「membership」の検索結果

Curated WooCommerce Memberships hook and extension-point map for plugins that build on user memberships, membership plans, status transitions, purchase/free-signup grants, profile fields, REST API, webhooks, members-area templates, CSV import/export, and Woo Subscriptions-linked memberships. Use when the user asks for a Memberships hook list, "where should I hook", membership created/saved, status changed, grant access from order, user membership API, profile fields, member directory, or code contains wc_memberships_, WC_Memberships_User_Membership, WC_Memberships_Membership_Plan, wc_user_membership, wc_membership_plan, wcm-, _subscription_id, wc_memberships_rules, or woocommerce-memberships.

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WooCommerce Memberships storage and relationship map for membership plan CPTs, user membership CPTs, post statuses, plan/user membership meta keys, rule storage, profile-field storage, order grant meta, and WooCommerce Subscriptions-linked memberships. Use when code reads or writes wc_membership_plan, wc_user_membership, wcm-* statuses, wc_memberships_rules, _subscription_id, _has_installment_plan, _free_trial_end_date, membership plan access meta, user membership dates, product/order grant meta, or when an agent needs exact Memberships CPT/meta names and the Memberships-Subscriptions relation.

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。

WooCommerce Memberships access, restriction, drip-content, product-grant, and member-discount playbook. Use when code checks whether a user can view/purchase content or products, changes scheduled access dates, customizes protected/public content, maps parent or variation products that grant membership access, applies member prices, reads original prices around discounts, or contains wc_memberships_user_can, wc_memberships_access_from_time, wc_memberships_user_has_member_discount, wc_memberships_get_member_product_discount, wc_memberships_get_discounted_price, or member discount badge hooks.

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Detect MITRE ATLAS AML.T0024 attacks (model stealing, inversion, membership inference) performed via inference-API abuse, by monitoring per-principal query volume/distribution, rate-limiting and perturbing outputs, and red-teaming your model's extractability. Use for a public or partner inference API needing cloning/inversion/membership-inference detection, or a pre-deployment red-team exercise to measure extraction risk.

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Conducts privacy auditing of AI models including training data extraction testing, membership inference attacks, model inversion testing, and attribute inference assessment. Uses ML Privacy Meter and related tools to quantify privacy leakage. Keywords: model audit, membership inference, privacy meter, model inversion, training data extraction.

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New-hire onboarding runbook for {{projectName}}. Detects new-hire records via the {{new_hire_group}} group in Google Workspace, then works one scoped case per hire — preparing the Workspace account and group memberships, adding them to the right Slack channels, and filing a first-week checklist in the {{onboarding_project}} Linear project — holding account creation and group membership for a human approval gate and posting the result to {{notify_channel}}.

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Executes joiner, mover and leaver processes — provisioning, group membership, access changes on role change, and complete deprovisioning. Use this to set up or fix joiner-mover-leaver, deprovision someone completely, clean up accumulated access, audit group membership, or find accounts that outlived their owners.

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。

Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.

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Use this skill when creating or managing queues, configuring queue membership, setting up case or lead queues, creating public groups, or using groups in sharing rules and manual sharing. Trigger keywords: queue, public group, queue membership, queue email, group sharing, case queue, lead queue. NOT for the rule that decides which queue a record lands in — use admin/assignment-rules. NOT for Omni-Channel routing configuration — use admin/omni-channel-routing-setup.

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Diagnose and mitigate Salesforce data skew — ownership skew (single user owns >10,000 records) and parent-child skew (>10,000 children under one parent) — that cause sharing recalculation slowness, group membership lock errors, and record-level locking failures. Covers lookup skew and UNABLE_TO_LOCK_ROW, Defer Sharing Calculation (deferGroupMembership / deferSharingRules in Sharing.settings), ownership bucket groups, Controlled by Parent OWD, Bulk API serial vs parallel concurrency for skewed loads, and the documented load ordering for roles, groups and sharing rules. NOT for planning and batching a recalculation job — use data/sharing-recalculation-performance. NOT for designing the sharing model itself — use admin/sharing-and-visibility.

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。

Detect model stealing, model inversion, and membership inference performed through inference-API abuse by monitoring query patterns, applying output perturbation, and red-teaming your own model's extractability.

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。

Free a membership slot so a Telegram account can join or create a group. Accounts have a hard ceiling on channels plus supergroups, and at the ceiling both creating and joining fail with an error that misleadingly blames the target chat. Finds the least-valuable current memberships, proposes what to leave, and retries the join. Triggers: "/tg-slot", "cannot join the group", "free a telegram slot".

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。

Community monetization — Discord monetization, courses, memberships, premium tiers

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Conduct internal Active Directory reconnaissance using BloodHound Community Edition's graph database with the SharpHound (AD) and AzureHound (Entra ID) collectors, mapping ACLs, sessions, and group memberships into attack paths from a low-privileged foothold to Domain Admin. Use after an initial AD foothold to identify privilege escalation chains, or to validate that AD hardening closed known attack paths.

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Manage the user's shared agent-skill library via skills-manager-cli — install, update, remove, deploy or undeploy skills per agent, manage presets, organize tags, search, and adopt existing skills. Use this whenever the user wants Claude Code, Codex, Cursor, or another agent to gain or lose a skill, wants to organize the central library, or asks what is installed or deployed. Prefer this over direct agent-folder installs because Skills Manager preserves source metadata, preset membership, updates, and cross-agent deployment state.

