due-diligence

Researches meeting attendees and their companies before any meeting using real-time web data. Surfaces roles, recent activity, company context, and talking points — then maps cross-attendee relationships. Use this skill when the user asks to prepare for a meeting, research someone they're meeting, or wants context on attendees. Common triggers: "prepare me for my meeting", "who am I meeting with", "research this person", "meeting prep", "brief me on [person]", "I have a meeting with [person/company]", "get me ready for my call", "what should I know about [person]", "background on [person] before our meeting", "attendee research". Requires the Nimble CLI (nimble search, nimble extract) for live web data. Do NOT use for multi-company competitor monitoring (use competitor-intel) or single-company deep dives without attendees (use company-deep-dive).

Validates practitioner credentials and license status against the NPI registry. Cross-references specialties, credentials, and practice addresses against official records. Returns Verified / Partially Verified / Unverified / Flagged per practitioner with mismatch details and source URLs. Triggers: "verify these doctors", "check provider credentials", "validate licenses", "verify NPI numbers", "cross-check credentials against NPI", "compliance audit on providers", "are these practitioners still licensed", "validate my provider list". Accepts CSV, Google Sheet URL, or pasted data. Do NOT use for extracting providers from practice URLs — use healthcare-providers-extract instead. Do NOT use for filling data gaps — use healthcare-providers-enrich instead. Do NOT use for discovering practices — use market-finder or local-places instead. Do NOT use for general extraction — use nimble-web-expert instead.

Runs a sourced KYC / AML research screen on a company: registration, officers, beneficial owners, sanctions, PEPs and adverse media, with namesakes excluded and a risk rating, using the Nimble `kyc-screening` agent template on live web data. Use when the user says "KYC on", "KYB", "AML screen", "sanctions check", "beneficial owners of", "screen this company", "onboarding check", or arrives from a Nimble use-case page. Interviews the user for the inputs, shows quick search results first, then runs the template at medium and high effort and shows each result as it arrives. Do NOT use for a credit view (use credit-risk). Not a certified compliance check.

Monitors press, social, developer communities, and competitor channels from any point around a product launch — tracking sentiment, flagging mischaracterizations, surfacing competitor responses, and recommending actions in real time. Covers press, Reddit, LinkedIn, JavaScript-heavy pages, and live community forums, triaging every signal by urgency. Delivers a Response War Room dashboard with a live signal feed, mischaracterization tracker, competitor response panel, and sentiment velocity chart. Use when asked to "monitor this launch", "track the launch", "what's being said about the launch", "flag any mischaracterizations", "competitor response to the launch", "post-launch coverage", "check press coverage for the launch", or "what's the reaction to the announcement". Do NOT use for ongoing brand monitoring unrelated to a launch — use brand-mention-monitor instead. Do NOT use for ongoing competitor intelligence unrelated to a specific launch window — use competitor-intel instead.

Discovers, enriches, and scores local businesses in any neighborhood using Nimble Web Search Agents (WSAs) and web data. Returns a structured, ranked list with confidence scores, reviews, social presence, and an interactive map. Use this skill when the user asks about local businesses, places, or neighborhood discovery. Common triggers: "find all coffee shops in", "map every bar in", "local businesses in", "discover gyms near", "what restaurants are in", "neighborhood guide for", "local places in", "find places near", "list all [business type] in [area]", "best [type] near [location]", "build a neighborhood guide", "local place search". Requires the Nimble CLI (nimble extract:templates run, nimble search, nimble extract) for live web data via WSAs and fallback search. Do NOT use for competitor analysis or monitoring (use competitor-intel), company research or deep dives (use company-deep-dive), general web search or extraction (use nimble-web-expert).

Discovers all businesses of a given type in any geography using Nimble WSAs. Two modes: Discovery finds businesses from scratch; Audit compares a user's existing list (Google Sheet, CSV, inline) against fresh discovery, categorizing entries as matched, discovered-only, or reference-only. Vertical presets (Healthcare, SaaS, Restaurants, Legal, Auto/Home) auto-select WSA routing. Triggers: "find all X in Y", "build a list of", "market sizing", "account universe", "how many X in Y", "TAM for", "discover all", "audit my list", "compare against", "what am I missing", "gap analysis", "verify my business list", "prospect list". Do NOT use for competitor monitoring — use competitor-intel instead. Do NOT use for company deep dives — use company-deep-dive instead. Do NOT use for neighborhood-level exploration with social enrichment — use local-places instead.

Lists material events at a holding since a date: exec changes, litigation, rating actions, guidance and defaults, with why each one matters, using the Nimble `portfolio-monitoring` agent template on live web data. Use when the user says "what happened at [holding]", "monitor my portfolio", "material events", "check my holdings since", "portfolio news", or arrives from a Nimble use-case page. Interviews the user for the inputs, shows quick search results first, then runs the template at medium and high effort and shows each result as it arrives. Do NOT use for sales accounts (use account-signals) or a full credit view (use credit-risk).

Finds qualified candidates for a role by searching LinkedIn, Indeed, GitHub, and other professional platforms using Nimble Web Search Agents. Accepts a job description, role title, or freeform request and returns a ranked candidate list with profiles, skills, and contact signals. Use this skill when the user wants to find, source, or recruit candidates for a role. Common triggers: "find candidates for", "source engineers in", "who can I hire for", "find me a [role]", "recruiting for", "talent search", "find a [role] in [city]", "build a candidate list", "sourcing for [role]", "who's available for", "find potential hires". Also triggers on a pasted job description followed by a sourcing request. Do NOT use for job market research or salary benchmarking — use market-finder instead. Do NOT use for researching a single known person — use company-deep-dive or meeting-prep instead.

Rigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, fair comparison, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-only or run-only exploration, passive repo analysis, verified novelty claims, or implicit experimentation.

Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, score chasing, or broad research assistance outside repository-grounded reproduction.

Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized `train_outputs/`. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.

Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.

Search, scrape, crawl, extract structured data, and monitor web pages via the ScrapeGraph AI CLI. Use when the user asks to search the web, scrape a webpage, grab content from a URL, extract JSON from a site, crawl documentation or site sections, monitor a page for changes, inspect request history, check ScrapeGraph credits, or validate API setup.

When the user wants to create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'battle card,' 'battlecard,' 'competitive one-pager,' 'win-loss analysis,' 'why are we losing deals,' 'loss reasons,' 'how do I respond to this objection,' 'prospect just said,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps,' 'cold call script,' or 'voicemail script.' Use this for any document or asset that helps a sales team close deals. For public competitor comparison pages, see competitors. For running buyer interviews or churn research, see customer-research. For marketing website copy, see copywriting. For cold outreach emails, see cold-email. For the offer being sold (bonuses, guarantees, pricing structure), see offers.

Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research. Use for: research, RAG pipelines, fact-checking, content aggregation, agents. Triggers: web search, tavily, exa, search api, content extraction, research, internet search, ai search, search assistant, web scraping, rag, perplexity alternative

When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.