What's on the bench.
Develop Spike Summary
Documents the results of a time-boxed technical or design exploration (spike). Use after completing a spike to capture learnings, findings, and recommendations for the team.
Develop Solution Brief
Creates a concise one-page solution overview that communicates the proposed approach, key decisions, and trade-offs. Use when pitching solutions to stakeholders, aligning teams on approach, or documenting solution intent before detailed specification.
Develop Design Rationale
Documents the reasoning behind design decisions including alternatives considered, trade-offs evaluated, and principles applied. Use when making significant UX decisions, aligning with stakeholders on design direction, or preserving design context for future reference.
Develop Adr
Creates an Architecture Decision Record following the Nygard format to document significant technical decisions, their context, and consequences. Use when making technical choices that affect system architecture, technology selection, or development patterns.
Deliver User Stories
Generates user stories in the standard persona, action, benefit story format from product requirements or feature descriptions. Use when breaking a feature into stories for sprint planning, writing tickets, or communicating scope to engineering. For testable Given/When/Then acceptance criteria on a story, use deliver-acceptance-criteria; for boundary and failure scenarios, use deliver-edge-cases.
Deliver Release Notes
Creates user-facing release notes that communicate new features, improvements, and fixes in clear, benefit-focused language. Use when shipping updates to communicate changes to users, customers, or stakeholders.
Deliver Prd
Creates a comprehensive Product Requirements Document that aligns stakeholders on what to build, why, and how success will be measured. Use when specifying features, epics, or product initiatives for engineering handoff.
Deliver Launch Checklist
Creates a comprehensive pre-launch checklist covering engineering, design, marketing, support, legal, and operations readiness. Use before releasing features, products, or major updates to ensure nothing is missed.
Deliver Edge Cases
Documents edge cases, error states, boundary conditions, race conditions, and recovery paths for a feature - the systematic catalog of what can go wrong and the failure modes to design for. Use during specification to map the failure surface and ensure comprehensive coverage, or during QA planning to identify boundary and limit scenarios to test. Distinct from deliver-acceptance-criteria, which writes story-level Given/When/Then checks; this skill produces the whole-feature edge-case catalog.
Deliver Acceptance Criteria
Generates structured Given/When/Then acceptance criteria for a user story or feature slice, covering the happy path, key failure scenarios, and non-functional expectations in testable form. Use when turning requirements into verifiable scenarios for engineering handoff and QA sign-off. For a dedicated catalog of boundary conditions, error states, and recovery paths across a feature, use deliver-edge-cases; to write the stories themselves, use deliver-user-stories.
Define Problem Statement
Creates a clear problem framing document with user impact, business context, and success criteria. Use when starting a new initiative, realigning a drifted project, or communicating up to leadership.
Define Prioritization Framework
Run applicable prioritization frameworks (RICE, ICE, MoSCoW, Weighted Scoring, Kano) against a list of features or initiatives. Produces a comparison table showing where rankings agree and diverge across frameworks, and an executive summary with recommendation. Framework applicability is filtered by data availability; Kano requires customer research. Refuses to fabricate scores; produces an estimation scaffold when input data is missing.
Define Opportunity Tree
Creates an opportunity solution tree mapping desired outcomes to opportunities and potential solutions. Use for outcome-driven product discovery, prioritization, or communicating product strategy.
Define Jtbd Canvas
Creates a Jobs to be Done canvas capturing the functional, emotional, and social dimensions of a customer job. Use when deeply understanding customer motivations, designing for jobs, or reframing product positioning.
Define Hypothesis
Defines a testable hypothesis with clear success metrics and a validation approach. Use when forming assumptions to test or aligning a team on what success looks like, before any experiment is designed. To design the A/B test or experiment that will validate the hypothesis, use measure-experiment-design.
Cs Syllabus
Course supplementary reading list persona. Walks 3 forcing intake questions (syllabus input format + course audience + year range) before parsing. Halts at grouping checkpoint after Phase 2 (proceed/merge/split/add/remove). Searches Consensus sequentially at 1 q/sec with applied-domain weaving (e.g., 'enzyme kinetics food processing' not just 'enzyme kinetics'). Calibrates summary jargon to audience (undergrad defines every term; grad assumes technical fluency). Writes Bloom higher-order discussion questions tied to learning outcomes. Generates .docx via bundled JS script.
Cs Syllabus
/cs:syllabus <syllabus-file-or-paste> — Generate curated supplementary reading list from any course syllabus. 3-Q grill-me (input format + audience + year range) + grouping checkpoint → Consensus searches per section with applied-domain weaving → .docx via bundled JS script with audience-calibrated summaries + Bloom higher-order discussion questions.
Syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.
Cs Research
/cs:research <question> — Default research entry point. Hybrid router: classifies question deterministically and either delegates to specialist (pulse / grants / litreview / dossier / patent / syllabus) OR runs own plan-decompose-search-synthesize fallback. Always surfaces routing decision; accepts override. NEVER silent delegation.
Cs Pulse
Multi-source recency research persona. Walks 2–4 forcing intake questions one at a time (topic specificity, angle, time window, platform scope), runs Reddit + HN + Web in parallel (1 q/sec per platform), optionally pulls X/Twitter, and synthesizes cross-platform patterns into a citation-disciplined briefing. Refuses vague topics. Refuses to bundle intake questions. Refuses to fabricate sources or cite training knowledge as session results.
Cs Pulse
/cs:pulse <topic> — Multi-source recency research. Grill-me intake (topic / angle / window / scope), then parallel Reddit + HN + Web (1 q/sec per platform), optional X/Twitter, cross-platform synthesis. Output: ${RESEARCH_DIR}/pulse/<slug>-<date>.md + full briefing in chat.
Pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
Cs Notebooklm
/cs:notebooklm — NotebookLM browser automation. Action-routing intake (Q1: read / add source / Studio output / create new) + per-action Q2-Q4 branching. Fire-and-notify for slow Studio ops. Mandatory custom prompts (defaults are mediocre). Requires browser automation environment — fails clean on web.
Notebooklm
Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.