10,242 skills found ¡ Page 283 of 342
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firecrawl / firecrawl-monitorAlert by webhook/email on web changes â use for "monitor/watch/track/alert me when": recurring checks on known URLs (prefer over repeated one-off scrapes) or web-wide watches for new results (queries + goal).
firecrawl / firecrawl-agentAutonomously navigate websites and extract structured data across pages
firecrawl / firecrawl-interactDrive a live browser on a scraped page: click, fill forms, log in, paginate, infinite-scroll
firecrawl / firecrawl-developer-indexSearches current documentation, release notes, API references and public repository issues for libraries, frameworks, SDKs, APIs and CLI tools with `firecrawl developer`.
firecrawl / firecrawl-research-indexFind the papers that answer a research query in Firecrawl's research paper index â a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math â using semantic search, semantic and structuralâĻ
nWave-ai / nw-at-completeness-checkCanonical AT completeness gate â research-anchored 7-category taxonomy (C1-C7) + 15-item mechanical checklist. Paradigm-neutral. Drives acceptance-designer reviewer verdict deterministically.
nWave-ai / nw-bdd-requirementsBDD requirements discovery methodology - Example Mapping, Three Amigos, conversational patterns, Given-When-Then translation, and collaborative specification
nWave-ai / nw-rigorSelects a quality-vs-token-consumption profile (lean, standard, thorough, exhaustive, custom, inherit) and persists it globally (~/.nwave/global-config.json) or per-project (.nwave/des-config.json)
nWave-ai / nw-tdd-methodologyDeep knowledge for Outside-In TDD - double-loop architecture, ATDD integration, port-to-port testing, walking skeletons, and test doubles policy
nWave-ai / nw-tdd-review-enforcementTest design mandate enforcement, test budget validation, TDD phase validation (3-phase canon per ADR-025), and external validity checks for the software crafter reviewer
nWave-ai / nw-test-design-mandatesDesign mandates for acceptance tests - hexagonal boundary, business language abstraction, user journey completeness, pure function extraction, 3 Pillars (domain language / chained narrative / production composition), and the layered ATD discipline (Universe-bound assertion, layer-dependent PBT mode,âĻ
nWave-ai / nw-test-optimizationMethodology for minimizing test count while maximizing behavioral coverage - behavior definition, anti-pattern catalog, consolidation patterns, stopping criterion, coverage-preserving validation
nWave-ai / nw-bdd-methodologyBDD patterns for acceptance test design - Given-When-Then structure, scenario writing rules, pytest-bdd implementation, anti-patterns, and living documentation
nWave-ai / nw-cicd-and-deploymentCI/CD pipeline design methodology, deployment strategies, GitHub Actions patterns, and branch/release strategies. Load when designing pipelines or deployment workflows.
nWave-ai / nw-command-design-patternsBest practices for command definition files - size targets, declarative template, anti-patterns, and canonical examples based on research evidence
nWave-ai / nw-ddd-event-modelingEvent Modeling facilitation technique â brainstorm events, identify commands and views, define aggregate boundaries, write Given-When-Then specifications
nWave-ai / nw-divergeGenerates 3-5 divergent design directions through JTBD analysis, competitive research, structured brainstorming, and taste evaluation before convergence
nWave-ai / nw-executeUse when a DELIVER roadmap already exists and you need to dispatch exactly one identified step through its TDD cycle. Use nw-roadmap to create the plan, nw-deliver for the whole wave, and nw-continue to resume at the next inferred step.
nWave-ai / nw-finalizeArchives a completed feature to docs/evolution/, migrates lasting artifacts to permanent directories, and cleans up the temporary workspace. Use after all implementation steps pass and mutation testing completes.
nWave-ai / nw-jtbd-bdd-integrationTranslating JTBD analysis to BDD scenarios - job story to Given-When-Then patterns, forces-based test discovery, job-map-based test discovery, and property-shaped criteria
nWave-ai / nw-jtbd-coreCore JTBD theory and job story format - job dimensions, job story template, job stories vs user stories, 8-step universal job map, outcome statements, and forces of progress
nWave-ai / nw-jtbd-workflow-selectionJTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes
nWave-ai / nw-roadmap-designRoadmap concision rules, step decomposition efficiency, AC abstraction guidelines, and step-to-scenario mapping. Load when creating implementation roadmaps.
nWave-ai / nw-speculative-dispatchSpeculative parallel implementation methodology â dispatch N candidate implementations, audit all, score, pick best. Auditability mandate: ALL candidates logged (not just winner).
nWave-ai / nw-spikeRuns a timeboxed PROBE to validate one core assumption, then optionally PROMOTES the probe into a walking skeleton â the first e2e thin slice of the feature, committed and demo-able. Use after DISCUSS when the feature involves a new mechanism, performance requirement, or external integration.
nWave-ai / nw-tdd-cross-languagePort the state-delta + property-based testing paradigm to languages other than Python. DIY recipes per language; canonical Python ref shipped in nwave_ai.state_delta.
nWave-ai / nw-test-organization-conventionsTest directory structure patterns by architecture style, language conventions, naming rules, and fixture placement. Decision tree for selecting test organization strategy.
nWave-ai / nw-user-story-mappingUser story mapping for backlog management and outcome-based prioritization. Load during Phase 2.5 (User Story Mapping) to produce story-map.md and prioritization.md.
