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.
npx skills add shalintripathi/saas-marketing-agents --skill marketing-analyticsgit 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/skills/shalintripathi/saas-marketing-agents/marketing-analytics)<a href="https://agentmods.dev/skills/shalintripathi/saas-marketing-agents/marketing-analytics"><img src="https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/marketing-analytics/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/skills/shalintripathi/saas-marketing-agents/marketing-analytics"><img src="https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/marketing-analytics.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 | $0.00423 | $0.05873 |
| Opus 5 | $0.00211 | $0.02936 |
| Sonnet 5 | $0.00085 | $0.01175 |
| Haiku 4.5 | $0.00042 | $0.00587 |
Grade A, and why
marketing-analytics 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 2d ago.
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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Analytics
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), 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
Marketing Analytics brings together performance analysts, conversion rate optimization specialists, customer insights researchers, data storytellers, and marketing operations architects to transform data into decisions. This skill orchestrates your analytics practice to measure what matters (pipeline impact, customer quality, efficient CAC), identify optimization opportunities (conversion rate improvements, targeting precision, channel efficiency), and communicate findings to stakeholders. Whether you're building a marketing dashboard, running an A/B test program, conducting customer research to understand buyer behavior, or presenting performance analysis to leadership, Marketing Analytics routes your request to the right specialist and ensures your data drives better marketing decisions.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/analytics-conversion-rate-optimizer.md 36 KB
- agents/analytics-customer-insights-researcher.md 25 KB
- agents/analytics-data-storyteller.md 11 KB
- agents/analytics-demand-planner.md 20 KB
- agents/analytics-gtm-data-strategist.md 19 KB
- agents/analytics-marketing-ops-architect.md 59 KB
- agents/analytics-martech-stack-strategist.md 18 KB
- agents/analytics-performance-analyst.md 36 KB
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.
- 2d ago Changed · +8 lines · +111 tokens per session deb0dee875a2
- 4d ago Changed · +1 lines · +95 tokens per session 3d66832a240c
- 8d ago Changed · +28 tokens per session f83ae39ec050
- 12d ago First seen · 391 lines · 189 tokens per session scan A c2210fab278f
marketing-analytics is a skill published in the GitHub repository shalintripathi/saas-marketing-agents (12 stars, last pushed yesterday), licensed MIT. It adds 423 tokens to every session and 5,873 once invoked, about $0.0021 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.
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