Digital Marketing Pro

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.

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.

Configure a tiered competitor alert system — per-competitor trigger thresholds across content, pricing, ads, social, ranking, and SERP changes, with critical/warning/info urgency routing, digest batching, and alert-fatigue guardrails — then send test alerts to verify Slack or email delivery. Triggers on "/digital-marketing-pro:competitor-alerts", "alert me when a competitor changes pricing", "set up competitor alerts", "too many competitor notifications", "tell me when competitors launch new ads". Requires baselines from /digital-marketing-pro:competitor-monitor and persists config via competitor-tracker.py; reads the brand profile for competitive context.

Turn one piece of content into a multi-channel repurposing plan — a derivative matrix targeting 10+ formats, full platform-adapted drafts, a publishing calendar, UTM-tagged links, and per-piece brand-voice scores; every derivative must pass the standalone test (own hook, own payoff) and the cut list records what failed it. Triggers on "/digital-marketing-pro:content-repurpose", "repurpose this blog post", "turn this webinar into social posts", "get more mileage out of this article", "atomize this whitepaper". Produces drafts and a schedule, not published posts. Reads the brand profile, channel style overrides, and platform specs.

Build a counter-narrative playbook responding to a competitor's positioning move — rebrand, category claim, aggressive campaign, price change, or partnership. Analyzes the move and its impact, selects a counter approach (direct counter, reframe, category counter, social proof, or zeitgeist) via narrative-mapper.py, and delivers a multi-channel response plan with content angles, ad concepts, PR angles, messaging guidelines, an urgency-calibrated timeline, and tracking metrics. Triggers on "/digital-marketing-pro:counter-narrative", "competitor just rebranded, how do we respond", "they are claiming a new category", "respond to their attack campaign", "counter a competitor price cut". Plans the response — it does not launch campaigns. Reads the brand profile and messaging guardrails.

Switch the active credential profile to a different client brand, validating each configured platform's API keys, env vars, and token expiry before anything runs — preventing cross-client data leaks and misrouted ad spend. Outputs a per-platform validation report plus a logged switch confirmation with audit trail. Triggers on "/digital-marketing-pro:credential-switch", "switch to the other client's account", "activate Acme's API keys", "are the right credentials active", "change which brand we're working on". Reads brand and credential profiles under ~/.claude-marketing/ and pairs with /digital-marketing-pro:client-onboarding when a profile is missing.

Evaluate and plan emerging marketing channels — voice and visual search, conversational and social commerce, communities, podcasts, and video — producing channel evaluation reports with 90-day pilot plans, setup checklists, and go/no-go recommendations. Advises and plans; it does not set platforms up for you. Triggers on "/digital-marketing-pro:emerging-channels", "should we open a TikTok Shop", "is voice search worth optimizing for", "plan a community launch on Discord", "evaluate podcast advertising for us". Reads the brand profile and industry benchmarks, and stamps any dollar figures through the benchmark book before they enter a plan.

Import brand guidelines — voice and tone rules, messaging, banned words and restrictions, channel styles, visual identity — and structure them into enforceable markdown files in the brand's guidelines layer, auto-classified by category, conflict-checked against the brand profile, and merged with existing rules rather than overwritten. Triggers on "/digital-marketing-pro:import-guidelines", "here's our brand voice guide", "add these banned words", "import our style guide", "save the rule that we never use jargon". Reads the active brand profile and existing guidelines manifest; saved guidelines are then applied automatically across all content-producing commands.

Turn a content topic, campaign, or existing piece into 3-5 named, briefable lead-magnet ideas cut from the brand's real assets and expertise, each graded on lead-gen power × build effort, with funnel-fit and delivery notes plus a not-recommended list that pre-empts the obvious-but-weak options. Triggers on "/digital-marketing-pro:lead-magnet-ideas", "lead magnet for this", "what should we give away", "opt-in ideas", "freebie for this campaign", "turn this into a lead magnet". Reads the brand profile for audience, expertise, and existing IP; routes onward to /digital-marketing-pro:email-sequence for the post-capture nurture or /digital-marketing-pro:funnel-architect when there is nowhere to send the lead yet.

