", "read the fucking prompt", "find my worst AI moment", "make a rage screenshot from this session".

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Quantitative cost measurement for technical research — token injection costs, payload sizes, context window consumption, and file-level counts from actual repo files. Use when a technical-researcher orchestrator needs the cost dimension of adding or changing something: how many tokens will it inject, how big are the artifacts, what is the context window impact? This is NOT blast-radius analysis (which files break) — it covers size, tokens, and performance cost only.

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Comprehensive UI design guidance based on Refactoring UI principles covering design personality, color theory, layout strategy, visual hierarchy, typography, spacing, mobile-first responsive design, and writing copy that doesn't read like AI wrote it. Use this skill whenever the user is creating new pages, building components, making design additions or changes, reviewing UI code, asking about design decisions (colors, fonts, spacing, layout), writing or editing interface copy, or discussing visual improvements. Trigger for any design-related conversation including "how should this look", "what color", "font size", "spacing", "layout", "responsive", "mobile", "this copy", "headline", "button text", "microcopy", or when reviewing/critiquing existing interfaces.

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When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' or 'ideas to grow.' This skill provides 140 proven marketing approaches organized by category.

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This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.

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Analyses sales call transcripts (and churn or renewal calls) to find why deals are won, lost, kept or churned. Reads each call across six dimensions (product, messaging, sales process, pricing, competition, customer context), pulls verbatim quotes with the speaker named, counts how often each pattern appears, and writes findings with recommendations. Works with any recorder export or pasted text. Triggers: "win/loss analysis", "why do we lose", "why do we win", "analyse these sales calls", "lost deals", "churn analysis", "objection patterns". Feeds /positioning and /messaging. Not for general meeting summaries or competitor research (use /competitor-research).

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Write high-CTR YouTube and YouTube Shorts titles under 100 characters using 2026 packaging formulas (curiosity-gap, number, how-I outcome, mistake/loss, transformation, versus). Balances curiosity with a real keyword, front-loads the click-deciding words for the 60-char mobile cutoff, and returns 3 to 5 A/B variants tagged by goal for Test and Compare. Use to title or rework a video. Not for the description (use yt-description-writer) or the thumbnail overlay (use yt-thumbnail-brief).

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Write a full YouTube video description under 5,000 characters with a first-150-character hook (the only part visible before Show more, and what shows in search and suggested), timestamped chapters, naturally placed keywords, links, and a clear call to action. Covers long-form and YouTube Shorts. Becomes the create-post content that publishes with the video. Use to write or rework a description. Not for the title (use yt-title-optimizer) or the spoken opening (use yt-hook-scripter).

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Remove the AI tells readers react to in a Facebook Page post: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, announcement auto-pilot. Also --mode audit (under-80 sweet spot, hook, engagement bait), --mode profile (learns how you write) and --mode interview (fills your Story Bank: the stories, scars and numbers posts are made of). Not for writing from scratch (use fb-post-writer). Keywords: humanize, de-AI my post, interview me, audit before posting.

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Iteratively edit and refine a named plan for a task through a conversational loop. Each round, the current plan is shown and the user is asked whether to keep refining, mark the plan as done, or proceed to the implementation or draft. Use when the user wants to plan a task purely through chat-driven refinement.

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Learn unfamiliar technologies used in a repo by studying how the repo actually uses them. Finds patterns, explains concepts in context, and points to examples in the codebase. Use when a repo uses frameworks, languages, or patterns you haven't worked with before. Not for mapping a repo's architecture or domain language. Use oss-explore-repo for that.

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Review other contributors' PRs to learn the codebase and build maintainer trust. Guides structured diff reading, helps formulate review comments, and teaches how to distinguish blocking issues from nits. Use when you want to learn a codebase by reviewing PRs, build trust with maintainers before contributing code, or practice code review on OSS repos. Not for reviewing your own PR — use oss-submit-pr for that.

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Guided codebase exploration for understanding a repo's architecture, patterns, and domain language before contributing. Not issue-specific. builds general understanding. Use when exploring a new repo, wanting to understand how a project works, or preparing to become a regular contributor. Not for learning a framework or language you have never used. Use oss-learn-stack for that.

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Generate a self-contained HTML changelog report showing recent documentation changes with interactive course generation buttons. Use this skill when the user asks for a docs changelog, documentation report, what changed recently, recent doc updates as a report, or runs `/docs --report`. Discovers changes via git history, categorizes them, summarizes what's new, and produces a stunning Obsidian & Amber themed HTML report where each entry has a "Create Course" button that copies the course command to clipboard.

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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for WebSocket and SSE handshakes, auth material, subscription state, realtime message schemas, reconnect behavior, and frame-driven runtime effects. Use when the user asks to inspect a WebSocket or SSE handshake, decode frames, trace subscriptions, follow reconnect logic, inspect auth material sent during realtime setup, or explain how live frames change rendered or persisted state. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for firmware images, partition tables, boot chains, update packages, extracted filesystems, embedded configs, and device-facing trust boundaries. Use when the user asks to unpack firmware, map partition layout, inspect bootloader or init chains, recover update keys or credentials, trace config loading, or explain how a device surface reaches the decisive artifact. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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Complete guide to vibe coding with the CodyMaster skill kit — from idea to deploy. Covers the full workflow, skills used at each phase, and common use cases. Read this first if you are new; reference it whenever you're unsure which skill to invoke.

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