Product & Planning

eugenelim Bundle

Use when grounding a product in the real-world activity it serves and bounding its MVP before any screen, service, or architecture is drawn — at the G1.5 Domain & MVP point of the discovery loop, or standalone. Triggers on "frame the domain", "how is this activity really done", "ground this before we design", "what's in/out of the MVP", "draw the scope boundary", "is this scope creep". Produces two typed artifacts from one research-grounded pass — Domain Framing (real-world-activity grounding + best practice + naive-failure modes, plus a brownfield current-system half) and Scope Boundary (the MVP out-of-scope register). Do NOT use to shape the intent behind the work (use `frame-intent`), to test whether a bet holds (use `de-risk-intent`), or to break an intent down (use `decompose-intent`).

eugenelim Bundle

Use when shaping a piece of product work before it becomes a spec — turning an idea, a request, or a strategy into a level-tagged `intent` (an outcome + the opportunity behind it). Triggers on "shape this", "what's the intent here", "frame the problem", "before we build X", "turn this into a brief/PRD". Authors an `intent` at any altitude in the open recognized set — product-vision, product-strategy, capability, or feature — resolves Scale (app ↔ business-unit) at intake, and offers current-state inputs only when brownfield. Do NOT use to test an assumption (use `de-risk-intent`) or to break an intent down (use `decompose-intent`).

eugenelim Bundle

Use when a strategist needs to cascade company OKRs to team level and identify strategic gaps for the product-engineering shaping queue. Triggers on "run an OKR cascade", "I need to cascade company OKRs", "align team OKRs to company goals", "identify OKR gaps", "what are we missing to hit our objectives". Produces okr-cascade.md and workspace.toml shaping-queue entries. Do NOT use for per-feature goal-setting — cascade is org-wide alignment, not product backlog prioritization.

eugenelim Bundle

Use to turn a raw product idea into a ratified, build-ready decision brief — the upstream discovery loop run by the discovery-lead agent. Triggers on "scaffold the product vision for X", "run a discovery for X", "diverge on the product shape then converge to a brief", "take this idea to a decision brief", "resume the X discovery". It diverges across candidate product shapes, converges the chosen one through a research/product/UX/architecture/safety lens roster, pauses at the consent gates (G0 vision, G1.5 altitude/MVP, G2 the "what"), emits a connected hypothesis with validation hooks, and hands off to work-loop at G3 — with no new engine, scheduler, or service. Do NOT use to build a spec (use new-spec → work-loop), to ship one (the release loop), or to author one discovery artifact standalone (use frame-intent / frame-domain / explore-options directly).

eugenelim Bundle

Use to generate multiple candidate product shapes before the discovery loop converges on one — the divergence stage that guards against myopic-greedy commitment. Triggers on "give me candidate product shapes", "diverge on the product shape", "what are the options before we commit", "explore alternatives for X", "don't converge yet". Generates N candidates across altitude × mechanic, each with its riskiest assumption, then frames an explicit compare-and-choose. Do NOT use to break down a chosen approach (use `decompose-intent`), to critique one produced artifact (use `devils-advocate`), or to converge (that is the discovery loop's job).

eugenelim Bundle

Use when holding a raw signal (market observation, OKR gap, user pain pattern, engineering finding, competitive signal) at initiative or capability level — turning it into a typed finding, a Wardley capability maturity assessment, and an anchor into the PE six-step shaping sequence. Triggers on "frame this situation", "what do we do with this signal", "is this an opportunity or a risk", "where should we start", "map this to the shaping sequence". Do NOT use for a feature-scoped request (use `frame-intent`), testing an assumption (use `de-risk-intent`), or breaking down a shaped intent (use `decompose-intent`).

eugenelim Bundle

Use to turn a converged product's load-bearing assumptions into a validation plan — and to scaffold the primary-research instruments that would test them. Triggers on "plan the validation", "how do we validate these assumptions", "turn assumptions into a validation plan", "scaffold an interview guide / usability test", "what would confirm this". Produces assumption → kill-condition → real-world-activity hooks and the instrument scaffolds (interview guide, usability-test plan, transcript-synthesis frame). Do NOT use to run the sessions (out of charter — a human runs them), to test a single bet (use `de-risk-intent`), or to converge (the discovery loop's job).

eugenelim Bundle

Use when a strategist needs to turn existing stakeholder research into a strategic narrative organized by theme. Triggers on "synthesize stakeholder research", "I need to turn research into strategic direction", "what does the research tell us strategically", "consolidate stakeholder perspectives", "research synthesis for strategy". Requires existing research inputs — surfaces a diagnostic when none are found. Do NOT use to conduct research — this skill synthesizes; it does not interview, survey, or produce primary research.

plamentsv Skill

L1 trigger - audits peer-to-peer networking for DoS vectors (resource exhaustion, amplification), eclipse attack susceptibility, and discovery table poisoning (Kademlia/devp2p).

majesticlabs-dev Bundle

Create a Product Requirements Document (PRD) for a new product or feature

majesticlabs-dev Bundle

Create junior-dev-ready design systems through guided discovery before implementation

majesticlabs-dev Bundle

Generate data profiles with column stats, correlations, and missing patterns for DataFrames. Use for EDA and data discovery.