Localize an entire campaign — emails, ads, social posts, landing pages, video scripts — for multiple markets, producing a deployment-ready per-market package: translations, transcreation options for emotional copy, Hofstede-based cultural adaptation notes, market-specific compliance additions, localized SEO and hreflang specs, RTL and locale formatting, quality scores, and a cross-market consistency report. Triggers on "/digital-marketing-pro:localize-campaign", "localize this campaign for Germany and Japan", "adapt these assets for new markets", "take the Q3 campaign multilingual", "prepare our launch for hi-IN and ar-SA". Prepares and scores assets but publishes nothing — each package ships with a deployment checklist. Reads the brand profile's language config and do-not-translate terms; for a single piece use /digital-marketing-pro:translate-content.

Track what AI engines (ChatGPT, Perplexity, Gemini, AI Overviews, Copilot) say about the brand, score responses against desired positioning, and flag misrepresentations, drift, and competitor narrative gains. Produces an alignment report, a narrative territory map, and a content strategy to correct AI perception, with snapshots persisted via geo-tracker.py for trend comparison. Triggers on "/digital-marketing-pro:narrative-tracker", "what is ChatGPT saying about us", "track our AI narrative", "is AI misrepresenting our brand", "are competitors gaining narrative ground". Reads the brand profile for reference positioning; recommends corrective content but does not publish it. Pairs with /digital-marketing-pro:narrative-landscape for competitor messaging territory.

Run a deep SEO audit of one URL across title/meta, headings, content depth, E-E-A-T, schema (with deprecation flags for HowTo, FAQ, SpecialAnnouncement), images, internal links, technical signals, and AI search readiness. Produces a scored /80 report with exact replacement title tags and meta descriptions, ready-to-paste JSON-LD, and optional competitor comparison. Triggers on "/digital-marketing-pro:page-seo-analysis", "analyze the SEO of this page", "why isn't this page ranking", "audit this URL before publish", "compare my page against competitor pages". Reads the brand profile and guidelines; analysis and recommendations only — nothing is changed on the site. For a site-wide view, pair with /digital-marketing-pro:seo-audit.

Pull live metrics from every connected analytics MCP into one cross-channel snapshot: KPI scoreboard with RAG status vs profile targets, period-over-period trends, industry benchmarks, top wins and concerns, and 3-5 recommended actions — then persist the snapshot via performance-monitor.py for trend history. Triggers on "/digital-marketing-pro:performance-check", "how are our marketing metrics", "pull current KPIs", "quick performance snapshot", "are we hitting our targets". Reads the brand profile for KPI targets and industry benchmarks; reports data gaps for unconnected platforms. Pairs with /digital-marketing-pro:performance-report, which turns these snapshots into the stakeholder narrative.

Send internal team notifications through a connected Slack or Intercom MCP — campaign status updates, performance alerts, and approval requests formatted by urgency tier (info/warning/critical with @here escalation), with inline campaign or approval context, call-to-action blocks, and a 24-hour alert-fatigue check on the target channel. Strictly internal team messaging, never customer outreach, and every send passes a mandatory approval gate with a formatted preview first. Triggers on "/digital-marketing-pro:send-notification", "ping the team that the campaign launched", "alert #marketing about the bounce-rate spike", "send an approval request to Slack", "notify leadership before EOD". Reads the brand profile and the channel's recent notification history.

Translate marketing content with automatic service routing per language pair, quality scoring across five dimensions (length ratio, formatting, key terms, placeholders, completeness), and a brand-voice check on the result; flags idioms, wordplay, and emotional CTAs for transcreation with 2-3 scored creative options plus back-translations. Triggers on "/digital-marketing-pro:translate-content", "translate this landing page into German", "localize this email for India", "transcreate our slogan", "does the translated version keep our brand voice". Reads the brand profile's do-not-translate terms, glossary, and formality preferences; executes via connected translation MCP servers.

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.

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.

Set up ongoing competitor monitoring — captures per-competitor baselines across content, pricing, ads, social, SEO, and SERP features, saves them via competitor-tracker.py, configures per-dimension scan schedules and alert rules, and produces an initial competitive intelligence brief with threat rankings. Triggers on "/digital-marketing-pro:competitor-monitor", "track our competitors over time", "watch competitor pricing pages", "set up competitor tracking", "detect when competitors change their site". Baselines power /digital-marketing-pro:competitor-alerts and share-of-voice trends. Reads the brand profile for competitive landscape context.

