「tone」の検索結果

Create a look-alike audience from a seed audience and a candidate population dataset. Classifies Rosetta Stone attributes, generates the same materialized-view scoring pipeline Lookalike Studio emits (Naive-Bayes categorical weights + Gaussian continuous similarity), gates on approval, submits via `narrative_workflows_create`, and monitors the build to completion. Use when: "create a lookalike audience", "find more users like this segment", "expand my seed audience to 500k similar users", "score the population against my customers", "build a look-alike of dataset X". (narrative-audience)

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Produce variants of an existing Style by shifting tone (light/dark), density (compact/relaxed), or accent (palette rotation) while preserving the brand identity. Use when the user wants alternate themes derived from one brand.

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Manage Linear issues from the command line using the linear CLI. Use when creating, updating, listing, or searching Linear issues, managing projects, cycles, milestones, or initiatives, or making Linear API calls.

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Knowledge base from the DoD Manufacturing Readiness Level (MRL) Deskbook (Version 2022, OSD ManTech / Joint Service–Industry MRL Working Group). Use for assessing and managing manufacturing maturity and producibility risk in defense acquisition: the 10-level MRL scale and its non-linear, target-not-grade nature; the five demonstration environments (laboratory → production-relevant → production-representative → pilot line → production line); the nine manufacturing-risk threads and sub-threads; how MRL targets map onto Adaptive Acquisition Framework milestones (MRL 4/6/7/8/9); conducting an MRL Assessment; building a Manufacturing Maturation Plan; putting MRL maturity into contract language (Section L/M, SOW, AS6500A, DIDs); tailoring criteria for S&T, single-system, ship, sustainment, and industry contexts; and screening operational-technology cybersecurity. Manufacturing-readiness focused — it measures producibility risk and frames mitigation; it is NOT a technology-readiness (TRL) guide, a full systems-engineering process model, a cost-estimating or schedule guide, or a deep cybersecurity audit method (see sibling packs for those).

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Knowledge base from the GAO Technology Readiness Assessment Guide (GAO-20-48G, 2020). Use for evaluating technology maturity in acquisition programs and projects: Technology Readiness Levels (TRL 1–9) and related scales (MRL, IRL), identifying Critical Technology Elements (CTEs), the five-step process for a high-quality TRA, the four characteristics of a reliable TRA (comprehensive, well-documented, credible, defensible), Technology Maturation Plans (TMPs), and using TRA results in knowledge-based, milestone decisions. Assessment/maturity oriented: it measures readiness and frames risk — it is not a full SE process model, cost-estimating, or schedule guide (see sibling packs for those).

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Knowledge base from NASA-STD-8729.1A — NASA's R&M (Reliability and Maintainability) standard covering spaceflight and support systems (Revision A, 2017-06-13). Use for NASA's objectives-driven R&M framework — the R&M objectives hierarchy (one Top Objective decomposed into four sub-objectives, paired with tailorable strategies), how R&M requirements are established inside the SMA Plan required by NPR 7120.5, the SMA Technical Authority concurrence/independent-evaluation governance, milestone vs. readiness review gates, the reliability/maintainability/availability vocabulary (Ai vs. Ao, the failure causal chain, risk as a triplet), and the R&M Evidentiary Methods catalogue (FMEA/FMECA, FTA, RBDA, RCM, LORA, plus the space-environment and parts-pedigree analyses). Scoped to NASA spaceflight and support systems and to assurance planning: it is an objectives-and-strategies standard, so it deliberately does NOT prescribe step-by-step analysis procedures (those live in the referenced NASA Preferred Reliability Practices) and is thin on facility R&M, detailed math/derivations, and non-NASA or commercial life cycles.

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Knowledge base from the DoD M&Q BoK (the Manufacturing and Quality Engineering Body of Knowledge), v3.0 of July 2025, published by OUSD(R&E). Use for the manufacturing-and-quality view of the defense acquisition life cycle: what M&Q engineers do across the Adaptive Acquisition Framework phases (Pre-MDD, Materiel Solution Analysis, Technology Maturation and Risk Reduction, Engineering and Manufacturing Development, Production and Deployment, Operations and Support); the twelve M&Q threads (A–L) built on the '5 Ms'; manufacturing feasibility and producibility; Manufacturing Readiness Levels and assessments; Key/Critical Characteristics and process capability (Cp/Cpk, SPC); the standards stack (AS6500, AS9100/ISO 9001, AS9103, AS9145); technical reviews (ASR/PDR/CDR/PRR) and milestone gates; DCMA surveillance; industrial base and supply chain; and sustainment (LCSP, IPS, ILA, ISR). Scope is DoD acquisition M&Q practice on the Major Capability Acquisition path — it is a best-practice compilation, not policy, and is thin on detailed shop-floor process engineering, contract law, and the full text of the cited industry standards (which it names but does not reproduce).

