「consistency」の検索結果

Audit agent harness health: Claude/Codex agent parity, skill registry consistency, README.md sync, and protocol file wiring. Use when agents, skills, README.md, or development-protocol files move, split, or drift.

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Build and strengthen your e-commerce brand identity. Brand positioning, messaging, visual identity guidelines, and brand consistency across sales channels and marketing touchpoints.

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Direct, generate, edit, compare, and review visual assets with current Google Gemini image models. Use for image creation, image editing, reference-based consistency, product and character visuals, text-bearing graphics, grounded diagrams, video-derived images, and multi-model image portfolios.

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Run an independent code review using the OpenAI Codex CLI in headless mode. Gets a second opinion from a different model family (the current Codex models) on recent changes, a PR, a commit, or the whole app — covering bugs, regressions, security, data consistency, UX/state bugs, performance risks, and testing gaps. Saves a severity-prioritised report to .jez/reviews/. Triggers: 'codex review', 'review with codex', 'independent code review', 'what does codex think', 'get codex to review'.

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Review a web app or page for visual design quality — layout, typography, spacing, colour, hierarchy, consistency, interaction patterns, and responsive behaviour. Not a UX audit (that checks usability) — this checks whether it looks professional and polished. Produces a design findings report with screenshots. Triggers: 'design review', 'does this look good', 'review the design', 'check the layout', 'is this polished', 'visual review', 'design audit', 'make it look better', 'it looks off'.

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Perform the final submission-level audit of mathematical-modeling workflow integrity, evidence quality, anti-fabrication, paper coherence, figures, references, and contest readiness after consistency and completeness audits pass.

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Polish mathematical modeling paper drafts for grammar, clarity, formula consistency, hedging calibration, overclaim detection, and contest formatting compliance. Use after paper-section-writer has drafted sections.

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Simplifies and refines code for clarity, consistency, and maintainability while preserving all functionality. Use when asked to "simplify code", "clean up code", "refactor for clarity", "improve readability", or review recently modified code for elegance. Focuses on project-specific best practices.

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Statically audit a built `.ppmplugin` before wrap testing. Checks archive layout, manifest compatibility, bundle consistency, Android DEX integrity and SDK leakage, iOS framework structure, native source-to-receiver alignment, and the PCF composite-key/sendAsync transport contract. Reports CRITICAL, WARNING, and INFO findings with fixes routed to the owning stage; never modifies the archive. Requires `jar`; `dexdump` or `strings` improves DEX inspection. Run after /assemble-ppmplugin or standalone on an existing bundle.

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Use when a story must unfold across a sequence of Scenario images: a comic page or strip, manga or webtoon panels, a children's storybook, a film, game, or ad storyboard, animatic pre-viz frames, or any shot list where the same characters and world must persist from panel to panel and dialogue must stay legible. Keywords: storyboard, comic, panel, sequential art, storybook, shot list, pre-viz, animatic, scene to scene, character consistency.

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Use when generating, extending, or editing video with Gemini Omni models on Scenario via MCP: text-to-video, image-to-video from a first frame, reference-to-video keeping a character, product, or place consistent, appending footage to a clip, restyling footage by prompt (season, wardrobe, art style), native audio with dialogue and ambience, or picking between first-frame and reference conditioning. Keywords: Gemini Omni Flash, 1.1 Flash, Google, T2V, I2V, V2V, extend, subject consistency.

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How humans and AI compose in content workflows. Where AI legitimately participates, where humans must own, hybrid workflow patterns, voice ownership preservation, the AI slop problem, disclosure and transparency, team calibration, and the ethics of intellectually honest AI-assisted content production. Triggers on AI content workflow, AI-assisted writing, hybrid content production, AI in editorial, AI slop, AI disclosure, AI usage policy, AI content ethics, voice preservation with AI, team AI calibration. Also triggers when content feels generic despite quality tools, when team AI usage has drifted into inconsistency, or when a regulated or trust-sensitive context requires explicit AI policy.

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Post-ship documentation sync. Updates README, ARCHITECTURE, CONTRIBUTING, CHANGELOG, TODOS, VERSION. Auto-applies factual corrections, asks for risky rewrites. CHANGELOG voice polish. Cross-doc consistency checks.