Scan the content library for decay — declining traffic, falling keyword positions, stale content, broken links, lost AI citations — scoring each URL 0-100 via creative-fatigue-predictor.py and ranking refreshes by recoverable revenue, with actionable refresh briefs and traffic-recovery estimates for top-priority tiers. Triggers on "/digital-marketing-pro:content-decay-scan", "which content is losing traffic", "find stale content to refresh", "our blog traffic keeps dropping", "prioritize content refreshes". Pulls performance data from Google Analytics/Search Console MCPs or exported CSVs; cross-reference causes with /digital-marketing-pro:seo-drift. Reads the brand profile for content strategy context.

Structured guidance for engineering growth systems — product-led growth motions, referral program design, viral loop mechanics, launch playbooks, retention loops, and affiliate programs — producing strategy documents, program specs, and spreadsheet-ready growth models. Recommends and designs; does not build product features or launch anything. Triggers on "/digital-marketing-pro:growth-engineering", "design a referral program", "how do we get a viral loop", "plan our Product Hunt launch", "reduce churn with re-engagement". Reads the brand profile, industry benchmarks, and campaign history; pairs with /digital-marketing-pro:cro for activation and onboarding optimization.

Baseline and interpret Google Search Console's AI Performance Report — combined AI Overviews + AI Mode impressions, cited pages, country and device mix (no click data; attribution stays in GA4) — from a user-supplied CSV export, with an in-SC AI opt-out recommendation and a gated quality scorecard. Triggers on "/digital-marketing-pro:gsc-ai-performance", "read the new GSC AI report", "baseline our AI search visibility", "how many AI Overviews impressions do we get", "should we opt out of AI results". Parses and archives exports via gsc-ai-performance.py, reconciles actuals against /digital-marketing-pro:aeo-audit probes, and feeds /digital-marketing-pro:seo-drift.

Plan influencer and creator marketing end to end — creator discovery and audience-authenticity vetting, campaign brief development, FTC and international disclosure compliance audits, contract and usage-rights frameworks, UGC strategy, and performance measurement (EMV, ROAS, brand lift). Advisory and planning only — it does not contact creators or publish anything. Triggers on "/digital-marketing-pro:influencer-creator", "find influencers for our launch", "are these sponsored posts FTC compliant", "how should we structure an influencer contract", "plan a UGC campaign". Reads the brand profile, guidelines, compliance rules, and campaign history via campaign-tracker.py before planning new work.

Audit a landing page across six conversion dimensions — above-fold clarity, trust signals, form friction, message match against the upstream ad or email, page speed, and mobile experience — each scored 1-10, rolled into an overall score benchmarked against industry averages, with the top 5 fixes ranked by expected conversion impact. Assessment and recommendations only; it does not edit the page. Triggers on "/digital-marketing-pro:landing-page-audit", "audit this landing page", "why isn't this page converting", "score our signup page", "does the page match the ad copy". Reads the brand profile, guidelines, custom templates, and agency SOPs before scoring.

Create and launch a paid ad campaign on Google, Meta, LinkedIn, or TikTok through the connected ad-platform MCP — campaign structure, audience targeting, bid strategy, negative targeting, creative quality scoring, compliance review, and a post-launch monitoring schedule. A mandatory execution gate shows the full spend summary and requires an explicit typed yes before anything goes live; budgets over brand thresholds force re-confirmation and every approval is recorded via approval-manager.py. Triggers on "/digital-marketing-pro:launch-ad-campaign", "launch the Google Ads campaign", "put these Meta ads live", "start the LinkedIn campaign tomorrow", "deploy our TikTok ads". Reads the brand profile's budget thresholds, guidelines, and agency SOPs; it is the paid-ads subset that /digital-marketing-pro:launch-campaign delegates to.

Score translated or localized content into one composite quality verdict — technical translation scoring (length ratio, formatting, do-not-translate terms, placeholders), content quality in the target language, brand voice consistency, and target-market compliance — classified as Publish Ready (85+), Native Speaker Review (70-84), or Re-translate (below 70) with specific, located fix suggestions per issue. Triggers on "/digital-marketing-pro:multilingual-score", "is this German translation ready to publish", "score this localized landing page", "did the translation keep our brand voice", "check compliance on the Japanese version". Runs the language-router, eval-runner, and brand-voice-scorer scripts, reads the brand profile's language config and do-not-translate list, and compares against the brand's multilingual baseline when past runs exist.

