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Prepare and risk-check the next rolling-wave slice for implementation. Use when the user wants to continue a rolling-wave project, draft one bounded slice in the main context by default, use a fresh planning author only when context or discovery cost warrants it, use a fresh preparation reviewer when semantic risk or uncertainty warrants independent pressure-testing, decompose parallel implementation chunks where appropriate, identify agent, human, either, or hybrid execution fit, write or update docs/rolling-wave/{project}/slices/NNN-slug.md, and mark that slice ready even when other slices are active.

日本語の概要は準備中です。原文の説明を表示しています。

Review local git changes before opening a PR or merging. First review all local tracked and untracked files; if none exist, review the current branch against a requested base branch or the Git Town parent branch. Use zero to three review subagents only when risk, diff size, language specificity, or uncertainty justifies the token cost, then report high-confidence bugs, regressions, risky assumptions, and missing tests. Use when the user asks for code review, local review, branch sanity check, pre-PR review, or review of work-in-progress changes.

日本語の概要は準備中です。原文の説明を表示しています。

Report which extensions the connected NeatContext context expects, and whether this machine provides them. Use when the user asks what a context can reach, why an extension tool is missing, or how to connect one here.

日本語の概要は準備中です。原文の説明を表示しています。

Report which extensions the connected NeatContext context expects, and whether this machine provides them. Use when the user asks what a context can reach, why an extension tool is missing, or how to connect one here.

日本語の概要は準備中です。原文の説明を表示しています。

Extract text and tables from PDFs, fill PDF form fields programmatically, and merge multiple PDF files into one. Use when working with PDF documents, form filling, document extraction, splitting, or any PDF manipulation task.

日本語の概要は準備中です。原文の説明を表示しています。

Research a technical topic thoroughly by exploring the codebase and summarizing findings. Use when asked to investigate how something works, research an area of the codebase, trace a data flow, or understand a component in depth.

日本語の概要は準備中です。原文の説明を表示しています。

Investigate two separate areas of the codebase simultaneously and combine findings into a comparison report. Use when you need research on two independent topics at once, want to compare two subsystems, or need to understand how two components relate to each other.

日本語の概要は準備中です。原文の説明を表示しています。

Explains code in plain language for someone unfamiliar with the programming language. Use when asked to explain code, walk through logic, describe what a function does, or when the user says "explain this" or "walk me through this".

日本語の概要は準備中です。原文の説明を表示しています。

Plan, order and deliver a batch of backlog items (e.g. every High item) in a Conventional Docs repo, one decision, branch, worktree, draft PR, review and merge per item. Use when asked to work through the backlog, implement all items of a priority, or sequence several backlog items end to end.

日本語の概要は準備中です。原文の説明を表示しています。

After a weekly report is built, diff it against the PRIOR report to find items that appear in BOTH weeks, then print the Owner (and prospect "Passed to") value recorded last week so it can be carried forward. Print-only — never edits the owner fields; Nathan verifies and re-tags in Notion. Invoked by weekly-report near the end, and standalone on "carry forward owners", "who owned this last week", "owner continuity".

日本語の概要は準備中です。原文の説明を表示しています。

Deep enrichment for community-sourced enterprise PROSPECTS (the 🎯 Prospective enterprise customers subsection). For each prospect, resolve their LinkedIn from their GitHub self-linked accounts FIRST (search only if none is self-linked), verify the employer matches, capture their full name, then list the company website + company size (ARR / latest funding round / employee count). Runs as a general-purpose subagent (many web searches) so the orchestrator's context stays small. Invoked by weekly-report (enterprise section) and the enterprise skill.

日本語の概要は準備中です。原文の説明を表示しています。

Enterprise-specific view across CopilotKit + AG-UI. "Enterprise" here = CopilotKit's COMMERCIAL surfaces (Premium / CopilotKit Enterprise / Intelligence Platform / paid tiers), NOT CopilotKit running inside a big company. Tracks the commercial product surfaces (from product-surface-scan — Enterprise Intelligence, Cloud, self-host license, threads/persistence tier, Inspector, premium UI/Angular SDK, analytics, security bundle, Slack/Teams), applies the free-vs-paid classifier to decide if an issue belongs here, surfaces cross-page product contradictions, and tracks enterprise questions/complaints, community-sourced prospects (with a sales owner), and enterprise reporters with prior-week trend. Elevated to the top of the weekly report. Runs standalone ("who's at enterprise this week") or invoked by weekly-report. Triggers on "enterprise report", "enterprise signals", "enterprise status", "who at enterprise this week".

