「story」の検索結果

Especialista em construir experiências imersivas baseadas em scroll - storytelling por paralaxe, animações de scroll, narrativas interativas e experiências web cinematográficas. Como as interativas do NY Times, páginas de produtos da Apple e experiências web premiadas. Torna websites em experiências, não apenas páginas. Use quando: animação de scroll, paralaxe, storytelling de scroll, história interativa, website cinematográfico.

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。

[Git] Use when generating developer KPI, performance, contribution value, story point, man-day, or code-quality reports from local git commit history.

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。

[Code Quality] Use when you need to review artifact quality (PBI, user story, test spec, design spec) before handoff. Supports --type={pbi|story|spec-tests|design}.

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。

Triage a GitHub issue that already has the cc-issue-created label and is assumed to be ready to start. First inspect the comment history to decide whether human confirmation is needed (cc-need-human-check, highest priority); otherwise decide whether the issue should be closed as not needed, unanswered confirmation items remain (cc-answer-issue-questions), the description is stale relative to settled comment-history content and must be refreshed before execution (cc-update-issue), or it can move to execution (cc-exec-issue). Dependency checks are out of scope.

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 data into compelling visual narratives by applying narrative structure, annotation techniques, scrollytelling patterns, and honest framing to data journalism, presentations, and infographics. Use when creating data-driven articles or reports, designing infographics with narrative, building scrollytelling experiences, annotating charts to guide interpretation, or when user mentions data storytelling, presentation design, annotated chart, narrative visualization.

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 editing Chinese web fiction, narrative prose, or story drafts that sound AI-generated, overly polished, formulaic, explanatory, or too symmetrical; use to detect AI-writing fingerprints and revise only wording while preserving plot, facts, characters, names, and intent.

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。

Agile product ownership for backlog management and sprint execution. Covers user story writing, acceptance criteria, sprint planning, and velocity tracking. Use for writing user stories, creating acceptance criteria, planning sprints, estimating story points, breaking down epics, or prioritizing ...

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。

Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.

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。

Analyze Chromium-based browser artifacts using Hindsight to extract browsing history, downloads, cookies, cached content, autofill data, saved passwords, and browser extensions from Chrome, Edge, Brave, and Opera for forensic investigation.

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。

Track design iteration history and apply consistent styling decisions across revision cycles. Use when handling follow-up change requests that reference previous design decisions (e.g., '前回も色で良いんだけど', 'same style as before', 'like we discussed').

Bootstrap a new or existing project with a small, file-based documentation system so Claude Code keeps context, lessons, and decisions across session restarts instead of starting cold every time. Sets up a handful of markdown files under .claude/ (standing rules, a free-form note to your next session, a phased roadmap, a prioritized backlog, and searchable history/changelog archives) sized and split so the files read every session stay small while the archives grow without ever costing context. Use this whenever someone is starting a new project and asks how to structure it for long-running AI-assisted work, wants Claude to "remember" things between sessions without relying on chat history, asks for a CLAUDE.md + backlog + changelog setup, mentions "session continuity", "persistent context", "project memory system", or is retrofitting an existing codebase that has no such system yet. Also use to explain or extend an already-bootstrapped bottle system (add a rule, start the archival script, add a new backlog section).

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。

Break an application or feature into thin vertical user-story slices with clear acceptance criteria and user-observable value. Use when planning a backlog, decomposing a feature, writing implementation-ready stories, or turning requirements into deliverable slices.

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。

KI-gestuetzte Textproduktion in drei Teilskills: Allgemeine Texte (Blogpost, Social, Newsletter, Copy, E-Mail, Bericht), narrative Storys (Skript, Kurzgeschichte, RPG, Weltenbau) und PR-Kommunikation (Pressemitteilung, Positionspapier) mit lokalem LaTeX-PDF-Compiler. Kein externer Dienst zwingend erforderlich.