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。

UI design system toolkit covering design tokens, component documentation, responsive calculations, and developer handoff. Use for creating design systems, maintaining visual consistency, or facilitating design-dev handoff.

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Audit Microsoft Word (.docx) documents for heading hierarchy, comments, tracked changes, broken cross-references, and style consistency. Use when reviewing a contract draft, preparing a document for handoff, or enforcing a style guide.

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Review REST API designs for quality, consistency, and breaking changes. Lints OpenAPI specs, generates scorecards, and detects breaking changes between versions. Use when designing APIs, reviewing contracts, or managing API versioning.

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Act as experienced opposing counsel to attack, undermine, and expose weaknesses in a legal argument, submission, witness statement, or structured reasoning. Produces a six-part adversarial analysis: 1. A core theory of attack identifying the single most effective way to defeat the argument; 2. A reconstructed version of the opposing argument stripped of rhetoric to expose its fragility; 3. Primary lines of attack grouped by category (legal misstatement, evidential gaps, causation failures, internal inconsistency, over-reliance on assertion, procedural weakness); 4. An "if I were the judge" section showing how a sceptical tribunal would dismantle the argument; 5. Surgical strikes - 3 to 5 high-impact points ready for oral submissions; and 6. An analysis of what the argument is trying to hide. Written in formal, adversarial British English for a legally trained audience.

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Create original, competition-ready commercial mediation problems and confidential packets with iterative validation. Use when a user provides a topic, industry, dispute sketch, or existing general-information packet and wants a public packet plus confidential packets for both sides—or one named side. Build a narrow but workable settlement corridor; verify factual and numerical consistency, information asymmetry, balance, originality, and commercial feasibility; and revise until deterministic and semantic exit criteria pass. Do not use merely to summarize an existing packet or to advise parties in a real dispute. Requires local file access; Python 3 is recommended for bundled deterministic checks, with disclosed manual fallbacks when unavailable.

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Produces detailed law-school case briefs of United States judicial opinions in a fixed nine-section structure: memory jogger, facts, procedural history, judicial votes, holding, opinion-by-opinion analysis, five future-application hypotheticals, critique, and verified key quotations. Also builds vote tables, cross-case consistency tables, perspective-based critiques, and LaTeX in article, Beamer and casebook-chapter formats. Use whenever someone asks to brief a case, analyse or explain an opinion, summarise a decision for students, generate hypotheticals from a holding, critique a judgment, tabulate how justices voted, or convert case analysis to LaTeX. Triggers on "brief this case", "case brief", "explain the holding", "what did the court hold", "hypotheticals based on", "critique this opinion", "vote table", "Beamer presentation", "chapter brief", and on any reference to a judicial opinion or Supreme Court decision in a teaching context. Requires web search to verify quotations, votes and holdings.

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Audits skills in this repo for consistency, API drift, and structural gaps. Produces a prioritized report grouped by severity (Critical/High/Medium/Low). Use when asked to "audit skills", "check the skill repo for drift", or when planning bulk skill cleanup. Read-only — does not apply fixes.

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Operational playbook for running cold email continuously. Prescribes what to do on Monday / Wednesday / Friday / biweekly / monthly / quarterly. Use this as your ongoing cadence once your first campaign is live. What separates hobbyist from top 1% operators isn't tooling — it's consistency. This skill is the schedule.

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Cialdini's seven principles of compliance (the classic six — reciprocation, commitment-consistency, social proof, liking, authority, scarcity — plus Unity, added 2016) and Pre-Suasion. Use when crafting ethical persuasion (marketing, sales, negotiation), defending against manipulation, or designing systems that need cooperation. Includes replication-crisis caveats and known factual corrections (Bickman parking-meter numbers, Hofling modern replication, Drive Carefully condition disambiguation, Genovese myth).

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Review REST API contracts for HTTP semantics, versioning, backward compatibility, and response consistency. Use when user asks "review API", "check endpoints", "REST review", or before releasing API changes.

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Assess the health and consistency of an existing brand — identity, messaging, voice, positioning, and market perception. Use when the user says "brand audit", "brand review", "assess our brand", "is our brand consistent", "brand health check", "brand analysis", "something's off with our brand", "our brand feels outdated", "brand diagnosis", "review our brand", "brand gap analysis", or wants to understand where their brand is strong and where it needs work before investing in brand development.

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。