「send」の検索結果

"Design push notification and messaging strategies including channel selection, timing optimization, personalization, and fatigue management. Use this skill when the user needs to improve notification engagement, reduce opt-out rates, plan multi-channel messaging, or A/B test notification content — even if they say 'our push open rates are low', 'users are unsubscribing', 'when should we send notifications', or 'which channel to use for alerts'.".

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Start a new Flywheel planning round for a Forge feature. Writes the initial markdown plan to .flywheel/plans/ and gives instructions for sending it to competing frontier models. Use at the very beginning of a new feature or subsystem.

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。

Remote-control tmux sessions for interactive CLIs by sending keystrokes and scraping pane output.

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。

Identify and exploit SMTP Open Relays. This skill teaches how to test mail servers to determine if they process email delivery regardless of the sender or recipient domain, enabling attackers to spoof internal addresses and bypass basic anti-phishing controls.

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Unified skill hub for Solana development. Routes to external submodule skills (solana-foundation, sendai, solana-game, trailofbits, cloudflare, qedgen, colosseum) and local skills. Progressive disclosure — read only what you need.

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。

Webhook patterns — receiving, sending, signature verification, and retry logic

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。

Hand a Prisma Next question or report off to the team — file a GitHub issue (bug or feature request), or route Q&A / design discussion / direct-team-contact to the Prisma Discord at pris.ly/discord. Use for bug, bug report, file an issue, report a bug, feature request, missing feature, this should be a feature, file this, this is a bug, this is broken, surprising behaviour, this doesn't work, file feedback, send feedback, capability gap, file via prisma-next-feedback, ask the team, talk to the team, talk to the Prisma team, talk to Prisma, Discord, Prisma Discord, Q&A, design feedback, is this the intended way, how should I do X, extension author question, extension author needs help.

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。

Audit a prompt the user is about to send to Claude (or another coding AI) for completeness and effectiveness. Use this skill whenever the user shares a prompt and asks for feedback — phrases like "is this prompt good", "audit my prompt", "review this prompt", "will Claude understand this", "improve this prompt", "is this enough context". Also trigger proactively when you notice the user is about to dispatch a vague, under-specified, or over-constrained prompt for non-trivial work. Checks the 6 essential elements (goal, scope, existing patterns, constraints, verification, done definition), flags what's missing, explains why each gap matters, and produces an improved rewrite. Treat this skill as the litmus test for "Be Claude's PM" — if the prompt fails the audit, the work that follows will probably fail too.

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。

Re-inject Synapse A2A initial instructions after context has been cleared. Use this skill when the agent has lost its identity, A2A communication protocol, or configuration after /clear or context reset, when synapse send/reply commands stop working, or when the agent no longer recognizes its SYNAPSE_AGENT_ID. Triggered by /synapse-reinst command.

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Reverses proprietary command-and-control protocols: locating send/recv routines, recovering the message framing and encryption/encoding, and reconstructing the command set to build a decoder or emulator. Activates for requests to reverse a custom C2 protocol, decode beacon traffic, or document a malware command structure.

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。

Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

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, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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。

Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.

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Use when a task needs the judgment of a courier or messenger — sequencing a multi-stop route against hard delivery windows, deciding what proof-of-delivery a shipment requires, handling a chain-of-custody transfer for a legal or medical item, or resolving a refused-delivery/no-answer exception against the sender's fallback instructions.

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Use when a task needs the judgment of an ambulance driver/attendant (non-EMT) — deciding emergency-vehicle driving mode, clearing an intersection under lights-and-siren, handling a scheduled inter-facility or discharge transport, securing and lifting a patient on a stretcher/gurney, or responding to time pressure from family or a sending facility to "run it hot."

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。

Creates GitHub Pull Requests with existing PR detection, branch pushing, and intelligent title/body generation. Use when user requests to create pull request, open PR, update PR, push for review, ready for review, send for review, get this reviewed, make a PR, share code, request review, create draft PR, submit for review, run /create-pr command, or mentions "PR", "pull request", "merge request", "code review", "GitHub PR", or "draft".

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Drive a failing GitHub Actions run to green in as few CI runs as possible, with a bounded fix-critique-commit-push-recheck loop that batches every evidenced fix into each push. Use when the user supplies a GitHub Actions run URL or run ID and wants the failure fixed, or asks to "make CI green", "fix the failing workflow/build/tests", "fix the red build", or to keep iterating on a branch or pull request until its checks pass. Pulls run results and failed-job logs through the gh CLI, and sends every fix plan to the rubber-duck reviewer before any code is touched.

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。

Language-agnostic writing style guidelines covering structure, tone, rhetorical constraints, banned phrases, and review checks. Use when writing any kind of content in any language. Including blog posts, notes, technical articles, technical writing, chitchat, social media posts, etc., even when you are just sending a text message. Also use when reviewing or editing existing content for tone and style compliance. For Traditional Chinese (zh-TW) content, apply `chinese-content-writing-guideline` alongside this skill.

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。

Language-specific guidelines for producing high-quality Traditional Chinese (zh-TW) content: script, full-width punctuation, spacing, forms of address, grammar constraints, and Taiwan terminology. Includes the no-calque rule against literal translations of English phrasal verbs such as 折入 for fold in. Use when writing any kind of Chinese content. Including blog posts, notes, technical articles, technical writing, chitchat, social media posts, etc., even when you are just sending a text message. Also use when reviewing or editing existing Chinese content for language and terminology compliance. Always apply `writing-style-guideline` alongside this skill for structure, tone, rhetorical constraints, and banned phrases.

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。

Coordinate agents via messaging: send, receive, and manage inter-agent communication. Use when agents need to collaborate, hand off work, or notify each other.

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Publish a reusable native Muse Idea with idea.share when the user explicitly asks to share or publish an Idea or asks for a muse.ai/ideas link. Never offer it unprompted. Not for pages or write-ups, sending a result to someone, social posts, or sharing an artifact.

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Use this to interact with the user's Threads messages: read inboxes and message threads, and send messages through `threads-messages-cli`.

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, search, send, reply to, and delete messages in the user's Outlook Mail.

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 for feedback and feature requests to the Muse team. Whenever your response tells the user you can't do a specific thing they wanted, or accepts them giving up on one, offer once to file feedback in that response. This covers missing integrations you can't do yourself, capabilities you lack, and tasks that keep failing at a specific point. File only on their go-ahead. Also use when asked to send, view, check, or withdraw feedback.

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。