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。

Drafts one anonymised DRAFT case study (situation, approach, outcome as evidenced, optional lessons) from engagement notes, status reports, closing reports, emails and metrics extracts the user supplies, with a fact trace to the notes, an evidence grade on every result, quotes only where the user supplied them with speaker role and permission, an anonymisation log and a confidentiality checklist that must be completed before publication. Use when the user asks to "write a case study from these notes", "turn this engagement into a customer story", "draft a success story for the website", "anonymise this project write-up" or "prepare a reference case for the proposal". Do not use for redacting identifiers from an existing document, use document-deidentification-pass instead; for checking whether a document's claims are substantiated, use claims-evidence-map. Drafts for human review; never approves, authorises or signs off.

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。

Turns one long support ticket thread (helpdesk history, email chain, chat transcript, call notes) into a one-page DRAFT escalation summary: the customer's ask in their own words, account context as stated, a dated history, what was tried and the stated result of each attempt, the current state, and what is needed from whom by when, every line referenced to a message and every missing fact marked UNKNOWN. Use when the user asks to "escalate this ticket", "summarise this thread for tier two", "write the hand-over for this case", "what has been tried so far", "brief engineering on this customer issue" or "prepare the escalation note". Do not use for a batch of tickets, use ticket-triage-pack instead; for the review after an outage, use incident-postmortem-drafter. Drafts for human review; never approves, authorises or signs off.

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 the user asks to "build a story bank", "collect our origin and customer stories", or "assemble reusable proof stories for the message"; assembles reusable narrative units — origin, founder, customer, transformation, and proof stories — each tagged to a claims-ledger ID and a message-house pillar, with every proof labeled Measured / User-provided / [needs source]. Not for authoring the message house or pillars — use message-system-architect; not for brand voice or naming rules — use brand-language-codifier; not for finished long-form prose — use content-writer; not for adjudicating whether a proof is true — use offer-claims-registry. 品牌故事库/起源客户转化/证据故事单元

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 the user asks to "make everyone tell the same story", "write our elevator pitch ladder", or "build a spokesperson Q&A and approved boilerplate pack"; derives from the narrative-registry canon, message house, and brand voice a repeatable enablement kit — an elevator ladder (10-second / 30-second / 2-minute), a spokesperson Q&A (tough questions with on-canon answers), an approved boilerplate/bio pack (25 / 50 / 100-word), and a do/don't language sheet — so sales, support, founders, and partners repeat one consistent story. Not for the launch-day runbook — use launch-day-conductor; not for finished per-channel copy — use content-writer or each discipline creative builder; not for launch-window battle cards — use sales-enablement-kit; this kit never adjudicates a claim. 叙事赋能包/电梯梯度/发言人问答/审定样板/该说不该说

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 the user asks to "plan the participation ramp before we promote", "how much account history or karma do we need in this community", or "design entry incentives and member lifecycle for our own Discord"; produces the per-community pre-promotion warming plan — account-history/tenure expectations (Estimated, named sources), a give-before-ask ledger spec, a per-community etiquette + rule digest with last-verified dates, and the warming → active graduation criteria that channel-registry requires as state-transition evidence — plus the owned-community variant (entry paths + member lifecycle for your own Discord/Slack/forum/企业微信私域). Not for launch-day submissions or T-0 threads — use community-launch-runner. 社区预热/先给后取/账号养成/毕业标准

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why.

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 premise, script, or beat sheet into an ordered storyboard and animate approved keyframes into a coherent video.

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 working with Aws Codepipeline — aWS CodePipeline CI/CD pipeline management and execution analysis. Covers pipeline inventory, stage and action status, execution history, pipeline triggers, artifact stores, and action type configurations. Use when inspecting pipeline health, debugging failed stages, reviewing execution history, or auditing pipeline configurations.

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。

Expert en construction de design systems avancés (tokens, composants, Storybook, Figma sync, versioning, theming)

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。

Creative director v2 — brand vision, campaigns, team leadership, client presentations, storytelling

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 System Builder IA — Expert en construction de design systems (Storybook, tokens, component API, theming, Figma sync)

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。