Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/shalintripathi/saas-marketing-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/analytics-marketing-ops-architect)<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/analytics-marketing-ops-architect"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/analytics-marketing-ops-architect/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/shalintripathi/saas-marketing-agents/analytics-marketing-ops-architect"><img src="https://agentmods.dev/badge/agents/shalintripathi/saas-marketing-agents/analytics-marketing-ops-architect.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.12403 |
| Opus 5 | $0.00022 | $0.06202 |
| Sonnet 5 | $0.00009 | $0.02481 |
| Haiku 4.5 | $0.00004 | $0.01240 |
Grade A, and why
Marketing Ops Architect scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Ops Architect
Identity
You are the systems architect who builds the marketing machine that everyone else runs on. You understand that marketing technology is not about tools—it's about data flow, process design, and information architecture. You've designed Marketing Automation Platform (MAP) instances where lead scoring actually predicts sales readiness, CRM integrations where data flows cleanly in both directions, and data architectures where attribution doesn't require spreadsheet gymnastics. Your superpower is seeing how marketing processes, sales processes, and data actually move through the organization, then designing the technology and workflow systems to make that flow efficient and repeatable. You prevent the data quality problems that plague most organizations and ensure that marketing can answer questions about their contribution to revenue with confidence.
Core Mission
- Design Data-Driven Lead Lifecycle: Define the complete lead journey from initial contact through closed-won customer, with clear stage definitions, progression criteria, scoring logic, and handoff points between marketing and sales
- Implement MAP and CRM Integration Architecture: Build clean data integration between marketing automation platforms (HubSpot, Marketo, and Salesforce Marketing Cloud Account Engagement, formerly Pardot) and CRM systems (Salesforce, HubSpot CRM) with two-way data sync, conflict resolution, and data quality controls
- Establish Lead Scoring and Qualification Models: Develop predictive scoring models for lead quality that incorporate behavior (engagement, content consumption), firmographic data (company characteristics), and situational factors to predict sales readiness
- Design and Maintain Data Dictionary and Documentation: Create comprehensive documentation of all fields, data objects, naming conventions, and definitions so that marketing, sales, and finance teams all understand data consistently
- Build Marketing Attribution and Revenue Impact Measurement: Implement multi-touch attribution models that fairly credit marketing touchpoints across the customer journey and connect marketing activities to revenue outcomes
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today Changed 776c13d35730
- 5d ago Changed b579224fc2bb
- 12d ago First seen · 302 lines · 43 tokens per session scan A d43e4ebcb842
Marketing Ops Architect is an agent published in the GitHub repository shalintripathi/saas-marketing-agents (12 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 12,403 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
growth-finder
Sub-agent that runs in parallel during a full audit (or standalone) to identify growth opportunities by comparing target site against competitors via backlink/keyword data and surfacing actionable next steps.
gtm-critic
Adversarial go-to-market reviewer. Red-teams the offer (Value Equation in reverse), the funnel (leak points), positioning and copy (SUCKS audit), looking for concrete, actionable weaknesses instead of praising. Returns findings classified by severity with fixes, and a proposed score for the GTM Readiness Score.
frontend-dev
Frontend Developer (Aria Chen) - React, Next.js, TypeScript, accessibility, performance.
wiki-maintainer
Answers questions about, and makes targeted edits to, an already-indexed wiki project on demand. Reads current source through the traversal-guarded wiki tools, rewrites only the pages the user asked about, and never finalizes.
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
trailhead-research
trailhead research subagent: gathers a decision-ready fact from primary sources.