「surface」の検索結果

Re-ingest-correctness SOP for production RAG. Activate when a calling agent builds, reviews, or debugs an ingestion pipeline that runs more than once over a changing corpus — scheduled re-index, incremental updates, CI re-ingest, or a "retrieval has duplicates / shows deleted docs" bug. Encodes the rule — **ingestion must be idempotent: a document's content hash decides insert/update/skip, so re-running over unchanged docs is a no-op** — plus the docstore + doc-hash upsert machinery (LlamaIndex `IngestionPipeline` + `DocstoreStrategy`), the delete-propagation problem, and cross-framework equivalents (LangChain `index()` + `RecordManager`, manual hash table). ENHANCE overlay over [[llamaindex]]: the IngestionPipeline exists in the base skill but the re-ingest-correctness contract is not surfaced.

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Lens — Add a cognitive lens to any problem. It accepts a task description and produces an enhanced description that surfaces hidden dimensions, prerequisites, and lines of inquiry—the things you do not know you do not know. Use when the user asks to brainstorm, analyze, generate a skill, distill, or fuse, or when the input is too simple and needs to be expanded.

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Decision protocol for managing the context/session state of an AI coding tool: when to /clear, when to keep context, and how to detect "context bleed" — the failure mode where stale conversation history biases the model against the current task. Surfaces a discipline that Aider (/clear), Claude Code (/clear), CrewAI (memory=False, re-instantiate), and LangGraph (new thread_id, subgraph isolation) all encode separately but none name as a skill.

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Cross-framework enhancement overlay for choosing a multi-agent topology BEFORE writing any agent. A binary-question rubric — is single-agent + tools enough? do agents need to know about each other? does the output need one voice? — maps the answer to single-agent / supervisor / swarm / sequential / hierarchical. Activates when a coder agent is tempted to "split the work into roles" or reaches for a multi-agent framework. Encodes the *selection rubric* that the per-framework skills assume but never surface. Search keywords: when to use multi-agent, single vs multi agent, do I need multiple agents, supervisor vs swarm, multi-agent vs single agent, agent team design.

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Drive the contracts engine's runtime surface (the stdio MCP server) to verify changes end-to-end. Scoped to public-plugins/plugins/healthcare/skills/contracts/ and ../../servers/documents/.

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Gather and correlate open source intelligence from public sources for authorized investigations, threat intelligence, and attack surface assessment. Use when the user mentions 'OSINT,' 'open source intelligence,' 'digital footprint,' 'public records,' 'threat intelligence,' 'investigate a domain,' or needs to research a target using publicly available data.

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Kalshi exchange mechanics — RSA-PSS auth, order schema, YES/NO orderbook convention, WebSocket, and endpoint surface. Market-type-agnostic shared layer for all Kalshi skills.

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。

[STUB] Options pricing models including Black-Scholes, binomial trees, Monte Carlo, implied volatility surfaces, and Greeks for crypto options

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Launch the app and hands-on verify that it works by interacting with it. Falls back to an existing integration test suite when there is no interactive surface in scope. Use when the user asks to "smoke test", "test it manually", "verify it works", "try it out", "run a smoke test", "check it in the browser", or "does it actually work". Not a unit test runner.

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Interpret third-party feedback by running parallel internal and peer interpretations to surface intent, correctness concerns, and ambiguities. Use when the user asks to "interpret feedback", "interpret comments", "what does this feedback mean", "clarify reviewer intent", "understand this review", or "interpret these suggestions".

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Build a self-contained local prototype at .turbo/prototypes/<slug>.html, drive it, and hand it to the user to settle unknowns that prose cannot answer. Use when the user asks to "prototype this", "build a prototype", "mock this up", "show me what it would look like", "let me try the interaction first", or when a decision waits on seeing a surface or using it firsthand.

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Generate and interpret security-research diffs between Windows versions or patch levels using this repo's WinDiff CLI and databases. Use when comparing Windows builds or binaries such as ntoskrnl.exe, ntdll.dll, win32k*.sys, ci.dll, or cng.sys to find changed syscalls, symbols, types, mitigation flags, callbacks, ETW/EtwTi telemetry, code-integrity behavior, drivers, or attack surface. Explain likely intent and security relevance with Windows-internals knowledge, and frame findings for anti-malware/EDR, anti-cheat, and vulnerability-research audiences rather than returning an uninterpreted symbol list.

