「rop」の検索結果

Get a second opinion from an external LLM at three checkpoints: T1 is the plan valid, T2 which path at a fork, T3 finish plus a QA breaker that tries to break the result. One structured move per exchange (PROPOSE, COUNTER, VERIFY, ACCEPT, BLOCK) with memory across turns, and every exchange mirrored into a human-visible channel. Supports a multi-vendor panel instead of a single reviewer. Triggers: "/secondop", "get a second opinion", "run the review panel".

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Package a contribution (gist, script, fix or skill) as a product instead of a bare snippet: README with problem and result, install steps, a test, license, honest limits and a clear entry point. Use before publishing a gist, sharing a fix or releasing a slice of internal tooling. Triggers: /pack, package this properly, make it a product, ship it with quality.

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Tidy an agent's always-loaded memory index (MEMORY.md) on macOS or Linux: trim long lines, move closed entries to an archive, fold domains into hub files, restore dropped pins and add pointers for orphan memory files. Use when the index is over budget or has orphans. Triggers: /memory-tidy, /mt, tidy memory.

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Check whether something was already decided before proposing it: searches the decisions journal, the declined registry and the rules codex plus semantic search, and returns what was decided, why, what was rejected, and under what condition to revisit. Triggers: "/precedent <topic>", "did we already decide this".

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- Build a sourced, corroborated profile of a named individual from public records, social platforms, professional networks, court and property filings, licensing boards, patents, papers and obituaries — anchoring the name to a… Use when asked to find, identify, background-check or profile a person, verify someone's claimed employment or credentials, or locate a missing or hard-to-reach individual

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Cut background heat and noise on this machine: audit scheduled tasks by runs per hour, autostart entries, GPU holders, power plan and top CPU, then propose disable or stretch candidates, decide line by line with the operator and apply only approved lines. Triggers: /deflate, fan is loud, laptop runs hot, what can I turn off, machine slow from background load.

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Sync CRM knowledge notes in a vault with the live CRM code repositories: pull the read-only repos, detect which changed, and refresh only the affected reverse-engineering notes and the keep/drop/decide note. Triggers: "/crm-sync", "refresh CRM knowledge", "what changed in the CRM code".

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Rewrite machine-written text so it reads like a busy human wrote it: cut 50-70%, break the even rhythm, drop AI-tell words and filler, keep facts and protected terms. Use before publishing any post, reply or email drafted by a model. Triggers: /ai-slop, /slop, humanize, anti-slop, make it shorter and alive.

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Use after substantial web projects or repeated design defects to convert evidence into reusable skill improvements through root-cause analysis, regression scenarios, and controlled proposals without silently changing the core OS.

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Use for a focused high-craft polish pass after structure and art direction are stable; improves typography metrics, spacing rhythm, imagery crop, surfaces, optical alignment, micro-interactions, and restrained detail without redesigning the whole page.

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Read and modify MIKE+ model parameters via the mike-plus MCP server — inspect or change values in any model table (pipe Diameter/Manning in msm_Link, node levels in msm_Node, catchment properties in msm_Catchment, etc.). Use when an agent must identify a current parameter and change it before re-running. Requires MIKE+ + license; mutating tools must run on a copy.

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Operational guide for the NV oOS Model Foundry (Proposal 067) — the cluster fine-tuning flywheel. Phase 1 shipped: the Corpus Foundry (Pro addon, addons/pro/includes/model-foundry/) — consent-gated, deduplicated, PII-scrubbed corpus exporters (trajectory_v1, preference_v1, docs_v1) with deterministic holdout splits and R12 provenance manifests. Covers the governance contract, row schemas, output layout, filter seams, the registration pattern for foundry tool slices, how to add a new exporter, and the test/validation gates. Use when extending the Corpus Foundry, debugging corpus exports, wiring a new data source, or continuing Phases 2–6 (train-worker, registry/serving, eval gate, fleet sharing).

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Builds a WooCommerce-style AJAX product search select (the selectWoo / wooselect dropdown) — class="wc-product-search" + the data-action attribute pointing to woocommerce_json_search_products (products only) or woocommerce_json_search_products_and_variations (products AND variations, often the right choice). Pre-selected items rendered server-side as <option selected> via wc_get_product() + get_formatted_name(); WC's wc-enhanced-select script auto-enqueued on WC admin screens, explicit enqueue required on non-WC pages. Solves the "load 20k products into a select" antipattern AI assistants commonly emit. Use when adding a product picker meta box, a custom WC admin page selector, or any UI where the user must search and pick from many products. Triggers on wc-product-search, woocommerce_json_search_products, woocommerce_json_search_products_and_variations, selectWoo, wc-enhanced-select, "select2 products in WooCommerce", or product-picker meta box scaffolding.

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Produces accessible color palettes and CSS design-token implementations for brands and websites. Use when the task asks for "color palette", "brand colors", "color scheme", "WCAG contrast", "dark mode colors", "design tokens", or "CSS custom properties for colors". Covers color theory, WCAG 2.2 contrast compliance, dark mode, AI palette extraction, and color psychology.

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Generate professional documents — PDF, Word (.docx), Excel (.xlsx), and invoices — from natural language descriptions or structured data. Covers AI-powered and simple document creation, HTML-to-PDF conversion, PDF extraction/OCR, merging, watermarking, and data export. Use when you need to create campaign decks, reports, proposals, invoices, spreadsheets, or any shareable document — especially for Step 7 monthly presentations, campaign briefs, and analytics reports.

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Examine every existing page on the site, build a semantic map across pillars, and add missing internal links so the site becomes a semantic graph anchored on clear topical pillars. Use this skill whenever the user asks to "add internal links", "build internal linking", "build a semantic graph", "link related pages", "strengthen topical authority", "fix orphan pages", "add pillar linking", or wants hub-and-spoke linking between pillars, hubs, and supporting content. Output is an edit list (proposed link insertions) plus optionally direct edits to page source files.

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Generate or audit an `/llms.txt` file at the site root that makes the site legible to LLMs and AI answer engines at inference time, following the llms.txt proposal (Jeremy Howard, 2024). Use this skill whenever the user asks to "build llms.txt", "create llms.txt", "generate llms.txt", "audit llms.txt", "make my site LLM-friendly", "expose the site to AI assistants", "let ChatGPT / Claude / Perplexity cite my site", "add an AI assistants index", or asks about `.md` companion pages for LLM consumption. Output is a valid `llms.txt` file (or an audit) plus optional `.md` companion page generation for top pages.

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Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonn

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A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

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Compiled CLI covering all 52 endpoints of the Anytype local API — objects, properties, tags, search, chat, files — one binary, no MCP server needed.

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Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.

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Create custom AI subagents with proper plugin structure, persona generation, and companion routing skills.

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Analyze cross-channel campaign data, quantify uncertainty, and propose evidence-labeled budget tests without overstating causality.

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When the user wants to optimize signup, registration, account creation, or trial activation flows. Also use when the user mentions "signup conversions," "registration friction," "signup form optimization," "free trial signup," "reduce signup dropoff," "account creation flow," "people aren't signing up," "signup abandonment," "trial conversion rate," "nobody completes registration," "too many steps to sign up," or "simplify our signup." Use this whenever the user has a signup or registration flow that isn't performing. For post-signup onboarding, see onboarding. For lead capture forms (not account creation), see cro.

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。