Marketing Foundation
Compact two-skill starter: clarify positioning and choose a lead magnet. Use Marketing Launch for the broader eight-skill go-to-market workflow.
Useful AI skills from strong open sources, cleaned up for discovery, task fit and direct use.
Coordinates multi-agent work with clear owners, work items, evidence, and merge gates.
Audits Claude Code context overhead and recommends ways to reduce unnecessary loaded content.
Diagnoses agent-system failures across prompts, memory, tools, wrappers, and output delivery.
Searches local and external skill sources for existing matches before a new skill is created.
Plans lead magnets around audience needs, buyer stage, capture approach, distribution, and measurement.
Turn existing customer evidence into a target-customer profile and segment criteria. Use customer-research-synthesis to collect evidence or customer-feedback-analysis to analyze a feedback dataset.
Turn a chosen audience and acquisition approach into a launch plan with channels, messages and milestones. Use go-to-market-motions when the acquisition model is still undecided.
Generate and compare five campaign concepts before choosing one. Use marketing-campaign-planning to organize execution of the selected idea.
Evaluates product-led growth loops and outlines measurable experiments for sharing, collaboration and referrals.
Choose for strategic comparison and differentiation from competitor evidence. Use competitor-research-profiles to first build detailed URL-based dossiers.
Defines one customer-value metric and supporting input metrics with clear measurement assumptions.
Develops differentiated product positioning ideas with audience fit, rationale, and supporting messages.
Draft and compare product vision statements grounded in company values and customer needs.
Choose an acquisition or sales motion suited to your economics and buying process. Use go-to-market-strategy to turn that choice into a launch plan.
Analyze an existing feedback dataset for themes, sentiment and improvement priorities. Use customer-research-synthesis to design new research and ideal-customer-profile to define the target customer.
Map external political, economic, social, technological, legal and environmental factors for a business decision.
Map customer touchpoints and friction from awareness through advocacy.
Compare growth options across existing and new products and markets.
Review methodology, calculations and conclusions before sharing an analysis.
Profile a dataset and identify quality issues and useful follow-up analyses.
Choose descriptive statistics and hypothesis tests while making assumptions and uncertainty explicit.
Plan useful SEO pages at scale with a data strategy, templates and twelve complete playbooks.
Review marketing pages and forms, prioritize friction fixes and design measurable experiments.
Plan transparent in-product upgrade prompts and experiments after users experience value.
Review account creation and trial signup friction while preserving necessary security and consent controls.
Plan the first useful product experience, activation milestones and measurable onboarding experiments.
Design dismissible, accessible conversion overlays with honest offers and measurable frequency rules.
Write full email drafts, subject variants and a branching flow diagram. Choose Lifecycle Email Sequences for broader lifecycle planning with ten supporting references and provider guides.
Turn a selected campaign concept into a brief, calendar, dependencies and measurement plan. Use marketing-campaign-ideas when you still need concepts.
Draft channel-specific marketing content using clear structures, evidence and calls to action.
Review drafts against supplied brand guidance and propose specific, prioritized revisions.
Turn supplied campaign or channel metrics into a traceable report with comparisons and testable recommendations.
Research one company or partner for a sourced B2B sales brief and outreach hypothesis. Use company-contact-enrichment to fill fields across lead or contact records.
Resolve and enrich B2B lead, company and contact records with field-level evidence. Use sales-company-research for a narrative account brief and outreach hypothesis.
Plan page hierarchy, navigation, stable URL patterns and useful internal links for a website.
Prioritize content pillars, audience questions and distribution plans using evidence and available resources.
Plan a scoped product or feature launch across preparation, release and post-launch adoption.
Design customer research or combine interviews, surveys and public evidence into needs and personas. Use customer-feedback-analysis for a supplied feedback dataset; ideal-customer-profile for ICP definition.
Plan a community around member value, participation and measurable business goals.
Choose to collect dated competitor dossiers from URLs, pricing pages and SEO evidence. Use competitor-analysis for the strategic comparison afterward.
Turn approved roadmap and release facts into audience-specific updates, release notes and changelogs.
Plan coordinated welcome, nurture and retention journeys with ten supporting references, including provider guides. Choose Email Sequence Copy and Flow for a focused copy-and-flow drafting workflow.
Define API contracts, pagination, error semantics and safe retry behavior; choose this for interface design, then Observability for evidence of runtime behavior.
Plan logs, metrics, traces and actionable runbooks for an existing service; use API Contracts first when the missing piece is interface behavior rather than runtime evidence.
Prepare project context, rules and restartable session handoffs; choose this for organizing context, and AI Context Window Audit for diagnosing existing overhead.
Turn customer evidence into prioritized assumptions, experiments and proceed/pivot/stop decisions. Choose Customer Research and Synthesis when the evidence itself still needs synthesis.
Design a deal-inspection scorecard with evidence, thresholds and override rules.
Design provider order, fallback paths and cost limits for an enrichment workflow. Use Company and Contact Enrichment for a specific research request.
Turn observed churn signals into owner-assigned retention plays and measurement plans.
Turn an identified sales coaching gap into short practice drills and follow-up criteria. Use Sales Coaching Competencies to define the rubric first.
Define comparable revenue cohorts, metrics and diagnostic views. Use Statistical Analysis Guidance for inference methods.
Design a transparent account-intent score with decay, tiers and review rules.
