Results for “discovery”

Use when creating or updating the project skill discovery config — generates or regenerates .dh/skill_discovery.yaml by scanning the repo to infer tech stack, inventorying installed skills via npx skills list, loading candidate skill content before suggesting, and writing a config-driven skill injection file. Triggers on /dh:setup-skill-discovery invocations and programmatic --auto calls from add-new-feature Phase 3.

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Expert product discovery guidance for user research and problem validation. Use when conducting user interviews, validating problems, applying jobs-to-be-done framework, sizing opportunities, customer segmentation, competitive analysis, prototype testing, usability testing, designing surveys, or synthesizing research insights. Covers discovery sprints, continuous discovery, and research operations.

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Product Discovery through an 18-task methodology in 6 blocks — from market analysis to an investor-ready financial plan. Use when someone wants to run Product Discovery, validate a startup, assess a market hypothesis, prepare for an investment round, or raises an adjacent topic — idea validation, niche sizing, competitor teardown, product-market fit, pitch preparation, startup unit economics, geographic expansion into a new country, go-to-market for SEA / Asia / MENA. People rarely name PD explicitly; they say 'is there a market for this', 'assess my idea', 'I need a deck for an angel', 'we are entering Thailand/Singapore/UAE, how do we size it'. Use the skill in those cases too. Three modes: Light (~45 min, idea stage), Full (~2-3 h, MVP with customers), Geographic Expansion (~2 h, product entering a new geography). Produces 3-4 artifacts in /mnt/user-data/outputs/: one-pager.pptx, financial-plan.xlsx, presentation.pptx, optionally interview-guide.docx.

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Builds a DRAFT proposal skeleton from a discovery summary (call notes, discovery brief, CRM record, emails) and the organisation's own proposal template: every template section in order, pre-filled only where the discovery material supports it with the source beside each line, and every section still needing a human input marked HUMAN INPUT with the owner role and the question to answer. Use when the user asks to "start the proposal for <prospect>", "build the proposal skeleton from the discovery notes", "pre-fill our proposal template", "what do we already have for the proposal" or "first cut of the proposal". Do not use for answering a formal RFP, RFQ or tender question set, use rfp-response-drafter instead; for turning a priced estimate into a statement of work use estimate-to-sow. Drafts for human review; never approves, authorises or signs off.

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Performs API inventory and discovery to identify all API endpoints in an organization's environment including documented, undocumented, shadow, zombie, and deprecated APIs. The tester uses passive traffic analysis, active scanning, DNS enumeration, JavaScript analysis, and cloud resource inventory to build a comprehensive API catalog. Maps to OWASP API9:2023 Improper Inventory Management. Activates for requests involving API discovery, shadow API Tespit, API inventory audit, or attack surf...

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Runs an iterative, conversational product-discovery process with a founder/stakeholder: structured interview, live low-fi wireframing, a linked feature/page node-graph built up as you go, a founder-confirmed lock-in checkpoint, then a generated PRD, a Mermaid-rendered sitemap, and a mockup with a full design system (palette, typography, dark mode). Use when building or operating an AI product-discovery chatbot, or when running founder/stakeholder discovery by hand and you need the structure (interview script, node-graph schema, PRD template, design-system handoff order). NOT for implementing the spec'd product once locked — hand off to feature-specific skills (ideal-web-app-builder, tailwind-v4-expert, color-theory-palette-harmony-expert, typography-expert, dark-mode-design-expert) for that. NOT for one-shot PRD generation without an interview loop — if the founder already has a written spec, this process is unnecessary overhead.

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Support drug discovery research by searching public databases for compound activity, molecular properties, drug interactions, and gene–disease associations. Assess drug-likeness, meaning how molecular properties fit established rules for potential oral medicines.

• Finding active compounds for a biological target
• Assessing molecular properties against oral drug rules
• Reviewing drug interactions and reported adverse events

Design how an AI agent finds and loads tools as needed. Compare discovery approaches, organize large tool collections, and assess tool selection accuracy, token costs, and cache reuse without placing every tool definition in the initial context.

• Designing on-demand loading for many MCP tools
• Comparing tool discovery approaches
• Investigating cache misses after loading tools

Find professionals with relevant experience and request a written or voice answer, or a short call, through Instant Expert. Use it for customer discovery and practical advice, with a free simulated test mode to try the process.

• Gathering firsthand experience from practitioners
• Interviewing potential customers
• Requesting a short call with a named professional

Turn brand documents, sales call transcripts, discovery reports, and direct input into writing guidelines. Define a consistent brand personality, adapt tone by context, and attach source evidence, confidence ratings, and recommendations for unresolved questions.

• Consolidating scattered brand materials into writing guidelines
• Extracting brand language from sales call transcripts
• Defining tone for social posts and business proposals

Get oriented with a biological research plugin by checking connected research tools and reviewing available analysis skills. Receive a connection summary, optional setup guidance, and suggested starting points for literature searches, sequencing analysis, drug discovery, or research planning.

• Getting started with the biological research plugin
• Checking connections to literature and drug discovery tools
• Reviewing available sequencing analysis skills

Add or edit skills bundled with Crush, following guidance on file placement, required metadata, compile-time embedding, and discovery tests. It also explains how built-in skills are loaded and how user skills override them.

