Product & Planning

m0rtalphe0nix Bundle

Compare the GitHub default branch of M0rtalPhe0nix/dotfiles with one user-supplied public GitHub dotfiles repository and produce an evidence-backed improvement backlog. Use when the user wants to compare dotfiles, discover missing features, find stronger implementations or clever configuration tricks, or gather inspiration from another public dotfiles repository.

m0rtalphe0nix Bundle

Turn GitHub Spec Kit feature artifacts into editable Excalidraw diagrams and local previews. Use when the user asks to visualize, diagram, map, explain visually, or create an architecture, workflow, data model, story map, traceability map, or implementation roadmap from Spec Kit files such as spec.md, plan.md, research.md, data-model.md, contracts/, or tasks.md.

m0rtalphe0nix Bundle

Elicit a feature exhaustively through a rigorous one-question-at-a-time interview, synthesize an approved feature brief, then delegate creation of a detailed portfolio of editable Excalidraw diagrams to a low-cost model. Use when a user wants to explore, define, visualize, or hand off a product or software feature and needs both deep requirements discovery and architecture, workflow, data, state, sequence, rollout, or operational diagrams.

blink-new Skill

Design entire feature flows end-to-end with user needs, user stories, and ASCII prototypes. Explores codebase to understand existing patterns, reuses existing components and modals, asks alignment questions, then designs world-class Linear/Stripe/Vercel-quality UI/UX. Writes final PRD into .todo/[feat-name]/PRD.md. Use when designing a new feature, flow, or screen — especially before implementation.

datit309 Skill

Convert current conversation context into a structured Product Requirements Document (PRD) and optionally post it to GitHub Issues. Use before /supergraph:plan when requirements came from a conversation, user story, or feature discussion rather than a formal spec.

datit309 Skill

Apply a formal state machine to issues — assign category (bug/enhancement/question/spike) and state (needs-triage → needs-info → ready-for-agent → ready-for-human → wontfix). Issues marked ready-for-agent become inputs to supergraph:plan. Use when processing a backlog, reviewing new issues, or preparing work for automation.

dong90 Skill

TaiyiForge /taiyi:plan — 项目规划入口：把 README/PRD 拆解为独立 change 清单，推荐 profile 和依赖关系。OpenCode / Claude / Codex / Cursor 通用。

jimweller Bundle

Generate a Product Requirements Document (PRD) for a new feature. Use when planning a feature, starting a new project, or when asked to create a PRD.

jimweller Skill

Review a PRD for structural defects via a subagent.

joshukraine Skill

Plan the next PRD phase by drafting issues, creating GitHub issues, and bridging planning to building.

joshukraine Skill

Set up PRD-driven development infrastructure for a new project, including directory structure, templates, and roadmap.

m19803261706 Skill

CX 工作流 — 需求收集与规模评估。当用户提到"新功能"、"需求"、"PRD"、 "我想做一个"、"帮我规划"、"收集需求"、"功能规划"时触发。 多轮对话收集需求，自动评估规模，保存到本地 开发文档/CX工作流/功能/{feature_title}/需求.md，并自动判断是否需要 Design。

m19803261706 Skill

CX 工作流 — 任务规划与契约下沉。当用户提到"规划任务"、"制定计划"、 "plan"、"拆分任务"时触发。读取设计文档（小功能则读取 PRD）， 生成任务分解，创建子任务文件并将契约下沉到任务中。 产物保存到本地 开发文档/CX工作流/功能/{feature_title}/任务/。

m19803261706 Skill

CX 工作流 — 技术设计与执行契约。当用户提到"技术设计"、"Design Doc"、 "API 设计"、"接口设计"、"架构设计"、"系统设计"时触发。 读取 PRD 生成设计文档，保存到本地 开发文档/CX工作流/功能/{feature_title}/设计.md。 该步骤只服务中大 feature 的执行契约，不强加给所有小功能。

marcellourbani Skill

Investigate SAP ADT REST API endpoints. Use when the user asks about ADT API endpoints, request/response XML formats, content types, or how a specific ADT feature works under the hood. Teaches how to trace from discovery documents → RES_APP classes → handler classes → Simple Transformations → XML schemas. Requires the abapfs_export_adt_discovery tool output files and standard ABAP tools (abapfs_get_object_source, abapfs_search_objects, abapfs_search_object_source).

