「questions」の検索結果

Interview you into a durable personal MEMORY.md — your decision rules, patterns, past failures, and preferences — that any AI can read to help you better, with privacy guardrails built in. Use when asked to build my memory file, help my AI remember me, create a MEMORY.md, or set up context about myself. Produces a structured personal-context file drawn out through good questions (how you decide, what you keep repeating, what you don't want to repeat), organized for an AI to use — while explicitly refusing to store sensitive data like credentials, financial, health, or others' personal info.

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。

Interview the user with sharp, one-at-a-time questions to turn a vague request into a tight, complete brief any other skill can run on. Use when a request is fuzzy, under-specified, or 'help me think this through', or before running a skill that needs inputs the user hasn't given. Produces a structured brief (goal, audience, constraints, success criteria) and hands off to the right skill — by interrogating, not guessing.

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。

Turn interview notes into a structured candidate scorecard and hire recommendation. Use when asked to write an interview scorecard, a candidate evaluation, an interview debrief, or to summarize feedback into a hire/no-hire call. Produces a per-competency assessment with evidence and ratings, an overall recommendation with confidence, and the open questions for the next round — evidence-based, bias-aware, and decision-ready.

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。

Turn a folder of accumulated documents into one decision-ready brief — the skim-map pass over the pile, the extraction against the brief's actual questions, the conflict reconciliation when documents disagree, and the provenance trail back to sources. Use when asked read all this and tell me what matters, synthesize this folder for the new lead, turn these 20 docs into a brief, or what does all this material actually say. Produces the pile map, the question-driven extraction, the reconciled brief with per-claim sources, and the didn't-read honesty ledger.

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。

Decode a care-home contract before a parent moves in — the fee-escalation clause with no cap, the needs-can-no-longer-be-met eviction trigger, the guarantor line that quietly makes you personally liable, and the after-death charges nobody mentions on the tour. Use when asked to review a care-home or nursing-home contract, what does this admission agreement mean, can they raise the fees, or can they make my parent leave. Produces a clause-by-clause decode ranked by financial and eviction risk, the questions to put in writing before signing, and the negotiate-or-verify list. Pairs with long-term-care-options for choosing the home; this is for the contract. Not legal advice.

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。

Decode an employment benefits package into what it's actually worth and where the fine print bites. Use when someone asks 'is this offer good', 'decode my benefits package', 'what does my equity actually mean', or 'what should I ask HR before signing'. Produces a benefit-by-benefit decode with real dollar values, ranked red flags (vesting cliffs, clawbacks, 'discretionary' bonuses, unlimited-PTO economics), and the questions to ask HR before signing.

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。

Design a 360-degree feedback survey or write a structured 360 feedback report. Use when asked to build a 360 feedback process, write 360 feedback for a colleague, design a feedback survey, or produce a feedback report. Produces either a complete survey instrument with rating scales and open-ended questions, or a structured narrative feedback report with themes, strengths, and development areas.

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。

Prepare for an industry analyst briefing (Gartner, Forrester, IDC and similar). Use when asked to prep an analyst briefing, write an AR briefing document, build talking points for an analyst call, or prepare a Magic Quadrant / Wave submission narrative. Produces a briefing kit — objective, company/product narrative, differentiation, proof points, the demo storyline, anticipated questions, and follow-up commitments.

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。

Decode a 401k or workplace retirement plan — the real cost of its funds, the match's fine print, vesting math, and the plan features worth using or avoiding. Use when someone asks 'is my 401k any good', 'decode my 401k plan', 'which funds should I look at', or 'what fees am I paying'. Produces a fee decode in dollars-over-time, match and vesting math, a fund-lineup triage by cost, and the questions for HR or the plan administrator.

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 an all-hands that lands with everyone from intern to VP — the mixed-altitude structure (the story for all, the numbers for some), the wins-with-names section done right, the hard-news slide handled straight, and the Q&A design that gets real questions. Use when asked build the all-hands deck, make the monthly town hall not boring, how do we share the numbers with everyone, or announce this change at all-hands. Produces the segment structure, the altitude-mixed content rules, the hard-news handling, and the Q&A mechanics.

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。

Structure vague opportunities and unclear briefs into actionable one-page problem statements. Use when asked to clarify a vague brief, frame an undefined problem, make sense of an unclear opportunity, or when the user says 'we need to figure out what to do about X' or 'I've been asked to look into Y'. Produces a structured problem brief with reframed questions, scoped boundaries, and a minimum viable research plan.

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。

Manual intent elicitation skill. Use when the user asks to clarify a fuzzy idea, run an elicitation session, design an agent/skill/workflow, identify strategic tension, do a postmortem, align taste/brand direction, or turn vague judgment into an actionable Intent Brief. The skill asks 3–5 sharp questions first, then compiles answers into an Intent Brief and routes the result into system/workflow change. Never run automatically or on a schedule.

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。

Read and write Perplexity: ask AI questions with web search and citations, list models, run raw searches. Trigger phrases: perplexity, sonar, ai search.

