Product & Planning Agent Skills

Writes or updates pathway pages for Alan Hirsch's platform, following a 12-section architecture that grounds frameworks in Scripture and story, offers practices, and invites course-based formation.

Exports a platform feature as a product constitution and data reference, including data model, API contracts, and acceptance criteria, for use in AI prototyping tools.

Places generated images into realistic device and print mockups such as laptops, phones, books, posters, and billboards for marketing previews and presentations.

Guides a structured software requirements specification workflow from topic intake through brainstorming, spec writing, planning, review, SRS generation, validation, and improvement reporting.

Runs a structured, multi-round brainstorm to capture actors, features, scope, constraints, and business rules for a project before writing a spec.

Stress-tests a plan against the project's domain model and documented decisions, sharpening terminology and updating DOMAIN.md and ADRs inline as decisions crystallize.

Designs 3D models, selects printing technologies, optimizes prints, and troubleshoots issues for additive manufacturing.

Drafts monthly investor updates, quarterly board decks, and high-signal stakeholder communications that surface wins, misses, risks, and asks clearly.

Guides setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.

Extracts a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md.

Breaks a plan, spec, PRD, or conversation into independently-grabbable GitHub issues using tracer-bullet vertical slices, then publishes them as native sub-issues under a parent tracking issue via the gh CLI.

Provides a suite of five product team skills covering OKR alignment, feature prioritization, sprint planning, user research, and design systems, with scripts and templates for each role.

Verifies each step of a rough implementation plan against source code and current documentation, attaching proof and marking steps as verified or unverified.

Guides SaaS pricing strategy: selecting models, value metrics, packaging tiers, and applying psychology tactics to optimize revenue.

Generates concise, Toss-inspired UX microcopy for buttons, empty states, errors, toasts, confirmations, and form guidance, with tone and localization notes.

Evaluate codebase against enterprise ICP for production readiness, compliance, and multi-stakeholder journey coverage

飞书 OKR：管理目标与关键结果。查看和编辑 OKR 周期、目标、关键结果、对齐关系、量化指标和进展记录。当用户需要查看或创建 OKR、管理目标和关键结果、查看对齐关系时使用。不负责：待办任务管理（lark-task）、日程/会议安排（lark-calendar）、绩效评估

围绕具体产品、产品想法或存量方案，产出用于产品进入、定位、竞争策略、上市路径、能力建设与路线图决策的证据型分析报告。适用于“值不值得做或发布”“进入哪个细分”“目标用户和市场是否成立”“竞品为何这样设计”“该借鉴、差异化或放弃什么”“核心能力与 Roadmap 怎么定”“如何调整已有产品”等请求，也适用于将用户研究、市场信息、竞品实测、内部资料和业务约束整合为决策建议。支持 0→1、存量产品调整、竞品专项与组合分析；默认交付为可独立阅读的飞书云文档，并用正文内 HTML5 block 呈现必要的产品定位图或能力路线图。不用于只需罗列功能、直接撰写实施 PRD，或在缺少依据时给出确定性预测的任务。

Contextual guidance and command discovery. Three modes — narrative (first-time), contextual (mid-task), compact (quick reference). Shows available commands, active skills, and intelligent suggestions based on vault state. Triggers on "/help", "what can I do", "show commands", "how does this work".

Make any software agent-native with HKUDS CLI-Anything — four routed modes: install ready-made harnesses via CLI-Hub (cli-hub list/search/info/install/launch), give agents the cli-hub-meta-skill for autonomous discovery, generate a new harness from any codebase/repo via the 7-phase /cli-anything pipeline, or iterate with :refine/:test/:validate; 40+ harnesses, 2,461 tests, Click CLIs with REPL + --json.

Turns vague features, bug clusters, roadmap items, or launch work into an execution-ready planning packet by choosing the right packet type, separating discovery from delivery, and making blockers, dependencies, and the next move explicit.

SEC EDGAR extraction pipeline: setup, filing discovery by CIK, recipe-driven extraction, and report generation.

Add phase to end of current milestone in roadmap

This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.

Orchestrator + builder for distinctive, production-grade frontends that don't look AI-generated. Derives stack and design context from product-soul/PRD/specs, then runs the anti-slop chain — explore distinct directions, lock a DESIGN.md system, build from golden examples with mandatory polish + every interactive/empty/loading/error state, then review. Load when the user asks to build a UI, design a frontend, build a landing page or dashboard or web app, beautify or redesign a page, make a UI look premium/playful/editorial, says "build me a frontend", "make this not look AI-generated", "design this interface", "give this real polish", or "frontend design". Routes to design-direction, design-system, design-review.

Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.

Orchestrator for the pre-decision business-idea lifecycle — generate ideas, model them, evaluate them, validate them with customers, and only then hand off to product-soul / brainstorming. Routes through `idea-generation`, `business-modeling`, `idea-evaluation`, and `customer-discovery`. Load when the user asks to explore business ideas, find a startup idea, evaluate a venture, validate an idea, says "what business should I start", "should I build this", "is this a good business", "I have a startup idea", "evaluate this venture", "model this business", "validate this idea", "Mom Test this", "Lean Canvas this", "Business Model Canvas", "Value Proposition Canvas", "go/no-go on this idea". Pre-decision suite — once one idea is committed, hands off to `product-soul`. Does NOT design features (use `brainstorming`) or audit built products (use `reality-check`).

This skill should be used when the user asks to "plan a feature", "create PRD", "interview me about requirements", "define stories", "write a spec", "break down feature into tasks", "create implementation plan", "help me scope this feature", "what questions should I answer", or discusses feature planning. Covers the PRD interview process, spec structure, story atomization, and 4-phase workflow from idea to Dex tasks.

Translates stakeholder feature requests into validated outcome statements before any work is committed. Use this skill — proactively and without waiting to be asked — whenever a stakeholder, exec, or customer arrives with a pre-packaged solution: "we need a dashboard", "add a Slack notification", "build an export feature", "create a report", "let's add a filter", "can we just add X". Also triggers for: "how do I push back on this request", "what outcome does this feature solve", "outcome vs output", "outcomes not features", "what are we really trying to achieve", "we're being a feature factory", "I need to reframe this as a problem", "the stakeholder is pushing a specific solution", "discovery before delivery", "assumption testing", "translate this request into an outcome", "ship outcomes not features". Runs the 'One Framework. Four Questions.' protocol (Liatti + Cagan + Torres): Behavior Change → Assumption Test → Cheapest Test → Success Metric. Produces an Outcome Brief with embedded AI prompts ready to pas

ateam-discovery

Turn research into a decision-ready brief tailored to a specific stakeholder and decision.

Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.

Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

Create okr tracker creator operations. Auto-activating skill for Enterprise Workflows. Triggers on: okr tracker creator, okr tracker creator Part of the Enterprise Workflows skill category. Use when working with okr tracker creator functionality. Trigger with phrases like "okr tracker creator", "okr creator", "okr".

Optimizes form completion rates for lead capture, contact, demo request, application, survey, and checkout forms through structured audits and A/B test recommendations.

The meta-framework for how a company runs — the connective tissue between all C-suite roles. Covers operating system selection (EOS, Scaling Up, OKR-native, hybrid), accountability charts, scorecards, meeting pulse, issue resolution, and 90-day rocks. Use when setting up company operations, selecting a management framework, designing meeting rhythms, building accountability systems, implementing OKRs, or when user mentions EOS, Scaling Up, operating system, L10 meetings, rocks, scorecard, accountability chart, or quarterly planning.