Jobs your agent can run

Finds high-value SEO and GEO keywords using web search, AI analysis, and optionally paid tools like Ahrefs or Semrush. Produces a validated keywords.csv file with a fixed schema for downstream pipeline consumption.

Writes product-led content pages optimized for both search engines and AI engine citations. Produces markdown files with frontmatter, following page-type frameworks (comparison, guide, use case, learn, trust) with verified sources and no fabricated data.

Trace the five growth loop types — viral, usage, collaboration, user-generated, referral — against what your product actually does today, measure the ones that exist, and say plainly when none does. Use when designing a growth mechanism, trying to reduce paid dependence, or asking why growth stops the moment ad spend stops.

Score the seven acquisition motions — inbound, outbound, paid, community, partners, ABM, PLG — against the team you actually have, recommend a stack of two to four, and name what to stop doing to pay for them. Use when choosing marketing channels, arguing about inbound versus outbound, or when six channels are all running at half strength.

Build a sales-ready battlecard against one named competitor from their live pricing page, docs, changelog and review sites, with a URL and a read date on every row. Use when a deal has gone competitive, when sales asks "what do I say about <competitor>?", or when an existing battlecard has gone stale and nobody trusts it.

Pick the first segment to attack, scored against burning pain, willingness to pay, winnable share and referral potential — with a cited source behind every score and unsourced scores marked as guesses. Use when choosing a first market, deciding where to focus limited resources, or arguing about which segment to go after next.

Read where an account is heading from recent conversations, backed by an engagement timeline and a research snapshot, with every claim tied to evidence. Use when preparing for a renewal, a QBR, or a check-in on a strategic account, or when someone asks whether an account is at risk.

Build and prioritize a B2B organic pipeline program — ICP-to-keyword mapping, technical SEO, comparison and alternative pages, content built for E-E-A-T and AI citation, link building, and CRM-attributed measurement — grounded in the GSC, Ahrefs and CRM data you actually pull, not assumed. Use when building or auditing a B2B SEO program, deciding which pages to build first for a sales-led or PLG motion, or asking why traffic isn't turning into pipeline.

Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.

Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.

Creates data visualizations (charts, graphs, tables) optimized for AI engine parsing and citation. Produces inline SVG/HTML with text summaries, data tables, and JSON-LD so AI engines can quote the data.

Finds free backlink and brand mention opportunities across Hacker News, Quora, GitHub, directories, and niche communities. Outputs a prioritized action plan with draft responses ready to post. Use after brand research and content creation to amplify reach and AI engine citations.

Audits a live website for AI-engine discoverability (AEO/GEO). Crawls the site, runs 16 deterministic checks plus a 6-dimension content evaluation, and produces a scored report (A-F) with prioritized fixes. Use to get a baseline before improve-aeo-geo, or to measure progress after changes.

Verifies truthfulness, accuracy, and link integrity of content before publishing. Catches fabricated statistics, dead URLs, misattributed sources, and company claims that contradict the brand DNA.

Build a personal language model from someone's own writing samples, then draft, edit, and check writing in that exact voice with no AI slop. The profile learns from every correction. Use when the user shares writing samples to learn their style, asks for something written "like me" or "in my voice", says a draft doesn't sound like them, wants a post, email, essay, or copy in their own voice, or wants to set up, inspect, or update a voice profile. Sits on top of no-ai-slop.

Researches a company from its URL and produces a Brand DNA file covering positioning, audience, competitors, voice, and messaging. Use when starting work with a new brand or customer.

Researches Reddit using a brand's Brand DNA to find promotable pain-point discussions, target subreddits, and real user search language. Produces a prioritized Reddit opportunity list for content seeding, helpful replies, and prompt research inspiration.

Audits a website codebase and makes code changes so AI engines (ChatGPT, Claude, Perplexity, Google AI Overviews) can better discover, parse, quote, and cite the site. Covers structured data, content structure, technical signals, and freshness.

Takes existing content markdown files and builds production-final resource center pages on client websites using their existing tech stack and design system. Output is live-ready — no review pass, no placeholder content, no prototype styling. Implements hub pages, section listings, article pages, and cross-linking for Blog, Guides, Learn, and Comparisons sections.

Use when the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before building or running the workflow; or build custom language/messaging from buyer, competitor, community, and CRM evidence. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.

Resolve LinkedIn profile URLs from name + company with strict identity validation to avoid false positives.