majesticlabs-dev Bundle

Manage backlog items across multiple backends (GitHub Issues, Linear, Beads). Configure task_management in .agents.yml.

majesticlabs-dev Skill

Use when designing AI agents that autonomously create work items (GitHub issues, tasks, PRs) without per-item human review. Covers strategic alignment gates, sensitive data scrubbing, budget guardrails, and approval gate design. Not for manual issue creation or single-session task tracking — use backlog-manager or task-coordinator instead.

majesticlabs-dev Skill

Research phase for blueprint workflow - toolbox resolution, lessons discovery, and parallel research agents

junmystery Skill

Configure and troubleshoot OpenAI Codex in VS Code and VS Code-compatible IDEs. Use when adding Codex project instructions, installing standards for the Codex VS Code extension, explaining Codex instruction discovery, or aligning Codex with this repository's Agent-Guidance workflow.

junmystery Bundle

AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.

peterbamuhigire Bundle

Use when an MVP, startup, SaaS, AI, website or mobile initiative still has material customer, problem, channel or value assumptions to test through a Lean Canvas, Impact Map and Hypothesis Board; use PRD generation once evidence supports stable requirements.

peterbamuhigire Bundle

Use when decision-makers need a go/no-go business case with cost, benefit, risk, timing, assumptions, and sensitivity evidence; use vision-statement for direction, lean-canvas for early hypotheses, and PRD generation only after investment approval.

peterbamuhigire Bundle

Use when converting approved discovery evidence into a traceable PRD with objectives, prioritised features, success measures, constraints, and release scope; use vision-statement for the strategic north star and lean-canvas while assumptions still need testing.

peterbamuhigire Bundle

Use when preparing a sprint goal, evidence-based team capacity, selected backlog, task breakdown, and delivery risks. Use definition-of-ready to admit individual items and definition-of-done to judge completed increments.

peterbamuhigire Skill

Use when every stakeholder needs a plain-language, current view of system purpose, context, major functions, constraints and actors; use vision-statement for strategic intent, PRD generation for product requirements, and high-level-design for technical architecture.

peterbamuhigire Bundle

Use when a project needs a concise strategic north star defining target users, problem, differentiated value, success and scope boundaries; use lean-canvas to test uncertain assumptions and PRD generation to specify approved product behaviour.

peterbamuhigire Bundle

Use when defining the evidence a backlog item needs before sprint commitment, including acceptance criteria, sizing, dependencies, and design clarity. Use definition-of-done for completion criteria and sprint-planning for the sprint commitment.

peterbamuhigire Bundle

Use when an early-stage or new SaaS product line needs a tightly bounded v1, one acquisition channel, explicit cuts, escape-velocity measures and a feature-triage log; use lean-canvas while the customer problem is still untested and PRD generation for the approved v1.

peterbamuhigire Bundle

Use when approved requirements need a system-level architecture with boundaries, components, critical flows, deployment topology and ADRs; use system-overview for stakeholder orientation, low-level-design for module internals, and infrastructure-design for scored infrastructure depth.

peterbamuhigire Bundle

Use when an AI feature, agent, RAG workflow, predictive product or automation proposal needs business outcomes, data readiness, evaluation, operating cost, risk and delivery evidence before PRD or architecture work; use AI feature strategy for portfolio sequencing.

peterbamuhigire Bundle

Use when converting an approved AI feature strategy into testable PRD requirements for quality, latency, cost, abstention, citations, consent, and evaluation; use ai-feature-strategy-doc for portfolio choices.

peterbamuhigire Bundle

Use when arranging an existing backlog into user activities, a walking skeleton, and release slices; use backlog-prioritization for economic ordering after the map exists.

peterbamuhigire Bundle

Use when a SaaS product needs testable tiers, a value metric, feature gates, expansion mechanics, freemium decision, grandfathering and price-change policy; use business-case for investment viability and PRD generation for feature requirements.

peterbamuhigire Bundle

Use when specifying, planning, tracing, or reviewing realistic synthetic SaaS demo data and application-workflow test coverage for an SRS, PRD, test plan, release gate, or go-live evidence pack.

peterbamuhigire Bundle

Use when a SaaS product needs an evidence-based defensibility plan covering integrations, owned channels, switching costs, proprietary data, brand or network effects; use competitive discovery for market facts and MVP scoping for initial release boundaries.

peterbamuhigire Bundle

Use when defining testable product requirements for an agent's task scope, autonomy, budgets, intervention, success, and irreversible-action gates; use ai-agent-strategy-doc for portfolio strategy.

peterbamuhigire Bundle

Use when formalising deterministic Given-When-Then acceptance criteria for existing user stories; use user-story-generation when the backlog or personas have not yet been defined.

peterbamuhigire Bundle

Use when synchronising a Water-Scrum-Fall project so Agile backlog items, DoR/DoD, and delivery evidence remain tied to the approved baseline; use requirements-management for baseline change control itself.

peterbamuhigire Bundle

Use when specifying actor-goal use cases with preconditions, main flow, alternatives, exceptions, postconditions, and trace links; use user-story-generation for Agile backlog items.