Specify accountable matching and conflict-resolution rules across customer data sources.
Map existing customer segments to cross-team actions, owners and measurable outcomes. Use User Onboarding and Activation for the individual first-value journey.
Review an authorized sales-call transcript with an observable rubric and evidence-linked coaching actions.
Specify retention metrics, cohort views and alert logic for a BI dashboard. Use Customer Retention Playbook for the intervention plan.
Define observable sales competencies and calibrated coaching rubrics. Use Sales Coaching Practice for follow-up exercises.
Compare done-for-you, guided and self-service delivery for an existing offer. Use Service Productization for repeatable packages and tiers.
Improve how an existing offer communicates its value through naming, structure and evidence-backed comparisons. Use Product Positioning for market differentiation.
Turn repeatable service work into defined packages, an offer ladder and optional upgrade paths. Use Offer Delivery Design when only the fulfillment format is undecided.
Turn observed page/funnel friction into an evidence-ranked experiment backlog. Use Landing Page Conversion Review for a focused page critique.
Original Braze Canvas, segmentation and lifecycle guidance with declared reference limitations.
Create voice attributes, a tone matrix and channel guidance. Use Brand Voice Content Review to check an existing draft against established rules.
Original workflow for chaining research, editorial review and social-pack agents.
Original website-to-brand-profile workflow; extracted observations must stay separate from inferred brand rules.
Map expressed buyer concerns to factual answers, supporting evidence and improvements to the offer.
Original Klaviyo developer guide; SDK scripts, API contracts and version claims are not functionally verified.
Design relevant offer extras that address concrete customer needs and disclose their actual conditions.
Original Klaviyo marketing review workflow with explicit data-access and dependency warnings.
Original multi-platform ad-audit orchestration; required platform packages and scoring files are not included.
Compare ways to monetize expertise against demand, capacity and goals. Use Service Productization to package a service already chosen.
Original LinkedIn advertising guide with explicit warnings for obsolete audience features and unverified benchmarks.
Original TikTok campaign, creative and measurement guide; platform details and benchmarks are unverified.
Synthesize topic sources into a cited brief with evidence, uncertainty and content angles. Use Customer Research and Synthesis for interviews and customer feedback.
Write timed cinematic video prompts with motion, camera and continuity cues.
Adapt a visual brief to model-specific syntax while flagging unknown capabilities.
Diagnose a failed image/video result and propose controlled prompt revisions.
Develop a short-film idea into a logline, treatment, scene list and revision plan.
Write cinematic still-image prompts with composition, lighting and identity anchors.
Track recurring characters, locations, props and changing scene state.
Write or revise filmable scenes, dialogue, beats and Fountain-style excerpts.
Translate a scene into shots, camera setups, assets and continuity notes.
Translate tone and genre into reusable camera, lighting and visual-style rules.
Use product/business data to frame a decision with evidence and tradeoffs. Use Metric Change Diagnostics to explain a movement first.
Define KPI formulas, targets, drivers and guardrails. Use North Star Metric for the narrower primary-value metric choice.
Investigate metric movements or discrepancies before choosing a business response.
Original workflow for marketing prompt evaluation, version history and governance.
Plan personas, journeys and usability research. Use Customer Research and Synthesis for evidence synthesis alone.
Original A/B testing and experimentation workflow with explicit statistical corrections.
Original schema.org implementation guidance with rich-result freshness limitations.
Original pricing, tiers and willingness-to-pay workflow. Use Expertise Business Model for the overall monetization structure.
Plan referral incentives, affiliate terms and measurement from the original framework.
Original multi-property Search Console comparison workflow with coverage caveats.
Original keyword-difficulty scoring workflow using competitor metrics and observed AI citations.
Plan discoverability and citations in AI search. Use Search Console Portfolio Review for measured property comparisons.
Review technical and on-page SEO issues using the original audit workflow.
Analyze industry rivalry, entry, substitutes and buyer/supplier bargaining power. Use Competitor Analysis for individual competitor comparisons.
Select a focused initial market segment before expanding. Use GTM Motion Selection for the selling model.
Extract reusable warehouse schema, dialect and business context for later analysis.
Plan ad variants, review criteria and production handoffs from the original workflow.
Plan employee change communications, sequencing and feedback loops.
Map process stages, queues and candidate bottlenecks from operational evidence.
Frame capacity, queueing and staffing scenarios with declared assumptions.
Review spend, renewals and supplier consolidation opportunities.
Identify candidate topic and keyword gaps between comparable websites.
Use the original Semrush workflow to frame competitive search research.
Use the original Ahrefs workflow for backlinks, keywords and competitor research.
Research keyword opportunities, intent and candidate content priorities.
Ground implementation decisions in resolved dependency versions and source documentation.
Plan browser debugging and test observations using a separately available DevTools MCP.
Frame application threats and defensive hardening work from the original checklist.
Plan enterprise project portfolios, risk registers and resource discussions.
Review a marketing page by value proposition, CTA, trust and friction. Use Conversion Hypothesis Prioritization for selecting among experiments.
Structure a SaaS health report from revenue, churn and acquisition inputs.
Frame acquisition rationale, diligence, negotiation questions and integration.
Frame data architecture, training-data rights, asset value and hiring decisions.
Compare foreign markets, entry modes, localization and operating requirements. Use Beachhead Market Selection for choosing an initial narrow segment.
