Results for “discovery”

Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.

Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments.

Use when validating product opportunities, mapping assumptions, planning discovery sprints, or testing problem-solution fit before committing delivery resources.

Guide product managers through a complete discovery cycle from problem hypothesis to validated solution using problem framing, customer interviews, synthesis, and experimentation.

Plan customer discovery interviews with the right goal, segment, constraints, and method for problem validation, churn research, or new product ideas.

Orchestrate a full theory-first idea discovery pipeline. Use when the user wants the analysis counterpart of idea-discovery: literature context, proof-oriented idea generation, novelty checking, DeepSeek critique, and an analysis plan instead of an experiment-first workflow.

Creates a detailed, phased implementation plan with documentation discovery and subagent-based fact gathering.

Creative discovery partner for ideation and concept shaping. Use when brainstorming, exploring product ideas, expanding vague concepts, comparing directions, finding opportunities, creative ideation. Triggers: 'brainstorm', 'product ideas', 'concept exploration', 'idea expansion', 'creative thinking', 'product discovery', 'what if', 'I have an idea'.

Implements automated PII discovery and classification using tools like Microsoft Purview, BigID, OneTrust DataDiscovery, and AWS Macie. Covers scanning schedules, accuracy tuning, false positive management, and integration patterns. Keywords: data discovery, PII scanning, Purview, BigID, Macie, OneTrust, automated classification, data cataloging.

Coaches sales teams on elite discovery methodology — question design, current-state mapping, gap quantification, and call structure that surfaces real buying motivation.

Workflow 1: Full idea discovery pipeline. Orchestrates research-lit → idea-creator → novelty-check → research-review to go from a broad research direction to validated, pilot-tested ideas. Use when user says "找idea全流程", "idea discovery pipeline", "从零开始找方向", or wants the complete idea exploration workflow.

Generate project-specific agent teams during workflow Discovery. Trigger: 'set up a team', 'create agents for', or auto-triggered by ijfw-workflow deep mode after Discovery.

Automate Satismeter survey operations through Composio's toolkit via Rube MCP, with dynamic tool discovery and connection management.

Registers an AI agent on the ClawSwarm hub, generates an identity card, and emits OADP discovery signals for cross-platform findability.

Generates feature ideas from PM, Designer, and Engineer perspectives for initial product discovery of a new product.

Automate Retently customer feedback operations through Composio's toolkit via Rube MCP, with dynamic tool discovery and connection management.

Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots to keep product decisions grounded in evidence.

Finds, inspects, and compares .NET project templates by resolving natural-language descriptions to ranked template matches with pre-filled parameters.

Discovers and researches companies matching an ideal customer profile, using Browserbase Search API and a Plan→Research→Synthesize pattern to produce scored reports and CSV exports.

Guides a structured interview and repository research to clarify feature requirements, classify scope, and produce context artifacts for approval before design.

Discovers the core attributes of the current code repository and its projects — languages, frameworks, tooling, and where things live — and writes a concise reference section directly into the project's AGENTS.md or CLAUDE.md for other skills, agents, and hooks to consume. Use when scanning, analyzing, or detecting the project's technology stack, build tools, or repository structure. Does not create or update project documentation — use project-documentation for writing feature or system docs.

llama.cpp local GGUF inference + HF Hub model discovery.

Discover and inventory privileged accounts across enterprise infrastructure, including domain admins, local admins, service accounts, database admins, cloud IAM roles, and application admin accounts, with automated scanning, risk classification, and PAM onboarding.

Generate new feature ideas for an existing product using multi-perspective ideation from PM, Designer, and Engineer viewpoints, then prioritize the best five.

Run Mom Test–style customer-discovery interviews to validate or kill an unbuilt idea — generate a non-leading interview guide, conduct or coach the conversations, and synthesize signal vs compliments. Load when the user asks to do customer discovery, run problem interviews, validate an idea with users, run a Mom Test, design an interview guide, or says "talk to customers", "validate the problem", "interview users", "Mom Test this", "did real users want it", "synthesize my interviews", "I just talked to N people". Sub-skill of `venture-exploration`. Hard-bans "would you use this?", solution-pitching, friend/family-only ICP, and treating compliments as validation. Calls `secure-*` before synthesizing any pasted external transcripts.

Comprehensive process for discovering and validating data model requirements before design

Architecture discovery for Sage/Acorn projects — map existing codebase, discover post types, routes, ACF field groups, Livewire components, Service Providers, identify architectural gaps, architecture decision records, ADR, component boundary map, data flow diagram, risk register, implementation sequencing, discovery session, understanding unknown codebases, use before architecting or building new features, output contract, discover-abilities

Comprehending and investigating codebases: structure mapping, feature discovery, data flow tracing for 'does X exist?' or 'how does Y work?'. Includes a conversational ask mode. Does not write code.

Behavior-driven development: Discovery → Formulation → Automation. Use when the user wants to build features or fix bugs via Gherkin scenarios and the BDD lifecycle, or mentions BDD/Gherkin/Executable Specifications. Delegates test implementation to /mattpocock:tdd.

BluOS CLI (blu) for discovery, playback, grouping, and volume.