Product & Planning

tools-only Bundle

Backlog Item Groomed Schema

tools-only Bundle

MANDATORY Azure Policy discovery requirements for governance constraints

tools-only Bundle

MANDATORY Azure Policy discovery requirements for governance constraints

tools-only Bundle

MANDATORY Azure Policy discovery requirements for governance constraints

tools-only Bundle

Azure governance discovery subagent. Queries Azure Policy assignments via REST API (including management group-inherited policies), classifies policy effects, and returns structured governance constraints. Isolates heavy REST API work from the parent IaC plan agents (Bicep and Terraform) context.

tools-only Bundle

Implements Phase 1 — Instructions, Skills & Dual-Field Governance. Creates Terraform instructions, terraform-patterns skill, updates azure-defaults, and migrates governance-discovery to dual-field output.

tools-only Bundle

**vibe.prd-generated-via-search-and-agentic-simulation.md**

google Bundle

Guides agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).

google Bundle

Generates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters. Use when asked to create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring metrics and resources. Don't use for raw metric discovery or metric selection.

google Bundle

Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.

google Skill

Provides guidance for authoring Apache Airflow DAGs in Managed Service for Apache Airflow (MSAA; formerly Cloud Composer). Covers environment context discovery, Airflow 2 vs 3 compatibility, authoring best practices, and local/remote validation processes. Use when creating or extending an Airflow DAG. Don't use when authoring Python code unrelated to Airflow DAGs.

google Bundle

Diagnoses, remediates, and manages Google Cloud Identity and Access Management (IAM) access issues. Supports two distinct operational modes: (1) Requester Flow for developers encountering access denials (capturing error context, self-service PAM JIT activations, elevated developer self-remediation, or logging structured tickets), and (2) Resolver Flow for privileged administrators (authoritative Policy Troubleshooter analysis, deny policy exemptions, least-privilege role discovery, and PAM/IAM provisioning).

google Bundle

Generates Google Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.

google Skill

Discovers golden base images for creating GKE custom node images based on technical specifications or context clues. Use when finding the golden base image for custom GKE node creation, mapping cluster configuration parameters (GKE version, OS, architecture, accelerators, gVisor, cgroups) to image names, or querying GKE base image maps. Don't use for general GKE cluster creation (use gke-cluster-creation) or standard node pool management (use gke-basics).

google Bundle

Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution skills.

adobe Bundle

Migrates legacy AEM (6.x, AMS, on-prem) to AEM as a Cloud Service via BPA CSV/cache and CAM/MCP discovery, one pattern per session. Use to review/scan a project for AEMaaCS migration — generates a read-only migration-runbook.md — or to fix specific Cloud Service blockers: scheduler, ResourceChangeListener, replication, EventListener, OSGi EventHandler, DAM AssetManager, HTL data-sly-test lint, Classic UI / ExtJS / Coral 2 → Coral 3 dialog migration (lui), Custom Design Widgets (cdw), Vault package install-time dependencies (vault-package-dependencies), Guava cache → Caffeine swaps (guavaCache), and static→editable template modernization. Also externalizes OSGi config secrets to Cloud Manager (scans ui.config/.cfg.json for $[secret:]/$[env:] placeholders) and converts AMS/on-prem Dispatcher configs to AEMaaCS (Branch E).

adobe Bundle

Use when orienting, onboarding, or planning before a concrete task — the entry point for building a customized Workfront UI on Adobe App Builder. Reach for this whenever the user is: brand new to Workfront UI extensions and asking where to start or what the process looks like; describing a Workfront customization idea and asking how to build it; asking for the end-to-end roadmap (set up → scaffold → build → test → deploy → publish); or asking how the React/Spectrum SPA, the serverless Runtime actions, and the Workfront extension points fit together. This umbrella routes each stage to its skill: workfront-ui-extension (front-end SPA + extension points), workfront-actions (Runtime actions + Workfront Public API v21), workfront-local-testing (previewing a build inside Workfront); machine setup and aio app init live in appbuilder-project-init. Skip it and go straight to the matching sub-skill when the user already has one specific task.

google Bundle

Generates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.