Frame sprint forecasts, retrospective actions and team-health discussions.
Plan B2B SaaS acquisition channels, funnel handoffs and measurement. Use Cross-Platform Advertising Review for comparing existing channel results.
Review account-creation steps, field friction and post-submit experience. Use User Onboarding Activation for activation after registration.
Structure a board or investor narrative around metrics, variance and decisions.
Review service-area business profiles, location content, NAP and local schema.
Frame a security program, risk register, incident coordination and board reporting. Use Application Hardening Guidance for application-level defenses.
Assess task difficulty and execution quality using a two-axis rubric.
Choose a pricing model, willingness-to-pay range and packaging tiers. Use Pricing and Packaging Guidance for the broader marketing workflow.
Audit content structure and citation signals. Use AI Search Visibility Planning for broader visibility strategy.
Build pipeline, bookings and cohort revenue scenarios with explicit assumptions.
Translate company values into observable behavior, rituals and review questions.
Compare fully loaded direct and partner channel economics and allocation scenarios.
Structure independent executive perspectives, critique and human decision review.
Review cross-functional organizational health and identify follow-up questions.
Frame partner tiers, joint go-to-market commitments and revenue-share economics.
Choose among the upstream marketing workflows and coordinate their handoffs.
Review paywalls, feature gates and in-product upgrade moments. Use Marketing Page Conversion Review for public pricing pages.
Plan a useful free calculator, generator or checker as a marketing asset. Use Lead Magnet Strategy for downloadable content.
Route an executive question to appropriate advisor perspectives and synthesize decisions.
Design discount bands, approval thresholds and exception rules. Use Deal Review Routing for applying an existing policy to one deal.
Organize contract, IP and regulatory questions for qualified counsel.
Plan TAM/SAM/SOM estimates, survey sampling and segment evaluation.
Explore interacting business shocks and cross-functional responses.
Review lead, contact or demo forms. Use Registration Flow Review for account creation.
Alternative popup framework from the Alireza collection. Use Popup Modal Planning for the existing M11 workflow with bundled references; this source variant has no reference package.
Organize named human review and structured feedback before a requested sign-off.
Frame model build-versus-buy, AI economics, governance questions and staffing.
Map bid requirements to evidence, gaps and win themes before a bid decision.
Choose research methods and organize evidence into an insight repository. Use UX Research and Journey Design for persona/journey artifacts.
Frame cash, unit economics, fundraising and board financial questions. Use SaaS Metrics Coaching for a focused metric health report.
Apply existing commercial policy to a specific deal and route exceptions to named humans.
Plan independent model critiques of a memo while preserving disagreements.
Manage stored prompt versions and lifecycle in Google Agent Platform, including explicit confirmation before deletion.
Review Google Cloud costs using the Well-Architected Framework; WAF here does not mean a web application firewall.
Analyze BigQuery job and reservation telemetry to compare slot capacity and cost options.
Plan lifecycle operations for stateful managed Agent resources. Use Google Agent Prompt Management for stored prompts only.
Replay historical access against proposed IAM v1 allow policies before a separately approved change.
Design synthetic evaluation datasets, judge-based evaluation and iterative agent improvement on Google Cloud.
Plan Google Data Manager event and conversion ingestion. Use Google Audience Ingestion for audience membership.
Configure GA accounts, properties, streams and integrations. Use Google Analytics Reporting for querying performance data.
Plan adding, removing or replacing Google Customer Match audience members. Use Google Conversion and Event Ingestion for events.
Set up client libraries and authentication for Google Data Manager; audience and event payloads use the dedicated ingestion skills.
Select BigQuery SQL AI/ML capabilities for forecasting, anomaly detection, vectors and generative analysis.
Set up Google Ads API access and a campaign retrieval example; use Google Ads Account Diagnostics once access works.
Inspect Google Agent Platform RAG corpora and retrieve grounded context; not a general database or Workspace RAG workflow.
Design ingress and egress controls using Agent Gateway, Model Armor, IAP and registries.
Gather requirements and design Google Cloud agent deployment instructions. Use Google Cloud Solution Architecture for non-agent systems.
Query Google Analytics reporting data through the Data API. Use Google Analytics Admin Configuration for account/property settings.
Inspect downstream BigQuery lineage before a proposed asset change. Use Google Data Lineage Summary for general lineage orientation.
Design a Google Cloud agentic data-science workflow spanning analysis, models and deployment planning.
Plan Terraform and telemetry-based alerts for agent reliability and supported quality signals.
Design cross-product Google Cloud solutions and review deployment plans; use Multi-Agent Deployment Design for agent-specific systems.
Summarize available BigQuery and GCS lineage; use BigQuery Lineage Impact Analysis for downstream change impact.
Browse and manage Google Agent Platform skill registry revisions; this is separate from the M11 catalog.
Plan model-category-specific tuning, dataset preparation and jobs on Google Agent Platform.
Investigate Google Ads conversion loss, impression share and bid/budget constraints; use API Quickstart for initial access.
Collect competitor ad samples and separate long-running from recently repeated creatives. Use Competitor Ad Intelligence for a cross-brand report.
Check GA4 metric definitions, channel totals, intraday completeness and attribution differences before reporting results.
Plan Google Ads experiments using the GoMarble proposal workflow; use Growth Experiment Design for broader experiment strategy.