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。

Debugs failing GitHub Actions CI runs for PostHog PRs, commits, and branches, and answers broad CI-health questions ("is CI red?", "is master green today?", "what's broken right now?"). Use when the user asks why CI is red, asks for the current CI or master status, or mentions a failing check, GitHub Actions run, Depot runner, workflow, job, shard, merge queue kick, flaky test, lint failure, typecheck failure, snapshot diff, migration check, generated types drift, or skills build failure. Start with the `hogli ci:insights` digest (cross-run CI history from engineering analytics), then guides read-only inspection, failure classification, smallest local reproduction with hogli, and safe reporting without rerunning CI or posting to GitHub. Running unattended as the "Master-red diagnosis" workflow: see references/master-red-incident.md.

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。

Transforms knowledge sources into an Obsidian StudyVault. Two modes: (1) Document Mode — PDF/text/web sources → study notes with practice questions. (2) Codebase Mode — source code project → onboarding vault for new developers. Mode is auto-detected based on project markers in CWD.

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。

Edit, trim, cut, caption, subtitle, reframe, combine, add background music to, or export video, audio, and image files through Cassette. Use this skill whenever the user asks to change, preview, or render a media file in the project — even if they never say "Cassette" or name a tool — for example "trim the intro off demo.mp4", "add subtitles to this clip", "make me a 30-second cut with music", "why is there dead air at the start". Drives the local Oh My Cassette stdio MCP tools in Codex or Claude as one multi-turn conversation with the Cassette agent, with per-turn timeline previews, guided questions, and rendering only on explicit export.

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。

Use only after explicit Codex `$superloopy:superloopy-research` or Claude Code `/superloopy:superloopy-research` invocation, a research task started with a leading `loopy` or `루피` (such as `loopy research`), or an active Superloopy loop explicitly routing a research deliverable here. Evidence-backed Superloopy research orchestration with automatic advisory usage targets, parallel read-only lanes, per-retrieval verdicts, graded and dated sources, empirical verification, a priced claim ledger, cited synthesis, and optional reports. Do not activate from research, investigate, look-up, summarize, deep-dive, report, or similar vocabulary alone, in any language; ordinary questions, debugging, and implementation context-gathering stay with their primary workflows.

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 strategic research engine — decomposes questions into parallel research threads, spawns multiple agents, and synthesizes into actionable strategic analysis

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 generated or changed WooCommerce code — extensions, payment and shipping integrations, checkout customizations, and order/product logic — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WooCommerce APIs: wc_get_order, wc_get_orders, wc_get_product, WC() cart or session, woocommerce_* hooks, Store API endpoints, payment gateways, order or product meta, HPOS, subscriptions, or bookings. Use on 'review this Woo plugin', 'is this HPOS compatible', or after tasks like 'write a WooCommerce extension', 'add a checkout field', 'hook into the order flow', or 'update stock'. Enforces HPOS-safe order access, CRUD over direct meta, feature-compatibility declarations, server-side checkout validation, money-handling discipline, and hooks over template overrides. DO NOT USE for WordPress code without WooCommerce APIs (use wp-guard), generic code review (use clean-code-guard), test review (use test-guard), or store configuration and admin-screen questions.

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 generated or changed WordPress code — plugins, themes, and blocks — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WordPress APIs: add_action/add_filter, shortcodes, meta boxes, AJAX handlers, REST routes, WP_Query or $wpdb, widgets, or WP-CLI commands. Use on 'review this plugin', 'is this safe to ship', 'make this translatable', 'speed up this query', or after tasks like 'write a plugin' or 'add an endpoint/shortcode/meta box'. Enforces escaping and sanitization, nonces plus capability checks, prepared database queries, core-API-first development, translation-ready strings, and query/caching discipline. DO NOT USE for WooCommerce-specific order, product, or checkout logic (use woo-guard), non-WordPress PHP, generic code quality review (use clean-code-guard), test code review (use test-guard), server or hosting configuration, or conceptual WordPress questions.

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 generated or changed production code before it ships, using Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks in any programming language. Best used reactively after an agent writes, edits, refactors, or fixes code, before presenting, committing, or merging the result. Use when the user asks "review this PR", "is this safe to merge?", "make this cleaner", "audit this code", "refactor this", "fix this bug", or after a coding agent produced implementation code. Can also guide writing when explicitly invoked before a risky edit. Invoke it on your own initiative the moment you finish writing, editing, or refactoring non-trivial production code, before presenting or committing — don't wait to be asked. DO NOT USE for factual/conceptual questions, CI/tooling config, git workflow, running/debugging tests, pure architecture discussion, prose writing, data analysis, or test-code review (use test-guard).

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。

Use when drafting an ACM CCS rebuttal during the HotCRP author-response window, covering threat-model defenses, adaptive-attack objections, ethics and disclosure questions, anonymity constraints, adversarial reviewer pushback patterns, and decision-focused replies aimed at the meta-reviewer.

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。

Plans and builds end-to-end Fabric data platforms on the Bronze, Silver, and Gold medallion pattern: ingestion to analytics, PySpark and Delta layers, pipeline orchestration, per-layer Spark tuning, Materialized Lake View versus notebook choices for Silver and Gold, and Direct Lake handoff. Use for layered architecture design, planning and recommendations. For questions over an existing Power BI report use fabriciq.

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。

Answers natural-language business questions over existing Power BI reports and semantic models through the FabricIQ MCP endpoint, discovering artifacts, resolving entities, generating the DAX itself, and returning a plain-language answer. Use when the user asks a data question, including one that says to query the model directly. For DAX the user supplies, or measures to save, use semantic-model-authoring.

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。