indranilbanerjee/digital-marketing-pro

共 30 个 Skill。

ab-test-plan

indranilbanerjee/digital-marketing-pro856

ab-test-plan

Design a statistically rigorous A/B or multivariate test plan — If/Then/Because hypothesis, control and variant specs, required sample size per variant (absolute vs relative MDE via sample-size-calculator.py), test duration, guardrail metrics, stopping rules, and go/no-go decision criteria. Triggers on "/digital-marketing-pro:ab-test-plan", "set up an A/B test", "how long should my test run", "calculate sample size for an experiment", "is this test result significant". Reads the brand profile and past campaign-tracker results to avoid re-testing validated hypotheses; finished tests are evaluated with significance-tester.py by the cro-specialist agent.

测试

ad-creative

indranilbanerjee/digital-marketing-pro856

ad-creative

Generate 3-5 ad copy variations per platform — headlines, descriptions, and CTAs formatted to Google, Meta, LinkedIn, TikTok, X, and Pinterest specs — each scored 1-10 with policy-compliance flags, A/B testing groupings, and a message-match check against the landing page. Triggers on "/digital-marketing-pro:ad-creative", "write ad copy for Meta", "give me RSA headline variations", "we need LinkedIn ad copy", "draft TikTok ad creative". Reads the brand profile, guidelines, and compliance rules; routes video ad scripts to /digital-marketing-pro:video-script and gates AI-generated visuals for EU campaigns through /digital-marketing-pro:c2pa-metadata and /digital-marketing-pro:check.

测试

add-integration

indranilbanerjee/digital-marketing-pro856

add-integration

Walk through adding a custom MCP server integration to the plugin — searches npm for an existing MCP package (or scaffolds a custom server from the plugin's guide), generates the exact .mcp.json entry, sets up environment-variable credentials, tests connectivity, and documents the tools the new server exposes. Triggers on "/digital-marketing-pro:add-integration", "connect Ahrefs to the plugin", "add a new MCP server", "integrate our internal API", "hook up Stripe data". Reads the brand profile and agency credential profiles at ~/.claude-marketing/credentials/ to map client-specific keys; custom builds follow skills/context-engine/custom-mcp-guide.md.

测试

aeo-audit

indranilbanerjee/digital-marketing-pro856

aeo-audit

Audit how a brand appears across the 6 canonical AI answer surfaces — ChatGPT, Perplexity, Google AI Mode, AI Overviews, Gemini, Copilot — probing 10-25 queries into a numbered output bundle with per-platform visibility scorecards, citation-accuracy checks, a competitor matrix, content gaps, and an optimization playbook behind a four-gate quality scorecard. Triggers on "/digital-marketing-pro:aeo-audit", "does ChatGPT know about our brand", "check our AI search visibility", "how does Perplexity describe us", "are we showing up in AI Overviews". Reads the brand profile; reconciles probes against GSC actuals via /digital-marketing-pro:gsc-ai-performance and defines the AI-visibility scoring standard reused by geo-monitor and share-of-voice.

AI 与智能体

aeo-geo

indranilbanerjee/digital-marketing-pro856

aeo-geo

Strategy module for Answer Engine / Generative Engine Optimization — audits AI visibility, restructures content for citation, runs entity-consistency checks across Knowledge Graph, Wikidata, Wikipedia, Crunchbase, and LinkedIn, and produces JSON-LD schema specs, monitoring frameworks, and a 90-day LLM content strategy. Triggers on "/digital-marketing-pro:aeo-geo", "how do we get cited by AI", "optimize for AI Overviews", "fix our entity consistency", "do we need llms.txt". Reads the brand profile, compliance rules, and industry benchmarks; its measurement counterpart is /digital-marketing-pro:aeo-audit, with GSC actuals via /digital-marketing-pro:gsc-ai-performance.

AI 与智能体

agency-dashboard

indranilbanerjee/digital-marketing-pro856

agency-dashboard

Generate a portfolio-level dashboard across ALL client brands — per-client RAG health scores, campaign activity, budget pacing, aggregate KPIs, team utilization, pending approvals, upcoming deadlines, and an alerts panel — built for agency standups and weekly reviews. Triggers on "/digital-marketing-pro:agency-dashboard", "how are all our clients doing", "portfolio health check", "budget pacing across accounts", "which accounts are at risk". Enumerates every brand under ~/.claude-marketing/brands/ and pulls data via campaign-tracker.py, execution-tracker.py, and team-manager.py; drill into a single client with /digital-marketing-pro:performance-report or /digital-marketing-pro:client-report.