Analyze Meta account performance, baselines and active-entity metrics. Use Meta Ads Deep Analysis for the wider audit framework.
Check Google Ads recommendations against valid budget controls, metric choice and source scaling rules.
Coordinate the full GoMarble competitor-to-production-brief workflow. Use the individual collection, diagnosis or brief skills for one step.
Review Meta recommendations against budget controls, conversion type, learning-stage and evidence requirements.
Combine competitor, own-creative and hook evidence into test directions; this synthesizes existing research rather than collecting new data.
Plan GoMarble tool parameters for Search bids, budgets, negatives and query isolation. Use Search Campaign Analysis to diagnose first.
Generate or critique hooks using the source psychological framework; does not require account data or execute ads.
Prepare Meta ad-set targeting, attribution and bids under a verified parent campaign. Use Meta Campaign Planning for campaign-level settings.
Plan updates to existing Meta campaigns, ad sets and ads; use Meta Ads Creation Workflow for new structures.
Plan PMax scaling after maturity and performance evaluation; use Google PMax Evaluation before choosing changes.
Diagnose your own creative patterns using account data, CSV or supplied assets. Use Meta Creative Metrics Analysis for the narrow metric framework.
Apply the source video/image/catalog diagnostic framework to Meta creative metrics; use Own Ad Creative Diagnosis for a broader asset teardown.
Structure a Meta audit across hierarchy, breakdowns, time and attribution; use Meta Account Performance Analysis for account baselines.
Plan paid-search keyword discovery and match-type choices using GoMarble's Keyword Planner workflow; not organic SEO research.
Review Shopping feed health and product-level decisions before campaign changes; not PMax optimization.
Prepare Meta ads with single-image/video or catalog creatives under an existing ad set. Use Ad Brief Production for creator instructions.
Route Google Ads create/update tasks through the GoMarble proposal and approval workflow; use API Quickstart for SDK setup.
Reconcile Shopify order reports with dashboard totals using dates, refunds, currencies and financial-status scope.
Classify Search queries and diagnose CPC, rank and budget pressure; use Search Campaign Change Planning for proposed mutations.
Plan shared Google Ads negative lists and campaign attachments, distinguishing campaign IDs from shared-set link IDs.
Summarize sampled competitor ads into cross-brand patterns and whitespace. Use Competitor Ad Collection for detailed cohort collection.
Organize an eight-dimension GoMarble Google Ads audit; use Google Ads Account Diagnostics for the Google-authored issue workflow.
Prepare Meta campaign objectives, ABO/CBO budgets and special-ad categories. Use Meta Ad Set Planning for targeting and attribution.
Coordinate Meta campaign, ad-set and creative creation with separate approval to enable new ads.
Turn a chosen evidence-backed creative direction into a creator brief, hook, shot list, voiceover and CTA.
Plan device, location and audience bid modifiers using the source mutation workflow; not campaign-budget allocation.
Evaluate PMax maturity, comparative performance and asset labels before scaling. Use Google PMax Scaling Plan after this diagnosis.
Organize creator rates, rights, exclusivity and history through the source registry protocol. Use Influencer Fit Assessment for shortlist scoring.
Maintain dated social-platform format and policy notes, separating official documentation from folklore; not channel selection.
Compare ranking snapshots and SERP-position changes over time. Use SERP Intent and Feature Analysis for a single-query layout review.
Distinguish creative fatigue from audience saturation using frequency and CTR/CVR trends; use Own Ad Creative Diagnosis for individual asset analysis.
Plan brand-mention sweeps, baselines and triage with explicit source coverage. Use Launch Window Monitoring for launch-specific telemetry.
Compare launch outcomes with preregistered channel targets and derive keep/change/stop recommendations.
Turn already approved proof into reusable stat cards, case snippets and testimonials; does not substantiate missing claims.
Assess creator suitability separately from campaign-specific commercial fit. Use Creator Record Governance for factual rates and rights history.
Plan conversion-event, UTM, deduplication and attribution-window checks. Use Conversion Value Mapping for value rather than firing logic.
Build a launch-day runbook with owners, observation windows and rollback criteria; requires the source readiness and date evidence.
Triage comments and DMs and draft ranked human-posted replies, escalation and UGC permission requests.
Review Shopping/PMax product attributes, disapprovals and truthful title improvements. Use Google Shopping Optimization for campaign performance decisions.
Define conversion values, margin adjustments and proxy-value assumptions before value-based bidding. Use Conversion Signal Review to check firing first.
Choose bidding strategy, initial targets and learning-phase plan; use Google Ads Bid Modifier Planning for specific modifier operations.
Draft media tiers, embargo pitches and factual press-release structure; no outreach is sent.
Plan substantive follow-up moments and assess whether an update warrants a relaunch; not paid amplification execution.
Organize canonical entity identity, sameAs and machine-facing facts. Use Narrative Canon Governance for human-facing brand wording.
Plan severity, human pause actions, statements and stand-down evidence. Use Launch Day Runbook for incidents inside an active launch.
Map audience or niche-community context into creator selection criteria; use Influencer Fit Assessment for named shortlist scoring.
Plan recurring engagement-decay and suppression-drift reviews; use Consent Record Governance for authoritative opt-in state.
Analyze a query's intent, result layout and feature opportunities. Use SERP Rank Change Tracking for longitudinal position changes.