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Knowledge base from the NASA Fault Management Handbook (NASA-HDBK-1002, Draft 2, April 2012). Use for the systems-engineering discipline of designing what a system does when it fails — the fault/failure/anomaly vocabulary, the five FM strategies (two prevention strategies — design-time fault avoidance and operational failure avoidance — plus three tolerance strategies — failure masking, failure recovery, and goal change), the six FM process activities across NASA mission phases Pre-A to E, response-latency-versus-time-to-criticality (TTC) design trades, fault/failure containment regions and FEPPs, the four redundancy approaches, top-down FM requirements development, FM verification vs. validation, the seven dedicated FM milestone reviews (FMCR/FMARR/FMPDR/FMCDR/FMTRR/FMLRR/FMCERR), FM organizational structure, and mined NASA Lessons Learned. Space-mission oriented (flight/ground/operations); spacecraft examples throughout. IMPORTANT: built from an UNAPPROVED DRAFT — several sections (detailed architecture building blocks, the Assessment & Analysis guidance, and Operations & Maintenance) are placeholders in the source and are thin here. Thin on detailed FDIR algorithms, terrestrial/IT fault management, and any approved-standard terminology that may have changed since Draft 2.

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Turns a list of merged changes, closed work items or commit messages the user provides into DRAFT release notes under the version heading and date the user supplies, grouped as features, fixes and other, in the organisation's tone from the style guide or prior notes given, with every entry traced to its source item, breaking changes and required actions flagged first, and internal-only items held back for the release owner to confirm. Use when the user asks to "write the release notes for this version", "turn these merged pull requests into a changelog", "summarise what shipped this sprint for customers", "draft the what's new for this release" or "group these closed tickets into release notes". Do not use for an announcement email or intranet post about a launch, use announcement-drafter instead; for a change ticket, use change-request-pack; for a how-to article about one fix, use knowledge-article-drafter. Drafts for human review; never approves, authorises or signs off.

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Builds a slide-by-slide presentation draft on the user's own slide template and checks every slide against written brand rules (colours with hex codes, fonts, logo placement, slide archetypes, tone, banned visuals), returning the approved outline, the DRAFT deck content and a compliance report as Markdown. Use when the user asks to "build this deck on our template", "make these slides on-brand", "check this presentation against our brand guidelines", "rebuild these slides to corporate identity (CI)" or asks for a CI-compliant or corporate-template presentation. Do not use for an accessibility review of slides, use document-accessibility-check instead. Drafts for human review; never approves, authorises or signs off.

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Builds a personal voice profile from roughly 90 days of the user's own sent messages and meeting speech, then drafts emails and documents that match how the user actually writes, returning the profile and every draft as Markdown for the user to keep, paste or send themselves. Use when the user asks to "write this like me", "match my voice", "draft this in my tone", "build my voice profile" or "refresh my voice profile". Do not use for an announcement in the organisation's voice, use announcement-drafter instead, nor for a weekly status email, use weekly-status-update-writer instead. Drafts for human review; never approves, authorises or signs off.

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Turn a supplied photograph into a bold one- or two-ink editorial poster using expressive cropping, visible halftone and oversized typography. Use for 单双色网点海报、专色编辑海报、risograph-like photo posters or bold monochrome editorial designs.

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Reinterpret a supplied architecture or structural-detail photograph as a bold relief-print poster with carved marks, a restrained ink palette and a tall condensed title. Use for 建筑版画海报、屋檐木刻海报、architectural linocut posters; not for a generic halftone photo filter.

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Gate for any outbound message before it leaves: pull request or issue comment, DM, invite, post, email. Use before sending to check facts, tone, platform rules, registry status and AI-slop, and to block text that fails.

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Guide users through a 6-phase pipeline to plan a complete project — from brainstorming through project metadata to blueprint, starter-file generation, and per-milestone micro-task design with inline pedagogical choreography.

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Create platform-optimized social media content — captions, hashtags, headlines, calls-to-action. Covers tone-of-voice, character limits, hook writing, A/B testing variants, and content repurposing across platforms. Use when writing captions, generating hashtags, crafting hooks, creating A/B test variants, adapting content per platform, or setting up an editorial voice.

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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stor

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Use when the user asks to "keep the launch momentum going after launch week", "plan a changelog / release-notes cadence as GTM", or "is this update worth a relaunch"; produces a T+1→T+30 momentum plan — a launch-moment calendar (milestone / shipped-loop / badge moments only), announcement-tier routing (major = full-channel, medium = targeted, minor = changelog-only), a relaunch legitimacy call, spike-to-owned handoff briefs, and the next Tier-1 moment with launch-stacking spacing. Not for the 30-day content-reuse map or paid amplification execution — use content-amplifier; not for planning the next launch end to end — use launch-tier-planner. 抗第二周断崖/changelog-as-GTM/relaunch/下一发布时刻

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Use when the user asks to "log this subscriber's opt-in", record unsubscribes/complaints, or query lawful basis; curates pseudonymous consent facts through the append-only consent stream and applies suppression/erasure tombstones immediately. Not for SEND scoring — use email-quality-auditor; not for building segments — use list-segment-builder. 订阅同意台账/实时退订抑制/合法性依据登记

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Monitor GitHub workflows, propose fixes for failures, and report status

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Run ADR conformance checks, explain failures, and identify required ADR/doc updates for the current change.

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Review a change for architectural drift, guardrail weakening, and ADR impact before shipping.

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Ship current branch — CI, SonarCloud, code review, security review, fix all issues, merge. Assumes code is already committed and pushed.

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Stage files, run pre-commit, fix failures, loop until clean

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。