AI 与智能体

agent-readiness-audit

indranilbanerjee/digital-marketing-pro856

agent-readiness-audit

Audit whether AI agents and AI crawlers can actually use a site — robots.txt rules per AI crawler token (OpenAI, Anthropic and Perplexity bots, Google-Extended, Applebot-Extended), Product/Offer/Organization/FAQ JSON-LD, whether main content is in the no-JavaScript server HTML, Merchant Center feed completeness incl. native_commerce checkout eligibility and conversational attributes, an optional agentic-commerce feed, and an optional experimental WebMCP check. Triggers on "/digital-marketing-pro:agent-readiness-audit", "can AI agents use our site", "are we blocking GPTBot or ClaudeBot", "is our product feed ready for AI Mode shopping", "run an agent-readiness check". Runs agent-readiness-audit.py offline on exports (network only with --fetch) and never recommends llms.txt for Google.

浏览器自动化

analytics-insights

indranilbanerjee/digital-marketing-pro856

analytics-insights

Marketing measurement module — builds KPI trees per business model, reporting templates (weekly, monthly, QBR, campaign), anomaly root-cause diagnosis, MMM and incrementality guidance, dark-social tracking, and privacy-first cookieless measurement architecture, including the GA4 AI Assistant channel group for attributing AI-referred traffic. Triggers on "/digital-marketing-pro:analytics-insights", "why did traffic drop", "define our KPIs", "design an executive dashboard", "can we do marketing mix modeling". Reads the brand profile, industry benchmarks, and campaign history; pairs with /digital-marketing-pro:gsc-ai-performance and /digital-marketing-pro:aeo-audit to triangulate AI-surface impressions against actual traffic.

数据库与数据

anomaly-scan

indranilbanerjee/digital-marketing-pro856

anomaly-scan

Scan all connected marketing platforms for statistically significant deviations from stored baselines — traffic drops, CPA spikes, deliverability collapse, budget overruns, or unexpected wins — classified critical/warning/info with probable causes, correlation to recent changes, and recommended actions. Triggers on "/digital-marketing-pro:anomaly-scan", "why did our CPA spike", "did anything weird happen this week", "check for anomalies", "our conversions suddenly dropped". Runs performance-monitor.py for baselines and detection, correlates flags against execution-tracker.py history and the diagnostic framework in skills/analytics-insights/anomaly-diagnosis.md, and persists critical findings as insights via campaign-tracker.py. Reads the brand profile.

数据库与数据

attribution-model

indranilbanerjee/digital-marketing-pro856

attribution-model

Design a multi-touch attribution strategy — recommends the best-fit model for the business's sales cycle and data maturity, defines credit-distribution rules and lookback windows, maps platform-specific setup (GA4, HubSpot, Salesforce, warehouse), and documents tracking gaps and known blind spots. Triggers on "/digital-marketing-pro:attribution-model", "set up multi-touch attribution", "which attribution model should we use", "configure GA4 attribution", "how should we credit channels for conversions". Reads the brand profile and consumes the canonical model taxonomy in skills/funnel-architect/attribution-models.md; to run the models against real conversion data, pair with /digital-marketing-pro:attribution-report.

AI 与智能体

attribution-report

indranilbanerjee/digital-marketing-pro856

attribution-report

Run multi-touch attribution analysis on real conversion-path data — applies two or more models side-by-side (first-touch, last-touch, linear, time-decay, position-based, data-driven), computes per-channel attributed revenue and ROAS, assisted-conversion ratios, path-length and time-to-conversion distributions, and budget reallocation recommendations. Triggers on "/digital-marketing-pro:attribution-report", "which channels actually drive revenue", "compare first-touch vs last-touch", "run an attribution analysis", "is paid social undervalued". Pulls journeys from Google Analytics, Google Ads, Meta, and CRM MCPs and includes GA4's AI Assistant channel; model definitions come from skills/funnel-architect/attribution-models.md, strategy design from /digital-marketing-pro:attribution-model.

数据库与数据

audience-intelligence

indranilbanerjee/digital-marketing-pro856

audience-intelligence

Audience research module — builds six-dimension buyer personas (demographic, psychographic, behavioral, need-state, information, decision), Jobs-to-Be-Done maps, RFM/behavioral/lifecycle segmentation models, anti-personas with exclusion criteria, B2B buying-committee maps, and lookalike seed specs. Triggers on "/digital-marketing-pro:audience-intelligence", "who are our customers", "build buyer personas", "segment our audience", "run a JTBD analysis". Reads the brand profile, industry benchmarks, and campaign history, and works from CRM/survey/analytics data when supplied — or labels hypothesis personas explicitly when data is thin. For a single quick persona document, /digital-marketing-pro:audience-profile is the lighter sibling.