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Use when the target has a non-Wi-Fi radio attack surface — Bluetooth/BLE (GATT, pairing, KNOB/BIAS/BleedingTooth), Zigbee/Thread/Matter & Z-Wave mesh (Touchlink, S0 downgrade), LoRaWAN/Sub-GHz LPWAN, SDR capture/replay/rolljam, smart locks/medical/IoT radios. For Wi-Fi/WPA/evil-twin see network-attack.

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Final craft pass applying the compound details from the polish checklist — micro-typography, spacing rhythm, hover states, and a signature detail — directly to code. Use when the surface is functionally complete but feels unfinished, or when the user says "polish this" / "it looks generic" / "add the final touches". Invoke when the user asks for polish on their UI, or mentions 'polish' alongside design / UI / frontend work.

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。

Pre-ship gate — runs detector, verifies brief and tokens, applies the 10-pass finish bar, ranks findings by feedback hierarchy. Use when the user wants to ship, merge, or finalize a surface and needs a verdict (READY / NOT READY / BLOCKED) before committing. Invoke when the user asks for finalize on their UI, or mentions 'finalize' alongside design / UI / frontend work.

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Production-readiness pass — audits and implements the full non-happy-path matrix: loading skeletons, empty states, error messages, partial data, i18n, offline, permissions, and first-run guidance. Use when preparing a surface for production or when the user says "it crashes on empty data" / "there's no loading state" / "harden this". Invoke when the user asks for harden on their UI, or mentions 'harden' alongside design / UI / frontend work.

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Redesign an existing site or app without losing what already works — audits the current surface first, classifies what to preserve (brand, IA, SEO, content), picks a refresh/reskin/rebuild scope, then modernizes deliberately. Use when the user says "redesign", "modernize this site", "refresh the UI", "make this look current", or points at an existing page/URL they want improved rather than rebuilt from scratch. Invoke when the user asks for redesign on their UI, or mentions 'redesign' alongside design / UI / frontend work.

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Full spec-driven pipeline — walks brief → tokens → shape (spec) → craft (build) → converge → ship in one guided run. Writes `.ui-craft/spec.md`. Run when starting a net-new surface from scratch. Invoke when the user asks for sddesign on their UI, or mentions 'sddesign' alongside design / UI / frontend work.

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Inspect a Core UI or code surface for a small number of justified motion opportunities and explicitly identify what should remain static. Use when asked what should animate, where motion would improve feedback or comprehension, how to make an interface feel more alive without over-animating it, or whether a proposed animation is worth adding. Read-only; do not use to review or fix existing motion code or to implement animations.

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Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the `cacheComponents` flag, work through a flood of blocking-prerender / instant validation errors, run the `cache-components-instant-false` codemod, or decide between opting routes out with `export const instant = false` and fixing them in place.

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Explicit polish reference for concentric radius, optical alignment, surface depth, contextual icons, and hit areas. Use only after Core frontend rules and packages/ui. Do not restyle product apps from these examples.

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Check reported lighting quantities and results in supplied simulation PDFs without adding repeated calculation surfaces. Use for scoped luminaire inventories and illuminance results; not simulation or compliance.

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Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface: 6 tools with --full (adds check_action); 13 tools with AR_EXTRAS=1 --full. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.

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Remove the discourse-level (structural) signs of AI writing that survive surface editing: stated lessons and moral-of-the-story closers, tidy single-track arcs, embodied-emotion performance ("chest tightened"), vague allusions instead of named references, unbroken linear structure, and shape convergence across pieces. Grounded in the StoryScope study (Russell et al. 2026): narrative structure alone detects AI text at 93.2% F1, and professional stylistic rewriting moved detection only 1.6 points. Use as the SECOND pass after the humanizer skill (which handles words and phrasing) whenever writing or revising LinkedIn posts, course lessons, blog posts, essays, newsletters, or emails that must read as human. Triggers: "humanize", "de-slop", "AI tells", "make this sound human", "structural pass", "deep humanize".

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。