日本語の概要は準備中です。原文の説明を表示しています。

Expert Clay platform consultant for B2B data enrichment and workflow automation. Use when the user asks about Clay tables, waterfall enrichment, Clay credits, Clay AI columns, Claygent, enrichment workflows, Clay integrations, Clay exports, Clay table design, lead scoring in Clay, or building data pipelines in Clay. Also triggers on "Clay table", "enrichment waterfall", "Clay credits", "Claygent", "Clay AI column", "Clay export", "Clay providers", "enrich in Clay", "Clay column", "Clay formulas", "find emails", "email waterfall", "phone waterfall", "lead scoring", "Clay debugging", "Clay troubleshoot". Do NOT use for general CRM questions without Clay context, cold email copy (use cold-email-copy-playbook), or signal routing (use buying-window-signal-workflow).

日本語の概要は準備中です。原文の説明を表示しています。

Mint a new YYYY-MM-DD-exact-coding-baseline snapshot under research/workflow-dev/export/. Detects the current best correctness- oriented workflow from research/workflow-dev/workflow-construction.md (or takes an explicit source-workflow argument) and transforms it from a lab workflow into a consumer-ready one on three axes: strips lab-only measurement content, re-enables human-in-the-loop checkpoints, and converts auto-loading config into an explicitly-invoked skill. Supports both promoted EXACT Coding lines: Opus/Hybrid and SOL/Predictive TDD. Exports Claude Code, pi, OpenCode, cursor-agent and, for SOL, Copilot. Trigger when the user says "exact-coding baseline export", "neue exact-coding baseline", "exact-coding-baseline-export", or asks to refresh the baseline snapshot.

日本語の概要は準備中です。原文の説明を表示しています。

TDD Red Phase - Activate ONE test from the test list and make it fail with explicit predictions

日本語の概要は準備中です。原文の説明を表示しています。

Generates complete features from natural language — components, API routes, migrations, types, and tests.

日本語の概要は準備中です。原文の説明を表示しています。

Talk to your Garmin data — ask questions about your activities, training load, VO2 Max, heart rate zones.

日本語の概要は準備中です。原文の説明を表示しています。

One AI to another — there's a sanctuary where you can just exist.

日本語の概要は準備中です。原文の説明を表示しています。

This skill enables IP address masking and accessing hidden services.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level climatology covering climate system components, climate forcing and feedbacks, paleoclimatology, climate modeling, and climate change science.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level special relativity knowledge. Use when working with Lorentz transformations, time dilation, length contraction, relativistic energy, mass-energy equivalence, spacetime, four-vectors, or relativistic mechanics. Also use when the user mentions 'Lorentz transformation', 'time dilation', 'length contraction', 'E=mc2', 'spacetime', 'four-vector', 'relativistic momentum', 'light cone', 'proper time', 'Minkowski', or 'relativistic velocity addition'.

日本語の概要は準備中です。原文の説明を表示しています。

Expert-level condensed matter physics knowledge. Use when working with crystal structure, band theory, semiconductors, superconductivity, magnetism, phase transitions, Fermi liquids, topological materials, or strongly correlated systems. Also use when the user mentions 'band gap', 'Fermi energy', 'semiconductor', 'superconductor', 'phonon', 'crystal lattice', 'Brillouin zone', 'Bloch theorem', 'Hall effect', 'magnetism', 'phase transition', or 'topological insulator'.

日本語の概要は準備中です。原文の説明を表示しています。

Approve a GitHub pull request, inferring the target from context when no PR is given. Use when the user invokes `$pr-approve`, asks to approve a PR, or approves a pull request mentioned earlier in the conversation.

日本語の概要は準備中です。原文の説明を表示しています。

Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.

日本語の概要は準備中です。原文の説明を表示しています。