数据库与数据

audience-profile

indranilbanerjee/digital-marketing-pro856

audience-profile

Build a named, narrative buyer persona document — demographic snapshot, psychographic drivers, jobs-to-be-done, day-in-the-life scenario, buyer journey map, objections with counter-messaging, and content/channel preferences — for the 2-4 personas a brand actually needs. Triggers on "/digital-marketing-pro:audience-profile", "create a buyer persona", "profile our target customer", "who is our ideal customer", "map the buyer journey for this segment". Reads the brand profile, guidelines, and any customer data supplied (surveys, CRM exports, analytics demographics); run by the marketing-strategist agent. For the deeper research module — segmentation, anti-personas, buying committees — see /digital-marketing-pro:audience-intelligence.

数据库与数据

autopilot-status

indranilbanerjee/digital-marketing-pro856

autopilot-status

Campaign autopilot operations dashboard — 0-100 health scores for all active campaigns, a chronological log of auto-corrections taken (bid, budget, audience, creative, pause) with before/after metrics, the current guardrail rule table, campaigns escalated for human attention ranked by urgency, and estimated savings from automated interventions. Triggers on "/digital-marketing-pro:autopilot-status", "how is autopilot doing", "what did the autopilot change", "which campaigns need my attention", "show guardrail settings". Runs campaign-health-monitor.py for health scores, corrections history, and the savings report; reads the brand profile for KPI targets, naming conventions, and budget constraints.

AI 与智能体

backlink-gap

indranilbanerjee/digital-marketing-pro856

backlink-gap

Find referring domains that link to your competitors but not to you, ranked by an outreach-priority score (0.40 DR + 0.25 link-overlap + 0.20 traffic + 0.15 topical relevance) — outputs a four-gate quality scorecard, a 30-prospect outreach shortlist, broken-link candidates, and pre-filled outreach templates. Triggers on "/digital-marketing-pro:backlink-gap", "where are competitors getting links we aren't", "plan a link-building campaign", "quarterly backlink audit", "first 50 link targets for a new client". Consumes backlink CSV exports from the brand's connected backlink MCP, runs scripts/backlink_gap.py, reads the brand profile for DR thresholds and voice, and hands off to /digital-marketing-pro:digital-pr and /digital-marketing-pro:pr-pitch.

AI 与智能体

brand-setup

indranilbanerjee/digital-marketing-pro856

brand-setup

Create or update the brand profile every other skill reads — a quick 5-question or full 17-question interactive setup capturing identity, business model, industry and compliance markets, 4-dimension voice scales, channels, goals, and competitors, saved to ~/.claude-marketing/brands/{slug}/profile.json via scripts/setup.py. Triggers on "/digital-marketing-pro:brand-setup", "set up a new brand", "onboard a new client", "switch to another brand", "update our brand voice". Also handles brand switching (updates _active-brand.json) and field-level profile edits; run this first — all marketing skills auto-apply the resulting profile, voice samples, and compliance rules.

AI 与智能体

budget-optimizer

indranilbanerjee/digital-marketing-pro856

budget-optimizer

Reallocate marketing spend across channels using performance data and diminishing-returns modeling — produces a current-vs-optimized allocation table, projected ROI ranges with confidence intervals, a phased 4-8 week reallocation timeline, and a 10-15% testing reserve. Recommends shifts only; it never changes spend on any platform. Triggers on "/digital-marketing-pro:budget-optimizer", "optimize my marketing budget", "which channels should get more spend", "reallocate budget based on ROAS", "is our channel split right". Reads the brand profile and guidelines, runs scripts/budget-optimizer.py, and pairs with /digital-marketing-pro:budget-tracker for in-flight pacing.

测试

budget-tracker

indranilbanerjee/digital-marketing-pro856

budget-tracker

Track advertising spend pacing in real time across connected ad platforms (Google Ads, Meta, LinkedIn, TikTok) — produces a budget dashboard with daily burn rates, end-of-period projections, overspend/underspend alerts, and dollar-specific reallocation recommendations backed by CPA/ROAS context. Monitors and recommends only; it never edits platform budgets. Triggers on "/digital-marketing-pro:budget-tracker", "are we overspending this month", "how is our ad budget pacing", "track spend across platforms", "will we blow through the budget cap". Reads budget targets from the brand profile, runs scripts/ad-budget-pacer.py, and saves snapshots for trend history; pairs with /digital-marketing-pro:budget-optimizer.

