Loading...
Loading...
Found 261 Skills
When the user wants to set up ongoing tracking of competitor activity — pricing changes, feature launches, hiring signals, content, or public mentions. Also use when the user mentions "track competitors", "what are competitors doing", "competitor alerts", or "market watch".
When the user wants to reverse engineer how another company grew and copy what worked. Also use when the user mentions 'reverse engineer,' 'how did X grow,' 'how does X get customers,' 'growth teardown,' 'marketing teardown,' 'GTM teardown,' 'growth blueprint,' 'what is X doing for marketing,' 'what made X take off,' 'copy X's playbook,' 'X's distribution strategy,' 'what content works for X,' 'funnel hack,' 'map their funnel,' or 'watch what X is doing.' Builds a dated log of a company's moves against its traffic curve from public data, sign-ups and demos, team interviews, and hidden signals (DNS, certificate logs, archives, sponsorships), compares it with the user's own data, and turns what lined up with growth into plays routed to the skill that runs each one. For a snapshot profile of a competitor's positioning, pricing, and features, see competitor-profiling. For comparison pages, see competitors. For why a single post went viral, see social.
An 18-agent pipeline that turns one topic line into a drafted research paper, literature review, or thesis chapter. Finds real sources at Crossref and OpenAlex, drafts each section against them, attacks its own draft for weak claims, then compiles citations deterministically so in-text markers map one to one onto the bibliography and every printed DOI resolved at Crossref or DataCite. Every agent is a markdown file you can open and edit. Pure stdlib, no API key, no account. Use when someone asks to write a research paper, do a literature review, draft a thesis chapter, find sources on a topic and write them up, or names opendraft or openpaper.
Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic alliance review — not technical sale enablement, not channel cost economics, not M&A.
This skill should be used when the user says phrases like "record a topic", "new topic", "how is this topic", "I have an idea", "help me note this down", or shares a rough content idea that needs evaluation and recording. Even if the user casually mentions a content idea, actively trigger the evaluation process without waiting for the user to explicitly say "record". First, use the five-dimensional logic of dbs-content to diagnose whether the topic is worth doing. Only record it if it is worth doing, and recommend 3-5 similar topics by drawing inferences. Do not trigger: Deepen the topic to generate an outline (use li-topic), directly write scripts (use li-writer), or AI polish or beautify the topic title. Use when the user wants to "record a topic", "log a topic idea", "is this topic worth doing", or shares a rough contentclaise Du.弹应用样子Pr广解除禁 \ 诊断和记录.
Break down benchmark accounts / competitor content—drop in a link, and the Skill automatically identifies the platform (Douyin/Xiaohongshu/Bilibili/YouTube/WeChat Official Accounts) and granularity (a single post or an entire account), fetches the content, and outputs a three-part deliverable: a reusable viral-content formula, a segment-by-segment breakdown of the visuals and voiceover, and the account’s persona and content positioning, while automatically archiving the result to benchmarks/. Short videos are automatically downloaded, their voiceovers transcribed, and visual frames extracted (multimodal image reading via a contact sheet), rather than analyzing captions alone. Use this when the user says “tear down this account/video/post,” “analyze a benchmark/competitor,” “why did this go viral,” “break down the content behind this link,” “teardown,” or “see how others are doing it.” If the content cannot be fetched, guide the user to paste the copy/subtitles; never fail with an error directly.
Searches scholarly literature with zero API keys across DBLP, Crossref, Semantic Scholar, and arXiv. Use when the user wants to find papers, search the literature, list a conference's proceedings (e.g. "all SIGSPATIAL 2025 papers"), survey related work on a topic, look up papers by author/venue/year, get DOIs or citation counts, or check recent arXiv preprints. Ships a venue-alias table that solves cross-API venue naming (DBLP "conf/gis" vs Semantic Scholar "SIGSPATIAL/GIS" vs Crossref proceedings titles) plus polite, cached, 429-resilient search scripts. Trigger words - find papers, literature search, related work, proceedings, DBLP, Crossref, Semantic Scholar, arXiv, citation count, DOI lookup, venue search.
Use when a creative task has no direction yet: finding inspiration, exploring looks or styles, proposing concept directions to pick between, building a moodboard or reference board, doing visual research, mining existing assets for a style, or escaping generic AI-looking output. Also when a saved Scenario collection should drive a new batch as art direction. Keywords: inspiration, moodboard, references, art direction, style exploration, concepts, serendipity, ideation, surprise me.
Leader's prep on a single rep before a 1:1 - their pipeline, recent activity, what they've been working on per chat and calendar, and where they might need help. Use when the user asks "prep for my 1:1 with [rep]" (a rep you manage), "how is [rep] doing", or "what's [rep] working on".
Start-Stop-Continue retrospective identifying what to Start doing, Stop doing, and Continue doing. Use for sprint retros, personal reflection, team process reviews, or habit audits.
Audit your biggest closed-won deals to find your PROVEN ideal customer profile, then find more accounts like them. Use whenever someone wants to analyze won deals, audit their best customers, see which companies generated the most revenue, find their real ICP, build a look-alike target list, segment customers by what actually pays, or learn which acquisition channel produced their best revenue. Triggers on: 'audit my biggest deals', 'which customers made us the most money', 'analyze my closed-won', 'what's my proven ICP', 'find more customers like my best ones', 'look-alike accounts', 'HubSpot deal analysis', 'revenue by account', 'which channel generated my best deals', 'acquisition source analysis'. For RevOps, Heads of Sales/Marketing, founders and growth leads doing ICP refinement, account-based targeting or pipeline/QBR review. Reads HubSpot via its MCP or a CSV export, then hands the profile to sales-nav-search-builder to generate the prospecting search. Maintained by La Growth Machine.
This skill is activated when users are preparing to apply a successful methodology (from others or their own past experience) to a new scenario. Typical trigger signals: "Company X succeeded with method X, we should try it too" "This worked for me before, let's keep doing it" "The industry best practice is Y". Scenarios where it should not be invoked: Users are facing repeated occurrences of the same type of problem and need execution rather than methodology selection. Difference from "Contradiction Analysis Method": This skill emphasizes "different problems require different methods due to their distinct natures", while the latter focuses on "identifying the most important problem".