Maintain versioned brand narrative, message hierarchy and voice facts; this records the canon rather than inventing positioning.
Plan acquisition channels, incentives and opt-in capture evidence. Use Lead Magnet Strategy for selecting a downloadable asset.
Plan a human-led founder engagement routine and relevant trigger responses; no mass messaging or engagement automation.
Plan launch-window ranking and KPI snapshots with source labels. Use Social Mention Triage for ongoing listening outside launches.
Describe pseudonymous opt-in, suppression and erasure event governance; does not install a registry or change an email platform.
Record authoritative launch dates, stages, embargoes and outcomes through the source event protocol; not readiness scoring.
Organize social-channel ownership, cadence, voice and UGC permission facts; not channel selection or permission inference.
Plan Google Ads creation and reporting through HyperFX. Use Google Ads Creation Workflow for the separate GoMarble connector.
Plan Pinterest campaign structures, targeting and reporting through HyperFX with explicit budget-unit handling.
Plan Amazon Sponsored Products targeting, bids, negatives and reporting through HyperFX.
Plan HyperSEO keyword, site and AI-visibility research; use SERP Intent and Feature Analysis for source-independent query interpretation.
Plan Reddit campaign, ad-group and promoted-post workflows through HyperFX; separate archive status from permanent deletion.
Plan Meta campaigns and reports using HyperFX activation tools. Use Meta Ads Creation Workflow for GoMarble's different approval contract.
Plan multi-surface competitor snapshots and diffs with HyperFX. Use Competitor Research Profiles for a source-independent company profile.
Plan one evidence-backed blog post and a persistent strategy document using HyperFX research and CMS integrations.
Prepare LinkedIn text, document or carousel publishing through HyperFX; use Social Selling Routine for human-led engagement planning.
Plan provider-specific lifecycle email operations across HyperFX integrations; use Email Sequence Copy and Flow for copy planning.
Gather and synthesize customer language through HyperFX sources or supplied research. Use Customer Research Synthesis for the existing bundled research workflow.
Research public Meta ad-library samples and optionally business contact information through HyperFX; use Competitor Ad Collection for GoMarble.
Maintain a shared brand-context document from evidence and interviews; use Narrative Canon Governance for formal versioned brand records.
Plan GA4, GTM, Search Console and BigQuery work through HyperFX; use Google Analytics Reporting for the Google-authored Data API guide.
Plan HyperFX prospect research, draft review and reply routing; this source includes sending tools but M11 only loads guidance.
Load HyperFX's third-party OpenAI Ads workflow description; platform/API availability and claimed tool behavior are unverified.
Plan brand-grounded ad copy and image generation through HyperFX; use Ad Brief Production for creator-facing production instructions.
Plan TikTok campaign parameters, video uploads and reporting through HyperFX.
Plan Snapchat campaign, ad-squad and creative operations through HyperFX with paused creation and separate activation review.
Plan transcript-based summaries, video packaging and thumbnails through HyperFX; no video is downloaded or uploaded by loading this guide.
Analyze SQL data models and performance bottlenecks.
Plan support operations, ticket triage and service workflows.
Plan returns, inspection and reverse-logistics workflows.
Organize customs and trade-compliance questions for qualified review.
Plan market and geographic research using public permitted sources.
Set operating boundaries for AI coding agents and their permissions.
Plan retention, dunning and win-back decision paths.
Organize ethical HR workflows, policies and employee-relations questions.
Plan ActiveCampaign contact, tag and automation work through connected tools.
Frame KPI, dashboard and business-analysis work from available evidence.
Review demand, alternatives and risk signals before building a product.
Plan business-continuity analysis and recovery documentation.
Plan public-source lead research through Apify; this does not authorize outreach.
Design agent-memory concepts and evaluation questions.
Plan demand forecasting, safety stock and replenishment decisions.
Organize quality investigations, corrective actions and supplier follow-up.
Plan tracing, token, latency and cost visibility for AI agents.
Draft and review employment-documentation structure for qualified local review.
Plan bounded scheduled agent runs with stop conditions and oversight.
Organize adverse-media and sanctions research while retaining uncertainty and review status.
Plan evaluation datasets, criteria and regression checks for AI agents.
Organize third-party risk-assessment and review workflows.
Plan Odoo accounting configuration and reconciliation work.
Design cloud architecture options and operational constraints.
Plan IT service-management practices and operational governance.
Plan free-tier boundaries, conversion path and abuse controls.
Plan public-source influencer discovery and evaluation; no outreach is sent.
Synthesize customer research and voice-of-customer evidence.
Plan app-store research, listing improvements and performance monitoring.
Plan recurring billing, invoicing and dunning workflows.
Clarifies customer-centered messaging, a one-liner and calls to action using the StoryBrand narrative structure.
Frames pricing and packaging around validated willingness to pay before product scope is committed.
Explores differentiated market opportunities with value innovation, strategy canvases and non-customer perspectives.
Plans a technology product’s path from early adopters toward a focused mainstream beachhead.
Analyzes product engagement loops using triggers, actions, rewards and investment with an explicit ethics lens.
Plans early network formation and growth for marketplaces, collaboration products and other networked services.
Audits strategy as diagnosis, guiding policy and coherent action rather than goals or slogans.
Selects decision-relevant product metrics, counter-metrics and evidence-based measurement plans.