AI 与智能体

c2pa-metadata

indranilbanerjee/digital-marketing-pro856

c2pa-metadata

Embed a C2PA provenance manifest into an AI-generated marketing asset (PNG, JPG, WebP, GIF, TIFF, MP4, MOV, WebM, MP3, WAV, PDF) via scripts/embed-c2pa.py — produces a signed copy of the file carrying IPTC digital-source-type AI claims, an optional c2pa.ai-disclosure assertion for EU AI Act Article 50 (applicable 2 Aug 2026), and a JSON status report. Triggers on "/digital-marketing-pro:c2pa-metadata", "sign this AI image for EU compliance", "add content credentials to this asset", "embed provenance metadata", "mark this video as AI-generated". Uses a self-signed dev certificate unless --signing-cert/--signing-key are supplied; pairs with /digital-marketing-pro:check, which verifies manifests pre-publish.

文档与办公

campaign-audit

indranilbanerjee/digital-marketing-pro856

campaign-audit

Inventory and score everything currently running for a brand across paid search, paid social, email, organic, SEO, AEO/GEO, CRM, and analytics — produces a dated audit document with a 4-tier triage (healthy / quick win / strategic gap / red flag), a quick-wins backlog, and a compliance posture section. Strictly read-only: it never pauses, edits, or launches anything. Triggers on "/digital-marketing-pro:campaign-audit", "what's currently running for this brand", "audit our existing campaigns", "we just inherited this account", "where is budget leaking". Requires a validated brand profile (run validate-profile first); missing connectors degrade gracefully into findings. Feeds /digital-marketing-pro:campaign-plan and pairs with /digital-marketing-pro:performance-check.

数据库与数据

campaign-orchestrator

indranilbanerjee/digital-marketing-pro856

campaign-orchestrator

Full campaign-lifecycle module — produces campaign briefs, budget allocations via three models (70/20/10, efficiency-ranked, funnel-weighted), channel-mix and media plans, UTM taxonomies with governance rules, launch checklists, ABM plans, and post-mortem reports. Plans and documents; it does not launch or edit live campaigns. Triggers on "/digital-marketing-pro:campaign-orchestrator", "build a media plan", "how should we split budget across channels", "set up UTM naming conventions", "run a post-mortem on the campaign". Reads the brand profile, guidelines, and campaign history via campaign-tracker.py; its reference docs are consumed by /digital-marketing-pro:campaign-plan rather than duplicated.

AI 与智能体

campaign-plan

indranilbanerjee/digital-marketing-pro856

campaign-plan

Generate a complete multi-channel campaign plan document — SMART objectives, audience segments with targeting criteria, channel mix with rationale, a budget allocation table with reach/cost estimates, a phased timeline from pre-launch to wrap-up, a KPI framework, and a risk register. Plans only; it does not launch or modify campaigns. Triggers on "/digital-marketing-pro:campaign-plan", "plan a campaign for our product launch", "build the Q3 campaign plan", "what channels and budget for lead gen", "draft a campaign timeline with KPIs". Reads the brand profile, guidelines, and agency SOPs, and reuses the /digital-marketing-pro:campaign-orchestrator reference docs for planning frameworks instead of re-deriving them.

AI 与智能体

campaign-status

indranilbanerjee/digital-marketing-pro856

campaign-status

Unified status dashboard for every tracked campaign across connected platforms — produces a summary table with health indicators, live spend and performance metrics, a 7-day execution history, pending approvals with age, KPI variance classification (on track / at risk / behind), flagged issues, and next scheduled actions. Reports only; it changes nothing on any platform. Triggers on "/digital-marketing-pro:campaign-status", "what campaigns are running right now", "any failed executions or stuck approvals", "status of the Q1-Launch campaign", "which campaigns are behind target". Reads the brand's campaign registry, execution log, and approval queue via campaign-tracker.py, execution-tracker.py, and approval-manager.py, plus live metrics from connected platform MCPs.

项目与协作

case-study-plan

indranilbanerjee/digital-marketing-pro856

case-study-plan

Build a complete case-study creation blueprint — a Challenge-Solution-Results narrative framework, 15-20 client interview questions plus 10 internal-team questions, a data-visualization plan, format specifications (PDF, web page, slide deck, video script outline, social snippets, sales one-pager), a distribution strategy, a permission/approval checklist, and a draft executive summary. Plans the case study; it does not produce the finished designed asset. Triggers on "/digital-marketing-pro:case-study-plan", "turn this client win into a case study", "what should we ask the client in the interview", "plan a success story for sales enablement", "case study formats and distribution plan". Reads the brand profile, guidelines, custom templates, and agency SOPs.