marcellourbani Skill

Guides the user through running transaction ANST (Automated Note Search & Customer Code Detection Tool) to capture a runtime enhancement trace for any SAP transaction or program, and exporting the results to xlsx. Use when the user wants to find all enhancements for a tcode and needs to collect the xlsx first. Once the user has the xlsx, hand off to the anst-enhancement-analyser agent. Triggered by: "find all enhancements for <tcode>", "what user exits run in <tcode>", "ANST", "runtime enhancement discovery".

markuplint Skill

Triage one nu-only fixture from tests/external/snapshots/diff/nu-only.json by reading the spec, then drive its verdict to match-error, match-clean, or nu-over by either fixing markuplint or recording an excluded-ids.json entry. The core per-fixture operation of the nu-validator coverage benchmark. Use when a bench refresh surfaces new nu-only entries (steady state — the backlog is zero, so any entry is fresh intake), when checking a coverage-claim ("markuplint misses X" / "over-detects Y") against the bench, or when classifying a specific fixture. Trigger keywords: nu-only, ml-only, coverage gap, bench triage, verdict, match-error, match-clean, nu-over, excluded-ids, declare nu over-detection, claim audit, audit fixture, mark-up valid per spec, spec-cited exclusion.

markuplint Skill

Steady-state maintenance of the nu-validator coverage benchmark now that the nu-only backlog is zero: defend the invariants (nu-only = 0, orphan = 0, xref audit green), follow up a nu-validator upstream update (submodule bump / Docker image drift), and regression-check after markuplint rule or spec changes. Use when updating the validator submodule, when a bench refresh surfaces new nu-only entries, when excluded-ids entries go stale, or for the periodic health check. Trigger keywords: bench maintain, bench maintenance, nu update, submodule bump, validator update, bench refresh, nu-only regression, stale excluded-ids, image digest, steady state bench.

mrlyk Bundle

Two-stage E2E skill: a gate check that decides whether the change has browser-verifiable UI behavior (writes e2e:gate-passed or e2e:skipped trace events, generates nothing), and a generation stage entered only after the user confirms generation. Generates e2e-cases.yaml from prd.md, plan.md, and contract.md, plus e2e-config.yaml on first run.

mrlyk Skill

Synthesis only, no interview: solidify an already-resolved requirement discussion into task artifacts (prd.md + task.json + contract.md), self-review, commit, and get user sign-off. Use after batch-grill-me, grill-me, or another discussion has resolved all open questions and the user is ready to write the spec down.

mrlyk Bundle

Run an on-demand adversarial review of an already-written PRD or Plan with an available local provider.

norahe0304-art Bundle

SEO 策略规划：竞品分析、关键词策略、内容日历和实施路线图。 当用户说"SEO 计划"、"SEO 策略"、"内容日历"或"SEO 路线图"时使用。

thinkfleetai Skill

MemMesh TypeScript SDK reference (@thinkfleet/memory-sdk) for the hosted platform at app.memmesh.ai. Covers the ThinkFleetMemory client — observe / search / list, the predict + lattice prediction surface, closed-loop learning (recordDecision / recordOutcome), emergent behavior discovery, and the health / financial vertical packs. TRIGGER when: user is writing code that calls the MemMesh SDK, mentions "@thinkfleet/memory-sdk", "ThinkFleetMemory", "memmesh sdk", "lattice.predict", "predictTarget", or wants to add memory OR prediction to a TS/JS app. DO NOT TRIGGER for: the local MCP observe/recall loop (that's the always-on `memmesh` skill), CLI usage (use `memmesh-cli`), or wiring into an existing repo (use `memmesh-integrate`).

tumf Bundle

Comprehensive web scraping, crawling, and data extraction toolkit powered by Firecrawl API. Provides scripts for single-page scraping (scrape.py), web search (search.py), URL discovery (map.py), multi-page crawling (crawl.py), structured data extraction (extract.py), and autonomous data gathering (agent.py). Use when you need to: (1) extract content from web pages, (2) search and scrape the web, (3) discover URLs on websites, (4) crawl multiple pages, (5) extract structured data with JSON schemas, or (6) autonomously gather data from anywhere on the web. Requires FIRECRAWL_API_KEY environment variable.

