Prepare for fundraising due diligence — runs CTO, CFO, CPO, sales, and codebase health reviews to produce a consolidated investor brief with scorecard, red flags, and strengths. Use before Series A, seed round, acqui-hire evaluation, or board presentation.
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Runs a 5-phase enterprise compliance and security hardening pipeline: regulatory review, GDPR audit, SOC 2 evaluation, dependency scan, and penetration test with cross-framework control mapping..
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Analyze vendor and contractor coordination systems for performance scoring, competitive bid evaluation, SLA compliance tracking, and vendor risk assessment.
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Audit workplace safety compliance systems for OSHA regulatory gap analysis, inspection readiness assessment, permit-to-work management, lockout/tagout program compliance, confined space entry procedures, and electrical safety evaluation..
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Analyze material forecasting and requirements planning systems including MRP/MRP II logic evaluation, BOM explosion accuracy, supplier lead time variability tracking, seasonal demand pattern detection, fabric yield and marker efficiency optimization, MOQ aggregation strategies.
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Analyze in-game economy systems including soft and hard currency source-sink balance, inflation projection modeling, loot table drop rate fairness and pity system evaluation, gacha probability disclosure, player marketplace health and price manipulation risks.
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Audit emergency and crisis triage systems for call prioritization accuracy, resource dispatching algorithm quality, severity classification model evaluation, response time optimization, geographic coverage analysis, mutual aid protocol readiness, and post-incident review workflows..
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。
tinh2/skills-hub-registry☆ 202026年9月5日 更新
Automates the end-to-end detection engineering workflow in Google SecOps using MCP tools. Use when fetching threat intelligence from blogs, generating Threat Detection Opportunities (TDOs), simulating attacker behavior with synthetic UDM events, evaluating rule coverage, generating new YARA-L 2.0 rules to close coverage gaps, and with user approval, deploy them to SecOps. Don't use when asked to perform threat hunting actions, and SOC investigative actions.
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。
vaila-multimodaltoolbox/vaila☆ 192026年10月8日 更新
Manages Agent Platform serving endpoints. Use when you need to create, list, describe, update, or delete serving endpoints for model deployment on Agent Platform. Also use when troubleshooting endpoint permission, quota, or resource busy errors. Don't use for deploying models to endpoints or for running model evaluations.
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。
vaila-multimodaltoolbox/vaila☆ 192026年10月8日 更新
Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for public Vertex AI deployments (use the `vertex-deploy` skill) or for running model evaluations (use the `agent-platform-eval-flywheel` 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。
vaila-multimodaltoolbox/vaila☆ 192026年10月8日 更新
Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.
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。
vaila-multimodaltoolbox/vaila☆ 192026年10月8日 更新
Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.
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。
vaila-multimodaltoolbox/vaila☆ 192026年10月8日 更新
Turn Caveman's exact report-only repository observations into an operator-chosen optimization candidate with a paired baseline/candidate evaluation. Use when the user asks to inspect an optimization observation, evaluate a candidate change, or act on the current Caveman optimization report. Require a logged-in Caveman CLI connection and explicit approval; never infer money or actuation from a profile.
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。
vaila-multimodaltoolbox/vaila☆ 192026年10月8日 更新
Apex test patterns for @InvocableMethod agent actions: per-reason-code branch coverage, bulk safety, callout mocking, deterministic assertions. NOT for testing whether the agent routes to the right topic or answers well — use agentforce/agent-testing-and-evaluation. NOT for designing the error envelope the tests assert on — use agentforce/agent-action-error-handling.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Configuring User Access Policies (UAP) to automatically assign or revoke permission sets and permission set groups based on user attributes. Use when automating permission provisioning on user create/update without Apex triggers. Covers policy configuration, filter criteria, evaluation order, and PSL assignment. Also covers booleanFilter OR logic, the `in` operator for multi-value filters, the `order` tiebreak between competing policies, actions incl. permission set / permission set group / permission set licence / package licence / queue / public group grant and revoke, the UserAccessChange audit object, and deploying the UserAccessPolicy metadata type. NOT for permission set design — use admin/permission-set-architecture. NOT for delegated user admin — use admin/delegated-administration.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Use when a subscriber admin is installing, upgrading, or rolling back a managed package (1GP or 2GP) sourced from AppExchange or a private install URL — covers pre-install evaluation, sandbox dry runs, license and dependency checks, the install/upgrade audit trail, post-install configuration the package's InstallHandler cannot perform, and uninstall fallback. NOT for building managed packages as an ISV (use devops/managed-package-development), unlocked-package development (use devops/unlocked-package-development), or AppExchange listing setup. Trigger keywords: InstalledPackage, installedPackages, securityType, activateRSS, sf package install, sf package installed list, PackageLicense, UserPackageLicense, AllowedLicenses, UsedLicenses, push upgrade, PackageSubscriber, namespace prefix, 04t, certified managed package limits.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Flow Orchestration admin: stage configuration, step assignment, background steps, interactive steps, evaluation flows, work items, pause/resume. NOT for approval routing a standard approval process would handle — use admin/approval-processes.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Use when scoring a list of business or solution requirements against the *actual* capabilities of a specific Salesforce org so each row can be classified Standard / Configuration / Low-Code / Custom / Unfit, given an effort tier (S/M/L/XL), a risk tag, and an AppExchange suggestion when applicable. Trigger keywords: fit gap salesforce requirements, score requirements against salesforce capabilities, salesforce capability matrix, classify requirement as standard config custom, fit-gap effort tier, AppExchange alternative for requirement. NOT for requirements elicitation (use admin/requirements-gathering-for-sf). NOT for architecture decisions on the GAP rows (use architect/solution-design-patterns and standards/decision-trees/). NOT for license or edition selection (use architect/license-optimization-strategy and architect/org-edition-and-feature-licensing). NOT for OmniStudio-specific fit-gap (use architect/omnistudio-vs-standard-decision).
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Identify, score, and prioritize Salesforce AI use cases before any implementation begins — opportunity identification, Impact-Effort matrix scoring, feasibility evaluation across Technical/Operational/Data/Risk dimensions, and ROI framing. NOT for the license checks and enablement steps once a use case is approved — use agentforce/agentforce-service-ai-setup or agentforce/agentforce-sales-ai-setup. NOT for making the data model AI-ready — use architect/ai-ready-data-architecture.
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。
PranavNagrecha/AwesomeSalesforceSkills☆ 192026年10月4日 更新
Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system 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。
umairinayat/Specter-AI☆ 182026年9月29日 更新
Franchise Owner Playbook — franchise evaluation, SOP, multi-unit operations, franchisor relationship, ROI analysis สำหรับเจ้าของแฟรนไชส์ไทย
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。
aiunlocked1412/claude-skill-unlock☆ 182026年4月17日 更新
Influencer marketing AI — brief, pitch, rate evaluation, performance review แบบ data-driven
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。
aiunlocked1412/claude-skill-unlock☆ 182026年4月17日 更新
Use when classifying a stuck, failed, empty, or zero-scoring evaluation as infrastructure or policy failure.
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。
Metta-AI/coworld☆ 172026年10月14日 更新
Use when monitoring Crewrift evaluations, rounds, or rankings across turns with a persistent poller.
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。
Metta-AI/coworld☆ 172026年10月14日 更新