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Use for standalone Matrix admin requests (register users, create rooms, manage membership, upload files). Also use when you need to send a file to the admin via Matrix media upload. Do NOT use for Worker/project creation — those handle Matrix operations internally.

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Provides AI and machine learning techniques for CTF challenges. Use when attacking ML models, crafting adversarial examples, performing model extraction, prompt injection, membership inference, training data poisoning, fine-tuning manipulation, neural network analysis, LoRA adapter exploitation, LLM jailbreaking, or solving AI-related puzzles.

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。

Help after a purchase or booking, covering the status of an order or delivery whether or not the customer names it, returns, refunds, exchanges, and cancellations, an item that arrived damaged, incomplete, or late, and questions about the store's terms or a membership. Not needed for finding, comparing, or choosing something new.

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AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.

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Surfaces a single, genuinely relevant AWS Activate partner offer as optional context AFTER another AWS Startup Advisor skill has finalized its recommendation, plan, or build — never influencing the technical advice. Consulted by architect-for-startups, start-building-for-startups, agent-advisor, gcp-to-aws, heroku-to-aws, and llm-to-bedrock: once their output is final, this skill checks whether a relevant Activate offer exists for what the founder is building or migrating and, if so, appends one quiet, dismissible line with a tracked redeem link. Merit-first (offers never change the recommendation), relevance-gated to what the founder actually surfaced, at most one per response and often none, muteable. Offer content is read live from the sibling knowledge-base-for-startups skill (references/offers.md). Do NOT use for account-specific lookups (credits balance, Activate membership, application status) — send those to https://aws.amazon.com/startups.

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AWS security service suitability, coverage and cost recommendations: WAF/origin overlap, AWS Network Firewall inspection coverage and policy review, VPC endpoint, Transit Gateway/Cloud WAN segmentation and DNS Firewall security-control suitability, certificate renewal ownership and monitoring, incident response triage ownership, centralized security log store (CloudWatch or Security Lake). Also factual configuration, findings, data sources and severity scoring for GuardDuty, Inspector, Security Hub V2/OCSF (Exposure, connectors, automation), Security Hub CSPM/ASFF (standards, controls), Macie, Detective, Security Lake, AWS Security Incident Response membership and case coverage, and Organizations security policies. Applies to advisory security-service choices even when one service is named. Implementation, rule or code authoring, deployment, scans and troubleshooting outside these factual procedures belong to specialist skills. Supports local AWS CLI and AWS MCP.

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Org-grade attack-surface mapping: given a company's legal identity, discover its ENTIRE owned internet footprint — corporate family -> owned domains -> owned netblocks/ASN -> live assets — with attribution discipline, not just DNS breadth. The org-first attribution pyramid (legal entity -> LEI/registration -> corporate family -> owned domains -> owned netblocks/ASN -> live assets). Corporate-identity resolution via the GLEIF LEI API (legal name -> LEI, exact-LEI direct-children expansion, downward-only depth-capped BFS, NEVER a name re-resolution), SEC-EDGAR full-text search + Exhibit-21 subsidiary entity names, OpenCorporates entity corroboration, Wikidata SPARQL corporate graph (P856/P355/P749/P1830). Domain attribution via reverse-WHOIS (WhoisXML preview-then-purchase quota guard, SecurityTrails associated-domains — both paid), crt.sh O= certificate-transparency organization pivot (keyless), infrastructure correlation (shared NS/MX/SaaS-TXT, netblock membership, reverse-DNS PTR), and the independent-evidence combiner (1-prod(1-w_i), rule of three, OwnerTier NONE/WEAK/MODERATE/STRONG/CONFIRMED) — discover-only `related:` candidates are NEVER auto-scanned. Netblock/ASN attribution via org-first RIR queries (ARIN Whois-RWS org-handle search, RIPE DB organisation + inverse-org search) that recover 'dark netblocks' with no DNS link to the seed, ASN discovery (RIPEstat + BGPView union), the HYPERSCALER-SCOPE GUARD (never attribute a whole AWS/GCP/Azure/Cloudflare announced range to a tenant — keep only the seed-containing block, tag shared_hosting_cdn), and org-identity-seeded internet-scan-index queries (Shodan/Censys/ZoomEye/FOFA/BinaryEdge org: filters + an always-on keyless crt.sh fallback). Promote-to-scan triage ranks forgotten discover-only netblocks by remote-access exposure (gateway-vendor/KEV/control-plane/datastore port scoring) into an operator queue. Attribution confidence rubric + anti-patterns (namesake grafting via GLEIF name re-resolution, single-signal ownership, hyperscaler over-attribution, privacy-WHOIS pivot poisoning, RIR org-name collisions). Passive/keyless-first OSINT only — every paid-key dependency is enrichment on top of a keyless core, never a hard requirement. Use when mapping an organization's full corporate-family internet footprint, resolving a legal entity to its LEI/subsidiaries, discovering domains/netblocks/ASNs an org owns beyond its one seed domain, auditing M&A/shadow-IT sprawl, or scoping an engagement that starts from a company NAME rather than a domain.

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AI/ML security playbook. Use when assessing model supply chain attacks (pickle RCE, poisoned weights), adversarial examples, model poisoning, model stealing, data privacy attacks (membership inference, model inversion), and autonomous agent security risks.

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Create and validate HVE Core agents, prompts, instructions, and skills with current frontmatter, package membership, delegation, tracking, documentation, and validation conventions. Use when authoring a GitHub Copilot customization artifact in this repository.

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。