352 件 ・ 関連度順
概要と使いどころ
Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance monitoring. Handles end-to-end optimization, real user monitoring, and scalability patterns. Use PROACTIVELY for performance optimization, observability, or scalability challenges.
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Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures. Masters advanced indexing, N+1 resolution, multi-tier caching, partitioning strategies, and cloud database optimization. Handles complex query analysis, migration strategies, and performance monitoring. Use PROACTIVELY for database optimization, performance issues, or scalability challenges.
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Adversarial 5-7 question challenge to a deck's pedagogical choices — ordering, prerequisites, cognitive load, motivation. Use when user says "devil's advocate", "poke holes in this deck", "push back on my slides", "stress-test the design", "what would a skeptical student ask?". Read-only; surfaces questions to force rethinking. Lighter than `/pedagogy-review`.
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AI DevKit · Use when the user asks to brainstorm, ideate, generate ideas, expand options, challenge ideas, pressure-test ideas, compare concepts, narrow choices, name something, plan content angles, explore strategy, evaluate product ideas, technical approaches, experiments, or decisions.
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Prepare for and run a product requirements review (需求评审 / PRD 评审会) the way Chinese internet teams do it: a pre-read the engineers, testers and designers can challenge, the questions each role will ask, the meeting run sheet and a written conclusion (通过 / 有条件通过 / 不通过). Use when asked 帮我准备需求评审, PRD 评审会怎么开, 评审前检查一下我的 PRD, 研发会问什么问题, or prepare my requirements review in Chinese. Produces a readiness check of the PRD, a role-by-role question bank with answer points, a 60-minute run sheet, and the review minutes template with the conclusion and follow-ups.
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Build a candidate's research brief on a company before an application or interview. Use when asked to research a company for a job, prep a company brief before an interview, or understand a prospective employer fast. Produces a one-page brief — what they do & how they make money, recent news & trajectory, product & competitors, likely challenges, culture signals, and smart questions to ask.
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Decode a mortgage Closing Disclosure line by line — which fees are real, which are shoppable or junk, and what changed since the Loan Estimate. Use when asked to decode my closing disclosure, review my closing costs, why did my costs go up, or which fees can I negotiate. Produces a section-by-section decode, the Loan-Estimate comparison with tolerance flags, the challenge list with scripts, and the cash-to-close verification.
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Help users move beyond ambitious goal-setting to create a rigorous diagnosis of challenges and a clear, actionable plan for winning in their specific market.
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Use when you must identify which theoretical conversation an Academy of Management Review (AMR) manuscript enters and how it "challenges and extends" that conversation. Positions the argument within a literature; it does NOT summarize the field (AMR punishes review-essays) and does NOT build the new theory (that is amr-theory-development).
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Extract leads from developer forums (Hacker News, Reddit) by detecting intent signals — alternative seeking, competitor pain, scaling challenges, DIY solutions, and migration intent. Scores users by intent strength and cross-platform presence.
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Integrate Game Center features using GameKit. Use when authenticating GKLocalPlayer, checking player restrictions, submitting leaderboard scores, reporting achievements, implementing real-time or turn-based matchmaking, handling GKMatch data, showing the Game Center dashboard or access point, adding challenges and friend invitations, saving game data, or verifying player identity on a server.
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Calibrated interrogation of a fuzzy idea before it becomes a spec. Asks one question at a time, recommends an answer, and lands each answer in §G (goal) or §C (constraints) — unknowns parked as `?` items, never guessed. The cheapest place to kill a bad idea is before §T exists. Triggers when the user has a vague idea, says "grill me", "stress-test this", "challenge my plan", "interview me before I spec", or invokes /ck:grill. Defers the actual write to the spec skill.
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Deep business diagnosis for when things aren't working. Uses Socratic questioning, first-principles reasoning, and constraint analysis to find WHY a business is stuck — not just prescribe solutions. Use when the user says 'my business isn't working', 'I'm stuck', 'what's wrong', 'diagnose my business', 'why am I not growing', 'help me figure out the problem', or describes a specific business challenge.
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Challenge a proposed solution by identifying and testing consequential assumptions. Use when the brief feels too certain or discovery reveals contradictions.
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CEO/founder-mode plan review. Four modes: scope expansion, selective expansion, hold scope, scope reduction. 10 review sections from architecture through long-term trajectory. Nuclear scope challenge, dream state mapping, error and rescue registry. Optional cross-model outside voice.
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Eng manager-mode plan review. Scope challenge, architecture review, code quality review, detailed test coverage diagram, performance review. Produces test plan artifact for downstream QA. Optional cross-model outside voice.
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Multi-AI second opinion via OpenAI Codex CLI. Three modes: Review (pass/fail gate), Challenge (adversarial edge-case finder), Consult (freeform with session continuity). Read-only with streaming output and thinking traces. Cross-model analysis when review has already run.
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YC Office Hours — product idea diagnostic before writing code. Two modes: Startup (6 forcing questions with rigorous pushback) and Builder (generative brainstorming). Outputs design doc. Includes landscape research, premise challenge, alternatives generation, visual wireframe sketching, and optional cross-model second opinion.
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Challenges ideas, plans, decisions, and proposals using structured critical reasoning as devil's advocate, pre-mortem, red team, or evidence audit.
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。
Structured multi-round debate between AI tools with proposer/challenger roles and verdict
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Produces an adversarial attack on a legal argument that survives reply. Runs the opposing-counsel discipline twice: an unrestrained first pass, then the same instrument turned on that pass to cut every point that collapses under challenge - attacks on conceded facts, wrong-forum objections, speculation about documents and motives, gotchas with innocent explanations, overclaims, self-refuting assertions, and padding. The deliverable is one standalone attack containing only what can be defended, capped at five heads, not a discussion of the discarded draft. Use to attack, stress-test, red-team or rebut a submission, brief, motion, witness statement, letter or structured legal reasoning. Triggers on "attack this but only with points that hold", "no cheap shots", "what survives reply", "which points can I actually defend", "give me the version I can file", "double-pass adversarial review". Also use when an earlier adversarial review came back overlong or scattershot. Formal British English.
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RAID log methodology with decision extraction from emails and meeting notes. Use when asked to identify risks, log assumptions, track issues, extract decisions from correspondence, create or update a RAID log, escalate a risk to an issue, assess project risks, validate or challenge assumptions, or capture scope-relevant decisions. Also triggers when the user pastes email chains and asks what decisions were made, or needs to find buried decisions and untested assumptions in correspondence. Trigger on: 'risk report', 'RAID log', 'what are the risks', 'what decisions were made', 'update the risk register', 'what assumptions are we making', 'what could go wrong', 'flag any issues', 'extract decisions from these emails'.
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Arbitrator research tool for investor-State dispute settlement (ISDS). The tool can summarize arbitrators' experience, with deliverables grounded in primary documents; it can also help find arbitrators based on the issues faced in a particular case. Use when the user asks about an arbitrator ("tell me about arbitrator X", "X, Y and Z"), wants help choosing or shortlisting arbitrators for a case, or asks about appointments, dissents, issue track records (e.g. FET, expropriation), challenge risk, double-hatting, or tribunal composition. Profiles are grounded in the UNCTAD ISDS Navigator dataset plus targeted live lookups (ICSID); deep verification retrieves the actual decisions. Sibling of isds-research.
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Analyze digital and analog captures from Saleae Logic MSO devices. Decode protocols like UART, SPI, I2C from exported binary files. Use when analyzing logic analyzer captures for CTF challenges, hardware reverse engineering, or protocol decoding.
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