Run a quick Deepline demo recipe to show the user how Deepline works.

Use this skill when a human needs to review a Deepline Play result and hand feedback, labels, or approval back to the agent for revision, evaluation, comparison, or bounded iteration. Triggers on “put this run in a Sheet,” “review these results,” “read my feedback,” “make this a standing rule,” “never regress on this case,” “compare these runs,” “keep improving,” or “add the revised run to the same spreadsheet.” Skip ordinary Play authoring or execution with no human review loop, generic spreadsheet work, and one-off CSV export.

Use for Deepline GTM work that searches, enriches, scores, collects signals, or automates a workflow: find companies or people, enrich a CSV, find emails or LinkedIn, compare providers, build a waterfall, create a webhook or cron, or write a Play. For live information work, run a small heterogeneous experiment, exploit the observed winner, and reopen misses. Skip pure copywriting and non-GTM research.

ACCESS-GATED beta. Deepline Monitors are provider event feeds (job posts, email replies, funding, intent) that stream into your warehouse and trigger plays. Only use if you have monitor access: run `deepline monitors status` first; if it reports no access, do NOT use this recipe — tell the user to contact the Deepline team.

GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,browserbase,builtwith,clay,clickhouse,cloudflare,contactout,contextdev,crustdata-v3,customer_db,databricks,dataforseo,datagma,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,generic_http,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,linkedin_scraper,lusha,meta_audiences,nooks,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,podscan,postgres,predictleads,prospeo,quickenrich,redshift,rocketreach,salesforce,salesforge,salesloft,scrapecreators,searchbug,sec_edgar,sentrion,serper,slack,smartlead,snowflake,socrata,sumble,….

Send feedback or bug reports to the Deepline team. Use when the user asks to report feedback or share a session, and proactively when a Deepline Play is disproportionately slow, appears stuck, or an ordinary outcome requires avoidable product steps.

Build, publish, and verify a Deepline Play as a durable state machine over Customer DB tables, including a small paid pilot. Invoke this skill explicitly when the user asks to build an engine.

Use this skill when answering business analytics, RevOps, GTM metric, pipeline, revenue, funnel, customer, or warehouse questions with Deepline. Triggers on phrases like 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', or any use of snowflake_get_semantic_layer / snowflake_run_semantic_query. Skip prospecting, enrichment, contact finding, outbound, or personalization workflows; use deepline-gtm for those.

Use this skill when building, enriching, auditing, or uploading B2B paid ads audiences to Google Customer Match, Meta/Facebook Custom Audiences, or LinkedIn Matched Audiences. Triggers on phrases like '/deepline-ads-audience', '/deepline-ads-audiences', 'upload this audience', 'create custom audiences', 'personal email hashes', 'increase Facebook match rate', 'Google ads audience', 'Meta audience', 'FB audience', or any workflow that turns CRM/customer/contact data into paid ads upload lists. Skip for outbound prospecting sequences, cold email, or pure campaign copywriting.

Convert a Clay table configuration into local Deepline scripts. Handles extraction (MCP or script), documentation, action mapping, script generation, and parity validation against Clay ground truth.

Build a Total Addressable Market list by sourcing accounts and contacts from providers like Crustdata, Dropleads, and PDL.

Find companies backed by a specific investor or accelerator, then find contacts and build personalized outbound.

Discover niche first-party signals that differentiate Closed Won vs Closed Lost accounts for ICP analysis. Use when the user provides won/lost customer domain lists and wants differential signals (website content, job listings, tech stack, maturity markers) to build account scoring models and prospecting criteria. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals. Before reading this file, first read deepline-gtm to understand the Deepline CLI tool and how to use it. Then read this file for guidance on the task.

Turn an ICP, a beachhead and a motion mix into a dated launch plan — messaging, channels, owners, and metrics each named with the tool that reports them. Use when planning a product or feature launch, opening a new segment, or converting a GTM strategy into something with dates on it.

Use when finding real role-holders at known company domains from an ICP, especially prompts like 'find all job titles at these companies', 'find qualified titles', 'find RevOps or marketing-ops buyers', or when exact title discovery should precede paid people search.

Build an ICP from the customers you already have — segmented by retention and expansion first, then profiled for what the best decile has in common — with firmographics, jobs to be done, pains, and explicit disqualification criteria. Use when defining or refreshing an ICP, when sales and marketing disagree about who to target, or when someone asks "who are our best customers, really?