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 jeremylongworth-source/AgentSkills --skill marketing-analytics-attributiongit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/marketing-analytics-attribution)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/marketing-analytics-attribution"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/marketing-analytics-attribution/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/jeremylongworth-source/agentskills/marketing-analytics-attribution"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/marketing-analytics-attribution.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 | $0.00069 | $0.00439 |
| Opus 5.5 | $0.00028 | $0.00176 |
| Sonnet 5.5 | $0.00014 | $0.00088 |
| Haiku 4.5 | $0.00007 | $0.00044 |
Grade A, and why
marketing-analytics-attribution 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 1mo 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.
What it actually says
Marketing Analytics Attribution
Core Workflow
- Define business questions before dashboards.
- Map the funnel and data sources: website, product, CRM, ad platforms, email, events, sales, billing, and support.
- Define events, properties, identities, UTMs, conversion goals, lifecycle stages, and revenue joins.
- Separate source-of-truth reporting from exploratory reporting.
- Validate tracking with test events, debug tools, CRM reconciliation, and known conversion paths.
- Report decisions, not vanity metrics.
Freshness Rule
Verify current GA4, Google Ads, and ad-platform documentation before prescribing event setup, conversion import, attribution windows, consent mode, enhanced conversions, or bidding optimization. Terminology changes: GA4 refers to important analytics events as key events, while Google Ads uses conversion actions and conversion goals for optimization/reporting.
Measurement Priorities
- Funnel: traffic, conversion, lead quality, opportunity creation, win rate, sales cycle, revenue, retention, expansion.
- Efficiency: CAC, payback, LTV/CAC, CPA, CPL, cost per opportunity, ROAS, margin-aware return.
- Attribution: use directional models; avoid pretending multi-touch reports are perfect truth.
- Experiments: define hypothesis, sample, metric, guardrail, minimum duration, success threshold, and action rule.
- Data quality: track missing UTMs, duplicate leads, offline conversions, consent gaps, bot traffic, and CRM stage drift.
Deliverable Shape
- Measurement questions
- Event/conversion schema
- UTM and source rules
- Dashboard outline
- Attribution assumptions
- Data QA checks
- Decision cadence
References
- Read
references/analytics-attribution-checklist.mdwhen designing or auditing marketing measurement.
What ships with it
2 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.
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.
- 1mo ago First seen · 43 lines · 69 tokens per session scan A 0454173e5f9d
marketing-analytics-attribution is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 17d ago), licensed MIT. It adds 69 tokens to every session and 439 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-03.
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