• Adding a skill bundled with Crush
• Editing an existing built-in skill
• Understanding skill discovery and overrides

Turn an unclear idea into a specification with testable completion criteria. The skill supports discovery interviews, drafts from existing code, completeness checks, and records of decisions and verification in a shared project document.

• Clarifying an idea through questions
• Defining testable project completion criteria
• Drafting a specification from existing code

Check whether AI browsing agents can access content and interact with a website. Review accessible controls, access policies, and discovery files, explain Lighthouse results, and draft fixes with evidence and priorities for review.

• Audit whether AI agents can use a website
• Understand Lighthouse Agentic Browsing results
• Review access policies for different AI agent purposes

Turn a broad research direction into ranked ideas, a refined proposal, and an experiment plan. The workflow combines literature searches, novelty checks, small pilot experiments, and Gemini review to assess evidence and identify useful next steps.

• Explore concrete ideas within a broad research topic
• Check how proposed ideas differ from prior work
• Compare promising ideas through small pilot experiments

Explore a broad research direction through literature searches, idea generation, novelty checks, small pilot experiments, and critical review. Receive ranked ideas plus a refined proposal and experiment plan for the leading candidate, with evidence recorded across stages.

• Finding concrete ideas within a broad research topic
• Exploring improvements to a reference paper
• Comparing promising ideas through small pilot experiments

Explore DeFi products, blockchain-based financial services, aggregated by OKX. Check yields, historical data, and existing positions across supported chains, then handle deposits, withdrawals, or reward claims through the onchainos CLI.

• Find DeFi products and compare yields
• Check DeFi holdings across multiple chains
• Deposit assets or withdraw existing positions

Upgrade MSTest v3 test projects to v4 by updating packages, adapting code to changed APIs, and checking execution behavior. It also helps resolve build errors and problems finding tests in CI after an upgrade.

• Upgrading an MSTest v3 project to v4
• Fixing compilation errors after an upgrade
• Updating custom TestMethodAttribute implementations

Discover subdomains, live hosts, and URLs to build a prioritized map for web security testing. Includes JavaScript analysis, API specification discovery, and monitoring for new subdomains, JavaScript changes, and GitHub commits.

• Building an inventory of web assets
• Prioritizing API and authentication endpoints
• Finding endpoints and secrets in JavaScript

Search Kaggle datasets, competitions, notebooks, and models through its official command-line tool. Download public data into a chosen directory and preserve audit records and file hashes, identifiers used to check downloaded files.

• Finding Kaggle datasets and inspecting metadata
• Downloading public data into a chosen directory
• Discovering competitions, notebooks, and models

Organization-grade cloud and supply-chain attack-surface discovery: S3/GCS/Azure Blob bucket discovery via observed-name mining (CNAME/cert-SAN/Wayback) and bounded two-class permutation (6 prefixes x 15 suffixes on trusted tokens, bounded target-bound expansion on subdomain stems), existence (HEAD/GET) vs public-listing confirmation, object-key triage into 9 value tiers (database dumps, credentials, IaC state, kubeconfig, VCS dirs, config, archives, PII, logs), dangling-CNAME bucket-takeover detection, and the ownership-gated severity model that stops an unattributable public bucket from becoming a false CRITICAL; the fully offline AWS-account-ID recovery from a leaked AKIA/ASIA/AROA access key (base32 decode, runnable stdlib Python, canonical test vector, AWS-documentation-example-ID screening); dependency-confusion confirmation for npm/PyPI (internal-signal classifier -- private-registry binding vs org-namespace match -- paired with a read-only public-registry 404 check and the npm scope-claimability nuance the public search API misses); and passive cloud-native/container/Kubernetes/CI control-plane fingerprinting (Lambda URLs, API Gateway, Cloud Run, App Service, kubelet/etcd/K8s API/dashboard, Jenkins/GitLab/Argo CD) as an org-attribution and exposure surface. Passive/discovery only -- no exploitation, no credential submission, no active control-plane confirmation (a stage-6 validate_cloud active tier is described but out of scope). Use when enumerating a target's cloud storage footprint, recovering an AWS account ID from a leaked key, confirming a supply-chain dependency-confusion vector, or fingerprinting cloud-native/K8s/CI infrastructure for an authorized external recon engagement.

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Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.

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Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice for PacBio + ONT), IsoQuant (de-novo or annotation-guided isoform discovery 2024 SOTA), Bambu (annotation-aware Bayesian discovery + quantification with Novel Discovery Rate), SQANTI3 (isoform classification: FSM/ISM/NIC/NNC + artifact flags), rMATS-long (event calling on long-read isoforms), and minimap2 (-ax splice:hq for HiFi; -ax splice -k14 for ONT cDNA; add -uf only for direct RNA or stranded cDNA preps). Solves microexon detection, recursive splicing, complex multi-exon isoforms, and DTU without transcript-quantification uncertainty. Use when short-read AS limitations (anchor length, complex isoforms, microexons, recursive splicing, transcript ambiguity) demand full-isoform resolution.

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Deep research and discovery before building something new. Explores local projects for reusable code, researches competitors, reads forums and reviews, analyses plugin ecosystems, investigates technical options, and produces a comprehensive research brief. Three depths: focused (30 min), wide (1-2 hours), deep (3-6 hours). Triggers: 'research this', 'discovery', 'explore the space', 'what should I build', 'competitive analysis', 'before I start building', 'research before coding'. Not for cited fact-checking research reports (a separate harness does those); this is pre-build product discovery.

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