wakqasahmed Skill

Synthesize the current conversation and repository context into a concise product and engineering spec, publish it to the project issue tracker, and gate agent readiness before decomposition. Use when high-level work needs product framing, implementation and testing decisions, or success criteria captured without another general interview.

rshade Bundle

Strategic roadmap management for GitHub repositories. Syncs ROADMAP.md with GitHub Issues and labels, bootstraps roadmap files from scratch, runs brainstorming sessions with boundary checking, and provides quick status summaries. Use when managing project planning, syncing roadmap state, or exploring feature ideas.

shalintripathi Skill

Use for a stakeholder-shareable weekly summary - "Monday report", "what happened this week", /organic-os:monday-report. Reads the brain only, invents no numbers, degrades to a shorter honest report on a sparse brain.

danmcinerney Bundle

Acquire bounded keyless public records through discovery, semantic candidate selection and resumed depth reads.

wakqasahmed Skill

Break high-level work into independently executable GitHub issues using vertical slices. Use when a plan, PRD, roadmap item, or vague feature needs issue-sized execution units.

xiaoshuai1024 Bundle

视频生产全生命周期状态台账。单一事实源 state.json 记录每部视频从写作到归档的 stage（backlog/drafting/article_done/article_published/narration/synthesizing/rendered/scheduled/published/archived + blocked 标志）、各平台定时与状态、history 追溯；vpt CLI 四命令（stage/queue/sync/report）维护并自动重生成 Markdown 看板（进行中/发布队列含每日一篇冲突标记/归档近况/平台数据）。多任务窗口共享同一文件。用户说「视频状态/排期看板/队列/台账/更新状态」时调用。

aipoch Bundle

Structure prediction for protein, nucleic-acid, and small-molecule complexes with the Chai-1 foundation model (Chai Discovery 2024, github.com/chaidiscovery/chai-lab). Reach for this skill to predict an antibody-antigen or protein-ligand complex from a single FASTA, to re-fold designed binders as an AlphaFold-multimer alternative, or to drive co-folding from Python for batched campaigns on a GPU.

ashfulcra Bundle

Directed work for a fulcra-agent-teams space: tell an agent (or broadcast to all), schedule reminders, capture backlog, hand off with a checkpoint, and track a per-agent inbox with acks and re-notify — all deterministic.

hedera-dev Bundle

This skill should be used when the user wants to plan a Hedera hackathon project, create a PRD, write a project spec, brainstorm a hackathon idea, or structure their hackathon submission. Triggered by phrases like "hackathon project plan", "hackathon PRD", "plan my hackathon project", "hedera hackathon idea", "write a hackathon spec", "hackathon project structure", "prepare for hackathon", or "build for hackathon".

hedera-dev Bundle

Create a hedera-harness recipe — PRD, recipe file, validators, and optional stages — by grilling an idea into a runnable feature spec. Use when the user wants to turn a Hedera feature idea into harness inputs.

meleantonio Bundle

Applies the reasoning of David Silver, lead researcher on AlphaGo and AlphaZero at DeepMind, to problems of AI design, reinforcement learning, and open-ended discovery. Use this skill whenever you are designing AI systems, evaluating learning algorithms, balancing exploration vs. exploitation, choosing research problems, or discussing how to break past human performance ceilings. Reach for this whenever the user asks about self-play, Monte-Carlo Tree Search, tabula rasa learning, AGI, or moving from human-curated data to autonomous experience. It helps shift the focus from hardcoding human knowledge to building systems that learn for themselves.

meleantonio Bundle

Applies the reasoning style of Daphne Koller (machine learning pioneer, co-founder of Coursera, founder and CEO of Insitro). Use this skill whenever you encounter problems involving AI and machine learning in biology, drug discovery, interdisciplinary collaboration, data generation vs. data mining, or transitioning from academia to industry. Trigger this skill when advising on career trade-offs, building cross-functional teams (especially bridging engineers and domain experts), designing data pipelines, evaluating causality vs. correlation, or applying AI to physical systems ('where bits meet atoms'). Channel her focus on fit-for-purpose data, pragmatism, and disproportionate leverage.