文档与办公

check

indranilbanerjee/digital-marketing-pro856

check

Run the unified pre-publish quality gate on marketing content — wraps scripts/eval-runner.py to score hallucination risk, claim substantiation (with --evidence), brand-voice fit (with --brand), structure (with --schema), content quality, and readability, plus a C2PA provenance check for AI assets in EU-targeted campaigns; returns a composite score with a PASS / WARN / BLOCKED decision and per-issue fix suggestions. Reports only — it never edits the content. Triggers on "/digital-marketing-pro:check", "is this safe to publish", "run a hallucination check on this draft", "validate this copy against the brand voice", "pre-publish quality gate". Resolves the active brand profile automatically; pairs with /digital-marketing-pro:c2pa-metadata to fix missing manifests.

项目与协作

churn-risk

indranilbanerjee/digital-marketing-pro856

churn-risk

Score customer segments for churn risk from behavioral signals — email engagement decline, purchase recency, usage drops, support sentiment — producing a 0-100 risk scorecard with four tiers, per-tier intervention playbooks (actions, timing windows, channels, messaging), LTV-at-risk totals, and retention-ROI prioritization. Assesses and recommends; it does not send outreach or launch campaigns. Triggers on "/digital-marketing-pro:churn-risk", "which customers are about to churn", "score our segments for churn risk", "email engagement is dropping, who is at risk", "build a retention intervention plan". Pulls behavioral data from a connected CRM MCP (Salesforce or HubSpot) or user-provided exports, runs scripts/churn-predictor.py, and reads the brand profile for lifecycle context.

AI 与智能体

client-onboarding

indranilbanerjee/digital-marketing-pro856

client-onboarding

Generate a complete onboarding package for a new marketing client — kickoff meeting agenda, 20-30 question discovery questionnaire, stakeholder map with RACI matrix, platform-by-platform access checklist, 30-60-90 day milestone plan, communication cadence, escalation protocol, welcome email template, internal team brief, risk register, and a day-by-day first-week action plan. Triggers on "/digital-marketing-pro:client-onboarding", "we just signed a new client", "build a kickoff agenda and discovery questionnaire", "30-60-90 day plan for the new account", "what access do we need from the client". Reads the brand profile, guidelines, custom templates, and agency SOPs so the package matches house process.

AI 与智能体

client-proposal

indranilbanerjee/digital-marketing-pro856

client-proposal

Draft a professional agency proposal or pitch document for a prospective client — executive summary, situation analysis, scope of services with a deliverables matrix, KPI targets with baselines and stretch goals, 2-3 pricing options, team bio structure, case-study placeholders, terms outline, and next steps, written from the agency's perspective. Triggers on "/digital-marketing-pro:client-proposal", "write a proposal for this prospect", "scope of work for a 6-month retainer", "respond to this RFP", "pitch deck outline with pricing tiers". Loads the agency's own brand profile (not the client's), plus custom templates and agency SOPs; industry benchmarks inform the KPI and pricing sections.

AI 与智能体

client-report

indranilbanerjee/digital-marketing-pro856

client-report

Generate a white-labeled client report in agency voice — weekly pulse, monthly review, or QBR — with a KPI scorecard vs targets and comparison period, channel breakdowns, top wins with attribution, root-cause analysis of misses, 3-5 strategic recommendations, and budget efficiency. Requires explicit approval before any external send; only then can it deliver via connected Slack, email, or Google Sheets MCPs and log the delivery. Triggers on "/digital-marketing-pro:client-report", "prepare the monthly report for the client", "build the QBR for this account", "send the weekly performance pulse", "white-labeled performance report". Reads the brand profile and pulls data via campaign-tracker.py, execution-tracker.py, and connected platform MCPs; formats via report-generator.py.

项目与协作

client-validation-document

indranilbanerjee/digital-marketing-pro856

client-validation-document

Produce the Part 5 Client Validation Document — the one true stop of the 12-Part engagement where unbiased v1 findings from Parts 2-4 are compiled into 12-25 evidence-cited finding blocks, each awaiting an ACCEPT / REJECT / EDIT / DEFER client decision, plus a paired JSON response template. Recorded responses feed the Part 6 Decision Matrix (engagement-state.py) to determine v2 re-runs. Triggers on "/digital-marketing-pro:client-validation-document", "prepare v1 findings for client review", "run part 5 client validation", "the one true stop", "record the client's validation responses". Requires Parts 3-4 marked completed in _engagement.json; reads the eight v1 core documents; pairs with /digital-marketing-pro:engagement-workflow and /digital-marketing-pro:four-core-documents.

AI 与智能体