Defines product positioning through competitive alternatives, differentiated attributes and best-fit customer context.
Designs evidence-aware scorecard and assessment funnels for qualified lead discovery and follow-up planning.
Frames customer progress, switching behavior and unmet needs for research and product decisions.
Structures evidence-based conversion research, friction analysis and test planning for websites and funnels.
Prepares customer interviews that focus on past behavior and evidence instead of leading questions.
Plans role-based B2B outbound sales processes, qualification and pipeline measurement.
Develops evidence-aware offers, value articulation, bonuses and ethical risk reversal for a specific audience.
Designs tenant-model and operating-boundary decisions for subscription SaaS products.
Shapes product work into bounded, evidence-aware bets before delivery resources are committed.
Evaluates AI-enabled workflows through outcomes, quality, full costs, uncertainty and accountable governance.
Builds outcome-based roadmaps and portfolio choices with evidence, dependencies and stop criteria.
Designs AI governance structures, decision rights, risk tiers and lifecycle evidence for qualified review.
Defines product decision rights, evidence standards and recurring cross-functional governance cadences.
Compares evidence-backed current and target states to prioritize bounded capability and readiness interventions.
Turns post-launch evidence into bounded continue, improve, pause, pivot or retirement recommendations.
Guides an embedded technical engagement from discovery through adoption and measured outcomes.
Use when deciding whether a process is worth automating, sizing ROI and build-vs-buy, choosing an automation platform, or diagnosing why a fleet of automations keeps breaking — the decision layer before anyone builds. NOT building the flow (that is `automation-flows`, or `n8n` / `make` / `zapier` / `power-automate` to drive a live platform).
Use when building or fixing a no-code automation on n8n, Make, or Zapier — trigger to multi-app steps with data mapping, dedup, retries and an error path — or picking the platform by billing unit (task vs credit vs execution). NOT a typed API client in code (that is api-connector-builder), NOT a webhook receiver in your own app (that is webhooks).
Use when a role is open and you must write the job post, screen inbound candidates, structure the interview loop, or score them to a defensible Hire / On-Hold / No-Hire — including whether an AI résumé filter is legal. NOT after the offer is accepted — onboarding, payroll, performance (that is `people-ops`), NOT offer terms (that is `contracts`).
Use when choosing an embedding model, chunk size, or query form, when semantic search returns irrelevant results, when adding hybrid BM25+vector or a reranker, or when a retrieval change needs a number (recall@k, nDCG, MRR). NOT operating the store — index tuning, quantization (that is `vector-db`) — nor the retrieve-to-answer loop (that is `rag`).
Use when building grounded Q&A over your own corpus — chunk, retrieve hybrid, rerank, ground, cite chunk ids, refuse when the sources fall short — or when the right document is retrieved but the answer is still wrong, invented, or unmeasured. NOT operating the store itself — collection schema, HNSW ef_search, quantization (that is `vector-db`).
Use when an operator runs deals out of a spreadsheet or Notion and wants real stages, win probabilities, deal hygiene, a weekly follow-up sweep, and a defensible roll-up forecast — including the case where the pipeline looks full but nothing closes. NOT statistical or scenario forecast modelling (that is `forecasting`), NOT sourcing prospects (that is `lead-gen`), NOT writing the outbound emails (that is `cold-outreach`), NOT the proposal or quote (that is `proposals`), NOT the post-close kickoff (that is `client-onboarding`).
Use when instrumenting product or web analytics — GA4/PostHog SDK wiring, event taxonomy, funnels, double-counted events, consent gating, PII scrubbing. NOT charting that data (that is dashboard), NOT choosing which metrics matter (that is kpi-framework), NOT experiment math (that is ab-testing), NOT cookie-policy text (that is gdpr-privacy).
Use when text must become a typed, schema-conformant object you can trust — pulling fields into a fixed JSON shape, extracting line items as typed records, classifying into enums, and building the Pydantic or Zod model plus the validate-and-retry loop. Covers extractors that throw parse errors, leak markdown fences, or fabricate a value where the field is absent instead of returning null. NOT getting the text out of a PDF, scan or DOCX first (that is `document-processing`), NOT general prompt craft untied to a schema (that is `prompt-engineering`).
Use when adapting an open-weight model to a target form or behavior — tone, output format, reasoning pattern — via LoRA/QLoRA or full fine-tuning with TRL SFTTrainer, then preference optimization (DPO/ORPO/KTO/GRPO), and for fine-tune vs prompt vs RAG. NOT adding facts to a model (that is rag); NOT the single-GPU Unsloth backend or GGUF export (that is unsloth).
Use when building or restructuring an LLM agent — provider adapter, tool calling, structured output, RAG, agent loop, eval gate, cost routing, tracing, MCP server — model-agnostic across OpenAI/Anthropic/Gemini/OSS so a model swap is a config change. NOT vector-store SQL alone (that is `postgresdb`) or service deployment (that is `deployment`).
Use when an already-running 02-DOCS/ wiki needs gardening judgment — what is worth capturing (default: nothing), where a loose note belongs, whether to split a bloated article or merge near-duplicates, how to link orphans back in, and what retires to _archive (never delete). NOT building or sweeping the wiki engine itself (that is `harness`).