Turn marketing data into a stakeholder-ready performance report: executive summary, channel-by-channel KPI dashboard, trend analysis, anomaly alerts with root-cause hypotheses, and recommendations ranked by expected impact — formatted for an executive or tactical audience. Triggers on "/digital-marketing-pro:performance-report", "write the monthly performance report", "summarize campaign results for stakeholders", "why did performance change last quarter", "turn these metrics into a report". Consumes snapshots persisted by /digital-marketing-pro:performance-check rather than re-pulling platforms itself; reads the brand profile, custom templates, and agency SOPs. Hands deeper anomaly diagnosis to /digital-marketing-pro:anomaly-scan.

Run a multi-dimensional competitive teardown of 2-5 competitors — content strategy, SEO, paid ads, social, AI answer-engine visibility, and pricing/positioning — producing a competitor overview matrix, per-competitor SWOT, gap analysis, and strategic recommendations prioritized by opportunity size. Triggers on "/digital-marketing-pro:competitor-analysis", "analyze our competitors", "how do we stack up against X", "competitive landscape report", "what are competitors doing that we aren't". Point-in-time analysis, not ongoing tracking — pair with /digital-marketing-pro:competitor-monitor for that. Reads the brand profile, guidelines, and compliance rules.

Orchestrate a full marketing engagement through the 12-Part methodology — Stone vs Opinion intake, external research, Four Core Documents, client validation, Decision Matrix v2 re-runs, growth planning, channel fan-out, and the continuous-improvement loop — with checkpointed, resumable state at every part. Triggers on "/digital-marketing-pro:engagement-workflow", "start a new engagement", "what part of the engagement are we on", "apply the decision matrix", "advance to the next part". Reads and writes engagement state via engagement-state.py only, and dispatches to /digital-marketing-pro:four-core-documents, growth-plan, yearly-planner, and continuous-improvement-loop.

Design an executive marketing dashboard as a build-ready specification — 5-7 north-star metrics with rationale, metric hierarchy, chart choices, alert thresholds, data-source mapping, wireframe layout, drill-down structure, and a mobile variant. It designs the dashboard; it does not build or connect a live one. Triggers on "/digital-marketing-pro:executive-dashboard", "design a CMO dashboard", "what metrics should the board see", "our exec report is too noisy", "create a leadership reporting view". Reads the brand profile and guidelines; pairs with /digital-marketing-pro:exec-summary for the written companion narrative.

Produce Part 3 of the 12-Part engagement: the four strategic-spine documents across 61 steps — 3.1 Business & SBU Analysis, 3.2 Segmentation Framework, 3.3 Brand Positioning & Communications, 3.4 DMFlow — with --doc single-document runs, --view v2 re-runs, and a --combined executive stitch. Triggers on "/digital-marketing-pro:four-core-documents", "produce the four core documents", "run part 3 of the engagement", "generate the strategic spine", "re-run positioning as v2". Requires an initialised engagement with Part 1 complete; reads Stone facts, Part 2 research, and the brand profile, and feeds /digital-marketing-pro:growth-plan.

Generate an intelligence briefing from the brand's compound intelligence base — total learnings with confidence distribution, cross-agent patterns by channel, audience, and objective, actionable playbooks synthesized from proven strategies, stale learnings flagged for revalidation, and a 0-100 compound intelligence maturity score. Triggers on "/digital-marketing-pro:intelligence-report", "what have we learned across campaigns", "summarize our marketing intelligence", "generate a playbook for the product launch", "where are our knowledge gaps". Reads the brand profile and pulls stats, patterns, and playbooks from intelligence-graph.py; suited to quarterly planning, strategy reviews, and onboarding.

Map competitor positioning across 3-5 narrative dimensions to find crowded clusters and unclaimed gaps, then score each gap by customer desirability times brand credibility. Produces a landscape map, ranked gap analysis, a recommended positioning territory, and a 30/60/90-day messaging plan to claim it. Triggers on "/digital-marketing-pro:narrative-landscape", "map the competitive narrative landscape", "what positioning gaps can we own", "where do competitors cluster", "find us a differentiated position". Reads the brand profile for current positioning and voice; analysis and strategy only — no messaging is published. Pairs with /digital-marketing-pro:narrative-tracker for what AI engines say about the brand.