adobe Bundle

Use the run-workflow MCP to discover, compose, execute, publish, and save Adobe Firefly workflows. TRIGGER when: user asks what the MCP can do; wants to process images/video/3D via workflow; wants to build/run/save/publish a workflow; wants to list/view saved or recent workflows, presets/interfaces, or golden demos (e.g. 'run banners at scale'); pastes any workflow/batch/execution ID; names a featured workflow (retargeting, product banners, localization, packaging, banner advertising) — call get_featured_workflow first. NOTE: 'banners at scale' = GOLDEN DEMO (list_golden_workflows), NOT the featured workflow 'Product Banners At Scale'. BARE ID = INSPECT ONLY — call inspect_run, never run_workflow_submit. ALWAYS call list_actions first for action/node discovery; a "what tools" question is answered directly from your visible tool list, no call. DO NOT TRIGGER for direct Firefly API calls without MCP (use firefly-api-specs).

hlnd2t Bundle

Convert an existing find-XXXX SKILL.md into a preprocessor Python script, updating configs/<GAMEVER>.yaml and removing the old SKILL.md. Covers xref-string-based and LLM_DECOMPILE-based discovery patterns.

shrugyu Bundle

从游戏客户端（安装包/APK/IPA/EXE 或 dump.cs、lua、usmap、抓包等）反推服务端协议并复现可部署服务端。含阅读路径分派、原理层(primer：三要素/数据包协议/协议表/热更源码)、四阶段路线图(workflow-roadmap：静态分析→建工具+登录链→重定向→补包循环→清单迭代)、11 种反推方法选择器（含内联服务端路线）、接口清单提取器（tools/）、协议规格模板(protocol.spec.yaml)、wire 级定点改写（不等 schema 齐就能跑）、客户端地址来源清查、三轴状态与验收体系、发布运维清单、进度清单(TRACKER.md)、登录链条与功能清单模板。覆盖：账号登录注册、房间匹配、战斗、掉落物资、抽卡、充值与邮件、部署(本地/服务器/Termux/Windows)、客户端对接、闭环验证；并支持 Unity(IL2CPP/Mono/Lua)、Unreal(UE4/UE5)、Cocos2d-x/Cocos Creator(JS/Lua 热更)、C#、AS3、Java、JS 等客户端；含进服后的 Live 运营手册；并含「内联服务端」路线（客户端进程内合成响应、运行时对象合成与字段发现、平台 SDK 登录态复用与目录服/区服两段准入）。

adobe Bundle

AEM Cloud Service expert skill — upgrade outdated Maven dependencies in pom.xml, both literal <version> and same-pom ${property} shapes. Use for "update my aem-sdk-api", "upgrade mockito", or scanning a project for stale dependency versions. Discovery can find <dependency> blocks but "outdated" needs a target version, which the user supplies. Pattern A/B locators and editing strategy are in recipe.md.

taichuy Bundle

用于从 1flowbase 当前源码构建、修复和审计 MCP 配置：只读投影 GUI 用户任务与后端契约，配置 Tool、input/output mapping、参数说明、Group、Binding 与 discovery policy，并通过 mcp_list、mcp_get、mcp_call 验证。只修改 MCP 配置数据；不修改 GUI、业务接口、产品源码或产品语义。

hlnd2t Bundle

Create an Agent SKILL.md fallback for an existing find-XXXX finder that relies on a fragile discovery foundation — above all LLM_DECOMPILE (patterns C/D/E), which matches the decompiled shape of a predecessor function against a stored reference and breaks when a symbol is inlined or de-inlined in a way the reference does not cover. The generated fallback coexists with the preprocessor and runs only when it returns failure, recovering every target robustly by decompiling the predecessor and following the inline/de-inline boundary with semantic anchors. Use when a finder broke on a game update, or you want to durably backstop one before it does. The recipe generalizes to any finder foundation. Triggers: create agent skill fallback, add SKILL.md fallback, robust fallback for finder, backstop LLM_DECOMPILE finder, final guarantee skill

hlnd2t Bundle

Create a new find-XXXX preprocessor Python script from scratch (no existing SKILL.md), add configs/<GAMEVER>.yaml skill and symbol entries. Covers xref-string-based and LLM_DECOMPILE-based discovery patterns. Use when a GitHub issue or user instruction specifies a new function to find.