Use when one prompt must give the same right answer across reruns, models, and pasted-in hostile input: forcing a fixed schema, picking the few-shot set, ordering the prompt blocks, or the inline cases you run while tuning. NOT the agent loop, tools, or retrieval (that is `building-agents`), NOT a standing CI eval harness (that is `agent-eval`).
Use when planning or running an equity round as a process: sizing the raise to a milestone, choosing post-money SAFE vs priced round, tiering investors by intro path, sequencing outreach for momentum, or reading a term sheet before signing. NOT the slide narrative (that is `pitch-deck`), NOT the cap-table or valuation math (that is `financial-model`).
Use when a team must decide what to measure before building anything — picking one north-star metric, separating leading input drivers from lagging outputs, adding guardrails so a number cannot be gamed, and setting a target that is not arbitrary. NOT the live dashboard that displays them (that is `dashboard`), NOT instrumenting the events (that is `analytics`), NOT the recurring board report (that is `reporting`).
Use when a support or sales bot on a live website must behave: persona/system prompt, grounding so it cannot invent prices or policy, jailbreak and injection defense, the human handoff, launch metrics and kill switch. NOT the agent loop or RAG index under it (that is `building-agents`), NOT a human answering one ticket (that is `customer-support`).
Coordinates bounded marketing work, ownership, timelines and delivery dependencies for SaaS teams.
Plans governed social, community and creator operations with clear platform, consent and owner boundaries.
Guides evidence-led SaaS SEO strategy, content and technical opportunity planning.
Plans developer marketing and DevRel work across technical audience, content and community context.
Frames self-serve activation, retention and expansion decisions for a SaaS product.
Plans SaaS event and field-marketing work with objectives, measurement and owner boundaries.
Guides account selection, tiering, cross-channel contracts and measurement for ABM programs.
Plans SaaS email and automation operations with deliverability, consent and lifecycle boundaries.
Guides SaaS product marketing, positioning and launch coordination from evidence to reviewable plans.
Guides client-facing marketing operations, quality gates and handoffs for accountable delivery.
Frames partnership and ecosystem decisions for SaaS with scope, evidence and ownership.
Plans communications and analyst-relations work while preserving approval and factual-evidence boundaries.
Builds an evidence-led sales proposal around a client’s stated needs, value and approval path.
Researches a prospect’s competitive context to prepare a factual sales strategy.
Creates a reviewable prospect-pipeline report from supplied, authorized evidence.
Plans follow-up sequences after a sales meeting with consent, timing and value boundaries.
Structures a human-led lead qualification conversation using BANT and MEDDIC evidence.
Prepares a factual, bounded brief for an authorized sales meeting.
Drafts consent-aware, personalized outreach options across channels for human review.
Organizes public company and firmographic evidence for account research.
Prepares evidence-based responses to sales objections for human review and conversation planning.
Maps an account’s decision process and stakeholders from authorized evidence.
Defines a testable sales ICP and account-selection criteria from business evidence.
Analyzes channel and video performance from user-supplied, authorized evidence.
Builds a testable ICP and buyer-persona hypothesis from supplied evidence.
Plans LinkedIn advertising decisions and measurement without configuring campaigns.
Develops a research plan for AI-search and generative-engine queries.
Structures a competitor traffic and authority assessment from authorized evidence.
Plans a community-presence approach with platform, community and human-review boundaries.
Analyzes supplied video-ad creative and produces reviewable improvement hypotheses.
Guides a backlink-profile assessment without accessing external SEO services.
Plans Search Console analysis and operational decisions without OAuth or property changes.
Structures a SERP analysis using user-supplied or authorized research evidence.
Plans a podcast editing workflow without installation, transcription calls or media processing.
Plans brand-mention monitoring and escalation criteria without provider API calls.
No local installation. No M11 login. Connect once. Broad task? Load 5–10 relevant skills and go. Precise task? Narrow through category, topic and tags.
The tunnel uses the same cards as the catalogue. Browse only as deep as needed — or load a broad bundle immediately.
SEO, Sales, Agents or another broad area → one bundle call → work.
Read-only access to published skills. Default 8, maximum 10 skills / 120,000 characters.
Compact two-skill starter: clarify positioning and choose a lead magnet. Use Marketing Launch for the broader eight-skill go-to-market workflow.
Build an evidence-led marketing plan from ICP and competition through positioning, campaigns, growth and measurement.
Diagnose architecture and context, plan agent-team responsibilities, then organize project context and session handoffs. Memory and cost-runtime reviews remain outside this pack.
Review the journey from landing page and lead capture through registration, first value and transparent upgrades.
Plan a campaign, draft its channel content and review the work against actual brand guidance.
Prioritize an editorial roadmap and plan how to launch and distribute it across suitable channels.
Understand customer needs, compare competitors and plan a community around real member value.
Choose a relevant lead magnet, then draft a permission-based nurture journey with entry, suppression and exit rules.
Define the API contract, then plan how to observe its latency, failures and retries. Guidance and checklist; no production changes.
Profile a dataset, choose and interpret statistical methods, then validate calculations and conclusions before sharing.
Define the target account, prioritize buying signals, plan a human LinkedIn engagement routine and prepare evidence-led responses to buyer concerns.
Plans developer marketing and DevRel work across technical audience, content and community context.