Send a targeted email campaign through a connected SendGrid, Klaviyo, Customer.io, Brevo, or Mailchimp MCP — subject-line and spam scoring, personalization with fallbacks, A/B variants, CAN-SPAM/GDPR/CASL compliance checks, a test send you confirm, then the full send with deliverability monitoring and early engagement snapshots. No email leaves without the mandatory execution gate: a campaign summary with recipient count and risk tier (medium/high/critical by list size) that you must explicitly approve. Triggers on "/digital-marketing-pro:send-email-campaign", "send this newsletter to the active list", "deploy the Q1 announcement email", "launch the promo email with two subject lines", "email this segment tomorrow at 9am". Reads the brand profile, guidelines, and platform publishing specs.

Design marketing automation programs — end-to-end workflow architecture, lead scoring models with MQL/SQL thresholds, nurture and drip sequences, behavioral triggers, lifecycle stage frameworks, deliverability and compliance automation, and MAP platform selection or migration plans — delivered as workflow maps, scoring rubrics, sequence plans, and audits. Triggers on "/digital-marketing-pro:marketing-automation", "build a lead scoring model", "design a welcome nurture sequence", "our contacts get too many automated emails", "should we migrate from Mailchimp to HubSpot". Produces designs and audit findings, not live platform changes. Reads the brand profile and compliance rules; its lead-scoring framework is the one /digital-marketing-pro:lead-import applies when importing leads.

Design a cross-platform retargeting playbook — funnel-stage audience segments with recency windows, creative sequencing per segment, frequency caps, exclusion lists, budget allocation, dynamic product-feed setup, KPI-based optimization triggers, and a 30/60/90-day roadmap. Triggers on "/digital-marketing-pro:retargeting-strategy", "plan our remarketing campaigns", "cart abandoners aren't converting", "how should we sequence retargeting ads", "set frequency caps across Meta and Google". Reads the brand profile and past campaign performance via campaign-tracker.py; it produces the strategy document and tracking checklist — it does not launch or modify live campaigns.

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.

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.

Full reputation playbook: FTC-compliant review generation, negative-review response frameworks, 3-tier crisis communication with a 72-hour severe-crisis timeline, 4-layer brand safety assessment, sentiment monitoring design, and 30/60/90-day recovery plans — delivered as ready-to-use plans, drafted responses, and audits. Triggers on "/digital-marketing-pro:reputation-management", "we're getting hit with negative reviews", "prepare a crisis communication plan", "how do we get more Google reviews", "someone is spreading misinformation about us". Reads the brand profile, guidelines, and compliance rules; it plans and drafts — it does not post responses or monitor platforms itself. For a single review reply, /digital-marketing-pro:review-response is the focused sibling.

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.

Design a structured ad creative testing playbook — prioritized variable matrix, isolated test grid, script-computed sample sizes and minimum budgets per variant, holdout control design, iteration cadence, and winner selection criteria. Plans the testing program; it does not launch or edit live ads. Triggers on "/digital-marketing-pro:creative-testing-framework", "design an A/B test for our ads", "our ad creatives fatigue too fast", "build a creative testing roadmap", "how many conversions per variant do we need". Reads the brand profile and guidelines, and pairs with /digital-marketing-pro:c2pa-metadata for AI-generated variants headed to EU placements.

Run Part 12 of the engagement methodology — the continuous improvement loop that aggregates quarterly-review, customer-feedback, competitive, and operating signals into a Quarterly Product & Offering Improvement Brief for business leadership, plus fast 1-3 page ad-hoc briefs when a significant signal lands mid-quarter. Triggers on "/digital-marketing-pro:continuous-improvement-loop", "run part 12", "produce the quarterly improvement brief", "aggregate this quarter's signals", "we need a fast read on this competitor move". Flags v2.x update-back triggers but never auto-executes them. Reads monthly reports, signals.jsonl, /digital-marketing-pro:competitor-monitor outputs, and the Living Project Instruction File.