parcha-ai Bundle

Reconstruct what a Claude Code or Codex agent actually did during one exact session, including goals, decisions, actions, file and git changes, tests, failures, recoveries, final state, and open work. Use when the user says "/recap", "recap this session", "what did this agent do", "give me the full handoff", or asks for an evidence-backed account of a long-running coding-agent session. Use Recall for prior-session discovery; use Recap after a session is identified. Never use it to expose hidden reasoning or to infer unobserved actions.

parcha-ai Bundle

Install, onboard, and run multi-model coding orchestration or solo single-model mode. Invoke when the user says install Parable, install parable.sh, set up or onboard Parable, connect coding subscriptions, names Parable, hands over a backlog, or asks to route work across models. Solo mode (`parable --solo <model>`) runs with a single model. For first-time install intent, collect subscription choices with the harness's native structured-question tool and then run the bundled parable.sh. Not for a single isolated bugfix or standalone code review.

vanillagreencom Bundle

Load to plan a cycle, audit issues, build a roadmap, or decompose research into issues.

vanillagreencom Bundle

Load to plan a cycle, audit issues, build a roadmap, or decompose research into issues.

getlago Bundle

Use when given a Linear ticket (URL or ID) for lago-front and the technical groundwork is missing — a defect report whose validity is unknown, or a change request nobody has costed against the code. Typically a Front-end ticket in Triage/Backlog/Scoping. Triggers on "/triage-frontend-ticket <ticket>", "triage this ticket", "fai analisi tecnica di questo ticket", "is this actually a bug?", "is this feasible?".

pdben-auto Bundle

Research an Amazon market from SellerSprite keyword and competitor exports, filter relevant ASINs by product task and listing attributes, deduplicate parent ASINs, and produce auditable category BI. Use for SellerSprite market research, Amazon FBA product research, keyword-to-ASIN discovery, competitor analysis, parent-ASIN deduplication, or interactive BI dashboards. Do not use for listing copy, personal shopping recommendations, or a simple chart without a defined market scope.

eiei114 Skill

Example Agent Skill shipped by this Pi package template. Use when testing that package skill discovery works.

btspoony Bundle

Morning Star codebase audit — survey any repository and produce prioritized, self-contained improvement plans for the normal Prepare → Execute flow. Strictly read-only on source code. Use when asked to audit or survey a codebase, find improvement opportunities (bugs, security, performance, test gaps, tech debt, dependency upgrades, DX), suggest what to build next (direction/roadmap), or when the user says 'what should I improve / fix / refactor / upgrade in this codebase'. Loads for deep, evidence-first review of a pull request / branch / diff / working-tree changes / a single commit (the `pr` variant — 'deeply review a PR'). Per-variant process detail lives in `references/` (`codebase-audit.md` full audit, `pr-review.md` PR review). Dispatched by PM under Task category `audit`.

btspoony Skill

Morning Star Spec-Driven 双阶段门禁：Prepare（`specify → clarify → plan`）、Execute（`plan(locked) → tasks → implement`；多 task 默认 `Execution mode: sdd`）。覆盖意图门禁、长期目标优先、分批 roadmap 强制落盘、clarify 纪律、hotfix 压缩路径、可验证编辑、Phase Gate 最小证据。Read when judging Prepare/Execute gates, before first implement dispatch, when product/architect enter Prepare, or to justify not skipping plan/clarify. `@project-manager` 每轮非 hotfix 必读；`@product-manager`/`@architect` 锁规格/plan 必读 Prepare；实现角色读 Execute + hotfix 例外。`quick` 禁豁免规则在 `mstar-harness-core`。

btspoony Skill

Morning Star 项目治理层约定 —— `projects/<id>/roadmap.md` 编写约定（frontmatter schema + body 约定）与 `projects/<id>/residuals.json` register 生命周期（open → verified close in place、severity 枚举、provenance 字段）、`_default` 项目回退规则。写/审 roadmap、登记或关闭 residual、判断项目归属（含无项目流程的 `_default` fallback）、或对齐 roadmap/register 与 engine 校验时 Read。schema 事实与 `packages/engine/src/project.ts` 逐字一致；字段语义 SSOT → `mstar-artifacts`；路径符号 → `mstar-conventions`。

nudgebee Bundle

Check for pull requests requesting your review and selectively review them using the review-pr skill