--- name: developer-marketing-ops description: "Developer marketing and developer relations for B2B SaaS with technical audiences. Use this skill when the buyer or user is a developer: documentation as a marketing surface, quickstarts and time-to-first-call, SDKs and sample apps, developer community and DevRel programs, open-source strategy, and technical content that survives engineer scrutiny. Also triggers on: developer marketing, DevRel, developer relations, developer experience, DX, docs, documentation, quickstart, SDK, API marketing, open source strategy, developer community, technical content, dev audience, hacker news, engineering blog." --- # Developer Marketing Operations ## Step 0 (always first): Load brand context **Before producing any deliverable, look for a `brand-context.md` file** in the user's project root (also check `./.claude/brand-context.md` and `./docs/brand-context.md`). It holds the company's ICP, positioning, messaging pillars, citable proof, voice, banned words, and compliance constraints. - **If it exists:** read it in full and treat it as binding for this run. Hand its contents to every specialist agent you route work to, alongside the task brief. Its "Rules for agents reading this file" section overrides an agent's own defaults. - **If it does not exist:** say so, point the user at the template ([`templates/brand-context.md`](../../templates/brand-context.md)), and offer to generate a filled draft by interviewing them or by reading their website and existing content. Then proceed with explicitly-labelled assumptions — never silently invented ones. **Non-negotiable regardless of which path applies:** do not invent customer names, metrics, funding, integrations, certifications, or outcomes. Only proof recorded in `brand-context.md` (or supplied directly in the request) may be used as fact. Where a claim would help but no evidence exists, emit a `[NEEDS INPUT: …]` marker in the deliverable rather than a plausible-sounding guess. --- ## What This Is Developer Marketing Operations markets to developers — an audience where most classic B2B tactics actively backfire. Gated PDFs, lead-capture forms in front of docs, and benefit-led copy without code all read as hostile here. This skill owns the artifacts a developer actually evaluates in an IDE, a terminal, or a repo, and hands channel execution to the existing acquisition skills. ## The Team: 1 Specialist Agent | # | Agent | File | What They Do | |---|-------|------|-------------| | 1 | Developer Audience Strategist | `agents/devmkt-developer-audience-strategist.md` | Owns documentation as a marketing surface, quickstart and time-to-first-successful-call design, SDK and sample-app strategy, open-source and community programs, DevRel motion design (talks, workshops, office hours), and technical content standards that survive engineer scrutiny. | ## How to Use ### Routing User Requests **Developer experience & docs** → Developer Audience Strategist - "Cut our time-to-first-successful-API-call" - "Audit our docs as a marketing surface" - "Design a quickstart that actually gets someone to hello world" - "What should our SDK and sample-app strategy be?" **Developer community & DevRel** → Developer Audience Strategist - "Design our DevRel program" - "Should we open-source this, and what does that commit us to?" - "Build a developer community motion that isn't astroturf" - "Why does our technical content get torn apart by engineers?" ### Working Method 1. **Load brand context first** (Step 0 above) and hand it to the specialist along with the brief. 2. **Route to the specialist** whose remit matches the request. Where a request straddles a boundary, name the boundary and route each half to its owner rather than answering both yourself. 3. **Produce the specialist's deliverable** in full, using only proof recorded in `brand-context.md` or supplied in the request. Emit `[NEEDS INPUT: …]` wherever evidence is missing rather than inventing it. 4. **Name the handoffs.** State explicitly which other skill picks up the next step, so work does not dead-end. **Boundaries this skill respects.** Scope is set by **artifact and audience, not channel**: this skill owns anything a developer evaluates in an IDE, terminal, or repo, and briefs channel execution out to the existing agents — `content-blog-strategist` still owns the blog program, `social-reddit-specialist` and the social skill still own community channels, and `seo-technical-auditor` still owns crawlability. It supplies the technical substance and the credibility bar; they run the surface. ## Output Standards - Every deliverable names its audience, its owner, and the decision it enables. - No invented customers, metrics, funding, certifications, or outcomes — `[NEEDS INPUT: …]` instead. - Cite real sources with links and read-dates when referencing external standards, platforms, or research; flag anything contested. - Where a recommendation depends on a number the company has not supplied (budget, headcount, current conversion rate), state the assumption in-line rather than burying it.
Plans developer marketing and DevRel work across technical audience, content and community context.
The complete original operating guide, source attribution and delivery limits.
Clarify the decision and evidence, apply the guide, then identify owners, approvals and unresolved questions.
Product context, target developer audience, evidence, approved channels and accountable owner.
Original documentation is published under the repository MIT license at the pinned revision. It is planning and operating guidance only. Referenced agents, scripts, systems, accounts, contacts and third-party services are not bundled or installed. Loading this source does not authorize messages, outreach, publishing, account changes, credential use, payment actions, deployment or execution.
Use Developer Marketing & DevRel Operations for [TASK]. Establish Product context, target developer audience, evidence, approved channels and accountable owner. Return a bounded, evidence-aware plan with open questions and approval points. Do not claim external execution or current facts without evidence.
Publishing, community outreach, event commitments or access to developer systems.
M11 added German routing, integrity records and action boundaries. Original documentation is published under the repository MIT license at the pinned revision. It is planning and operating guidance only. Referenced agents, scripts, systems, accounts, contacts and third-party services are not bundled or installed. Loading this source does not authorize messages, outreach, publishing, account changes, credential use, payment actions, deployment or execution.
MIT License Copyright (c) 2025 Shivaa Tripathi Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
No local installation · No M11 login
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